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The efficacy of and mechanisms behind the widespread use of lower leg compression as an ergogenic aid to improve running performance are unknown. The purpose of this study was to examine whether or not wearing graduated lower leg compression sleeves during exercise evokes changes in running economy (RE) perhaps due to altered gait mechanics. Sixteen highly-trained male distance runners completed two separate RE tests during a single laboratory session, including a randomized treatment trial of graduated calf compression sleeves (CS; 15-20 mmHg) and a control trial (CON) without compression sleeves. RE was determined by measuring oxygen consumption at three constant submaximal speeds of 233, 268, and 300 m·min-1 on a treadmill. Running mechanics were measured during the last 30 seconds of each four-minute stage of the RE test via wireless tri-axial 10g accelerometer devices attached to the top of each shoe. Ground contact time (tc), swing time (tsw), step frequency (SF), and step length (SL) were determined from accelerometric output corresponding to foot strike and toe-off events. Gait variability was calculated as the standard deviation of a given gait variable for an individual during the last 30 s of each stage. There were no differences in VO2 or kinematic variables between CON and CS trials at any of the speeds. Wearing lower leg compression does not alter the energetics of running at submaximal speeds through changes in running mechanics or other means. However, it appears that the individual response to wearing lower leg compression varies greatly and warrants further examination.
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Lower-Leg Compression, Running Mechanics,
and Economy in Trained Distance Runners
Abigail S.L. Stickford, Robert F. Chapman, Jeanne D. Johnston, and Joel M. Stager
The efcacy of and mechanisms behind the widespread use of lower-leg compression as an ergogenic aid to improve running
performance are unknown. The purpose of this study was to examine whether wearing graduated lower-leg compression sleeves
during exercise evokes changes in running economy (RE), perhaps due to altered gait mechanics. Sixteen highly trained male
distance runners completed 2 separate RE tests during a single laboratory session, including a randomized-treatment trial of
graduated calf-compression sleeves (CS; 15–20 mm Hg) and a control trial (CON) without compression sleeves. RE was deter-
mined by measuring oxygen consumption at 3 constant submaximal speeds of 233, 268, and 300 m/min on a treadmill. Running
mechanics were measured during the last 30 s of each 4-min stage of the RE test via wireless triaxial 10-g accelerometer devices
attached to the top of each shoe. Ground-contact time, swing time, step frequency, and step length were determined from accel-
erometric output corresponding to foot-strike and toe-off events. Gait variability was calculated as the standard deviation of a
given gait variable for an individual during the last 30 s of each stage. There were no differences in VO2 or kinematic variables
between CON and CS trials at any of the speeds. Wearing lower-leg compression does not alter the energetics of running at
submaximal speeds through changes in running mechanics or other means. However, it appears that the individual response to
wearing lower-leg compression varies greatly and warrants further examination.
Keywords: endurance athletes, energy cost, gait, ground-contact time, performance clothing
Endurance runners are using compression garments presumably
as a means to improve training, performance, and recovery, yet there
is little consistent, conclusive research exploring the efcacy of and/
or mechanisms underlying the use of lower-leg compression as an
ergogenic aid specically during running. Improved venous return
and clearance of metabolites,1 proprioception,2,3 force production,2–4
thermoregulation,3 and subjective measures2,5 have been evaluated
as potential mechanisms to improve athletic performance using
compression, with varying results. With regard to distance running
in particular, studies evaluating the use of compression stockings
to improve performance have been equivocal.5–8
A relatively constant nding among studies evaluating com-
pression garments is a decrease in active hip-joint range of motion,
suggesting the likelihood of an “ergogenic interplay” between
compression and biomechanical factors.2,3,7 In addition, there is
evidence to suggest that compression garments reduce longitu-
dinal and anterior–posterior muscle vibrations on landing during
repetitive jumping.3,4 This nding has been attributed to enhanced
muscle activation, as soft-tissue vibrations with ground impact can
be attenuated by increased muscle activity.9 Similarly, compression
garments appear to allow greater maintenance and consistency of
repeated-jump performances, although whether this would trans-
late to any kinematic measure during other modes of exercise is
unknown. A potentially comparable measure during running is
stride-to-stride variability, which has been shown to relate to the
energy cost of locomotion and increase with fatigue.10,11 Only
recently have kinematics been examined with subjects wearing
lower-leg compression garments during endurance running, and
no differences were observed when the results were compared with
a noncompressive control visit.8 However, the runners used in the
study can be considered moderately trained (mean 10-km best: 38
min), and no indication of gait stability was measured.
It is well known that individual differences in running mechan-
ics inuence the oxygen cost of running at submaximal workloads
(ie, running economy [RE])10–14 and that a strong relationship exists
between RE and distance-running performance.15–17 Small differ-
ences in RE often inuence performance outcomes, particularly at
the elite level, where all athletes possess a high maximal oxygen
uptake (VO2max) and can sustain efforts at a high percentage of
their VO2max for prolonged periods of time.17 Thus, any change in
running mechanics that inuences RE could ultimately affect an
athlete’s performance. It is currently unknown whether lower-leg
compression sleeves alter gait mechanics and/or stride-to-stride
variability in young, highly trained runners and, if so, what impact
this alteration will have on RE. We hypothesized that wearing
compression sleeves would reduce stride-to-stride variability and
improve economy during treadmill running.
Subjects (N = 16) were highly trained men, all either current col-
lege or professional distance runners. Subject anthropometrics and
personal-best race performances are displayed in Table 1. Subjects
reported running 6.5 ± 0.9 d/wk and 100 ± 32 km/wk during the 6
months before the study. All runners were determined to be t to
participate in the study, as assessed by physical activity and training
The authors are with the Dept of Kinesiology, Indiana University,
Bloomington, IN. Address author correspondence to Abigail Stickford at
International Journal of Sports Physiology and Performance, 2015, 10, 76-83
© 2015 Human Kinetics, Inc.
Effect of Compression on Gait and Economy 77
questionnaires. Their specialty racing events included the 1500-m,
3000-m steeplechase, 5000-m, and 10,000 m. Primary inclusion
criteria were active training, age 18 to 30 years, and a 5000-m time
of 16:30 within the past year. Runners who had not raced a 5000-m
in the past year were deemed highly trained by VO2max measures
(>65 mL · kg–1 · min–1) obtained within the past year. The study was
carried out from late July through early September. Subjects were
informed of the risks and benets of the study and gave written
informed consent before testing. All protocols and procedures were
approved by the institutional review board of Indiana University.
Subjects completed a single experimental session. Since subjects
could not be blinded to wearing compression garments, they also
completed a questionnaire dening their a priori experiences with
and beliefs regarding compression garments. The 7 dichotomous
questions were summed to give an overall belief score, with high
positive values indicating substantial experience with and positive
opinions on the effectiveness of compression garments.
Two separate RE tests took place during the session. The
sequence of tests, a trial with calf-compression sleeves (CS) and a
control trial without compression sleeves (CON), was randomized
and counterbalanced, with approximately 10 to 15 minutes rest
between. Graduated calf-compression sleeves (Zensah, Miami, FL)
generating 15 to 20 mm Hg of compression (per manufacturer’s
statement) were worn by the subjects during the CS trial; manufac-
turer recommendations for sizing based on height and maximal calf
circumference were used. The elastic of the sleeve reached from ~2
cm above the ankle to ~4 cm below the knee. For both trials runners
wore the same pair of their own lightweight shoes and low-cut socks.
RE was assessed by measuring VO2 during 4-minute stages at
each of 3 constant submaximal speeds of 233, 268, and 300 m/min
on a motorized treadmill (Quinton, model 18-72, Bothell, WA).
Treadmill speed was veried through the use of a laser tachometer
(Mastech, model DT-2234C, San Jose, CA). RE was calculated from
the VO2 measured over the nal 60 seconds of each 4-minute stage
at each speed and the slope of line relating VO2 to speed.
Ventilatory and metabolic variables were continuously mea-
sured during exercise using a computer-interfaced, open-circuit,
indirect calorimetry system. Minute ventilation (VE) was deter-
mined using a pneumotach (Hans Rudolph #3813, Kansas City,
MO) and amplier (Hans Rudolph #1110) on the inspired side.
Subjects breathed through a low-resistance 2-way valve (#2700,
Hans Rudolph), and a 5-L mixing chamber was used for collection
of expired gases. Fractional concentrations of O2 (FEO2) and CO2
(FEO2) were determined from dried expired gas sampled at a rate of
300 mL/min, using separate O2 and CO2 gas analyzers (SA-3 and
CD-3A, respectively, AEI Technologies, Pittsburg, PA). Analyzers
were calibrated before each test using commercially available gas
mixtures within the physiological range. VE, VO2, and VCO2 were
averaged over each minute of exercise, with VE corrected to BTPS
(body temperature and pressure, saturated) and VO2 and VCO2
corrected to STPD (standard temperature and pressure, dry). These
variables, as well as FEO2 and FECO2, were continuously measured
and monitored with a data-acquisition control system (DASYLab
10.0, National Instruments, Norton, MA) sampling at 50 Hz.
To measure select kinematic variables related to running gait,
accelerometric data were gathered during the last 30 seconds of
each 4-minute stage of the RE test. Separate wireless triaxial 10-g
accelerometers (G-link, Microstrain, Williston, VT) were attached
to the shoelaces on each foot using plastic ties. The accelerometers
sampled each axis at 1024 Hz, with data from each 30-second stage
being stored in separate les. Accelerometer data were analyzed
using a custom in-house program, following a technique described
previously.18 Briey, the unltered output of the accelerometer in
the vertical and horizontal planes was used to identify contact and
toe-off time points for each step, allowing quantication of (1) foot
ground-contact time (tc), dened as the time (s) from when the foot
contacts the ground to when the foot toes off (ie, breaks contact
with the ground); (2) swing time (tsw), dened as the time (s) from
toe-off to ground contact of consecutive footfalls of the same foot;
(3) step frequency (SF), dened as the number of ground-contact
events (ie, steps taken) per second; and (4) step length (SL), dened
as the length (m) that the treadmill belt moved from toe-off to
ground contact in successive steps (opposite feet), calculated from
SF (steps/min) and treadmill speed (m/min). Values of tc, tsw, SL,
and SF were determined from the average of accelerometric values
obtained from a minimum 20 consecutive steps. Gait variability was
calculated as the standard deviation of a given gait variable for an
individual during the last 30 seconds of each stage. Mechanical
parameters of the spring-mass model during running, including
vertical displacement of the center of mass at lowest point, peak
displacement of the leg spring, maximal ground-reaction force, ver-
tical stiffness, and leg spring stiffness, were calculated as described
by Morin et al19 using measures of body mass, height, ight time,
and ground-contact time.
Statistical Analysis
Descriptive statistics were used to describe the characteristics of the
group, and Pearson correlations were used to quantify relationships
between mechanical and metabolic variables (SPSS 18, Chicago,
IL). To assess differences in the outcome measures of tc, tsw, SL,
SF, and submaximal VO2 at the different running speeds during CS
and CON testing sessions, a 2 × 3 repeated-measures ANOVA was
conducted. When the F value was considered statistically signicant,
differences between CS and CON at each speed were determined
using simple main effects. A modied Bonferroni adjustment was
done to account for the multiple planned comparisons. Data are
reported as mean ± standard error of the mean (SE) unless otherwise
stated. Signicance was set at P < .05.
Table 1 Subject Characteristics and Reported
Personal-Best Race Performances During the 1 Year
Before the Study, Mean ± SD
Characteristic Value
Age (y) 22.4 ± 3.0
Height (cm) 180.6 ± 4.6
Mass (kg) 66.4 ± 5.2
Event average time (min:s)
1500 m (n = 8) 3:56.2 ± 0:12.6
5000 m (n = 12) 14:47 ± 1:02.2
10,000 m (n = 4) 29:22 ± 0:35.7
Note: Some subjects (n = 9) reported personal bests in more than 1 event.
78 Stickford et al
Running Economy
There were no differences in VO2 between CON and CS trials at
any of the speeds (P = .70–1.00) (Figure 1). At 233 m/min, VO2
was 46.7 ± 1.6 mL · kg–1 · min–1 (CON) and 46.5 ± 1.5 mL · kg–1 ·
min–1 (CS). At 268 and 300 m/min, submaximal VO2 was 54.0 ± 1.6
mL · kg–1 · min–1 for CON and 54.0 ± 1.7 mL · kg–1 · min–1 for CS
and 62.1 ± 1.7 mL · kg–1 · min–1 for CON and 62.2 ± 1.8 mL · kg–1
· min–1 for CS, respectively. In addition, there was no difference in
the slope of the lines relating submaximal VO2 and running speed
between the 2 experimental conditions (slope = 0.230 and 0.233
for CON and CS, respectively; P = .54) (Figure 1).
Running Mechanics
There were no differences in tc, tsw, SF, and SL between CON and
CS trials at any of the running speeds (P = .28–.94) (Table 2A).
Gait variability was also not different from CON to CS conditions
at any of the speeds (P = .42–.73) (Table 2B). Spring-mass model
parameters were comparable to those previously reported19 and did
not differ between CON and CS.
As seen previously, tc was inversely correlated with submaxi-
mal VO2. Figure 2 shows the relationship between the inverse of tc
(tc–1) and VO2 for each individual during the 3 speeds of the control
condition. The mean coefcient of determination (R2) was .96 ± .02.
A similar relationship was seen between these variables during the
treatment condition.
Individual Response to Compression
The individual metabolic response to compression was quite variable
(ΔVO2 range –4.8% to 5.1%), with some runners consistently show-
ing a higher VO2 during the CON condition and others displaying
higher VO2 while wearing compression (Figure 3). We completed
a post hoc analysis using subjects with the greatest improvements
(n = 4) and largest decrements (n = 4) in RE (from CON to CS)
to determine if there were any distinguishing characteristics that
explained these individual responses to compression. There were no
differences between groups in spring-mass model parameters (Table
Figure 1 — Submaximal oxygen consumption (VO2) during control (black
circles) and compression (white circles) conditions. Slopes of the running
economy lines are 0.230 during control and 0.233 during compression
trials. Values are mean ± SE.
Table 2A Gait Variables, Mean ± SE
Gait Variable
Speed (m/min) Condition Ground-contact time (s) Swing time (s) Step frequency (Hz) Step length (m)
233 Control 0.204 ± 0.003 0.507 ± 0.010 2.831 ± 0.038 1.38 ± 0.02
Compression sleeve 0.205 ± 0.003 0.506 ± 0.009 2.827 ± 0.035 1.38 ± 0.02
268 Control 0.188 ± 0.003 0.503 ± 0.010 2.907 ± 0.037 1.53 ± 0.02
Compression sleeve 0.189 ± 0.003 0.500 ± 0.009 2.910 ± 0.035 1.53 ± 0.02
300 Control 0.175 ± 0.002 0.495 ± 0.008 2.990 ± 0.037 1.68 ± 0.02
Compression sleeve 0.175 ± 0.002 0.495 ± 0.009 2.994 ± 0.036 1.67 ± 0.02
Table 2B Calculated Variability (SD) in Measured Gait Variables, Mean ± SE
Gait Variability (SD)
Speed (m/min) Condition Ground-contact time (s) Swing time (s) Step frequency (Hz) Step length (m)
233 Control 0.0059 ± 0.0012 0.0096 ± 0.0013 1.62 ± 0.12 0.013 ± 0.001
Compression sleeve 0.0066 ± 0.0014 0.0088 ± 0.0012 1.57 ± 0.17 0.013 ± 0.001
268 Control 0.0055 ± 0.0010 0.0086 ± 0.0012 1.71 ± 0.22 0.015 ± 0.002
Compression sleeve 0.0052 ± 0.0011 0.0080 ± 0.0009 1.72 ± 0.21 0.015 ± 0.002
300 Control 0.0054 ± 0.0008 0.0086 ± 0.0010 1.93 ± 0.21 0.018 ± 0.002
Compression sleeve 0.0051 ± 0.0014 0.0082 ± 0.0015 1.81 ± 0.19 0.017 ± 0.002
Figure 2 — Mass-specic rates of oxygen consumption (VO2) increase linearly with inverse ground-contact time (1/tc) for all subjects. Average coef-
cient of determination (R2) is .96.
Figure 3 — Individual percentage changes in oxygen consumption (VO2) from the control (CON) to compression (CS) condition across 3 submaximal
80 Stickford et al
Table 3 Main Mechanical Parameters During Treadmill Running (Mean ± SD)
Speed Parameter Group CON Group CS Positive CON Positive CS Negative CON Negative CS
233 m/min Δyc (m) 0.05 ± 0.01 0.05 ± 0.01 0.05 ± 0.01 0.05 ± 0.01 0.05 ± 0.01 0.06 ± 0.01
ΔL (m) 0.14 ± 0.02 0.14 ± 0.02 0.14 ± 0.01 0.14 ± 0.01 0.15 ± 0.03 0.15 ± 0.03
Fmax (kN) 1.80 ± 0.27 1.79 ± 0.24 1.82 ± 0.09 1.84 ± 0.05 1.73 ± 0.44 1.69 ± 0.38
kvert (kN/m) 36.53 ± 8.47 35.84 ± 7.44 35.26 ± 4.98 36.00 ± 3.49 33.60 ± 13.66 32.38 ± 11.59
kleg (kN/m) 13.67 ± 3.28 13.41 ± 2.88 13.33 ± 1.71 13.62 ± 1.11 12.63 ± 5.37 12.15 ± 4.90
268 m/min Δyc (m) 0.04 ± 0.01 0.04 ± 0.01 0.05 ± 0.00 0.05 ± 0.00 0.05 ± 0.01 0.05 ± 0.01
ΔL (m) 0.14 ± 0.02 0.14 ± 0.02 0.14 ± 0.01 0.15 ± 0.01 0.15 ± 0.02 0.15 ± 0.03
Fmax (kN) 1.88 ± 0.26 1.86 ± 0.25 1.91 ± 0.05 1.89 ± 0.05 1.84 ± 0.46 1.84 ± 0.44
kvert (kN/m) 43.42 ± 9.38 42.97 ± 9.20 43.12 ± 4.73 42.04 ± 4.91 41.95 ± 14.94 42.70 ± 15.89
kleg (kN/m) 13.41 ± 3.01 13.27 ± 2.97 13.49 ± 1.30 13.14 ± 1.35 13.03 ± 4.90 13.27 ± 5.22
300 m/min Δyc (m) 0.04 ± 0.00 0.04 ± 0.00 0.04 ± 0.00 0.04 ± 0.00 0.04 ± 0.00 0.04 ± 0.00
ΔL (m) 0.15 ± 0.02 0.14 ± 0.02 0.15 ± 0.01 0.15 ± 0.01 0.15 ± 0.02 0.14 ± 0.02
Fmax (kN) 1.96 ± 0.25 1.97 ± 0.27 1.97 ± 0.05 1.96 ± 0.08 1.95 ± 0.43 1.96 ± 0.43
kvert (kN/m) 52.14 ± 10.49 53.30 ± 12.77 49.45 ± 1.44 48.79 ± 3.97 52.44 ± 16.50 53.20 ± 16.38
kleg (kN/m) 13.68 ± 2.92 14.00 ± 3.54 13.14 ± 1.35 12.97 ± 1.15 13.84 ± 4.66 14.05 ± 4.62
Note: Spring-mass model parameters based on a sine-wave modeling of the force–time curve during contact (calculations based on Morin et al19). Positive refers to
improved running economy with compression (n = 4); negative refers to worsened running economy with compression (n = 4). No signicant differences in any measures
between conditions or groups.
Abbreviations: CON, control; CS, compression trial. Δyc, vertical displacement of the center of mass when it reaches its lowest point; ΔL, peak displacement of the leg
spring; Fmax, maximal ground-reaction force during contact; kvert, vertical stiffness; kleg, stiffness of the leg spring.
Table 4 Comparisons in Stride-Frequency (SF) and Stride-Length (SL) Variability (SD) During the Compression
Trial Between Subjects Who Showed Improvements (n = 4) and Decrements (n = 4) in Running Economy
Speed (m/min) Improved running economy Worsened running economy
Effect size (Cohen
SF Variability 233 1.11 ± 0.18 1.77 ± 0.38 .02* 2.22
268 1.37 ± 0.20 2.24 ± 1.23 .14 1.00
300 1.56 ± 0.29 2.20 ± 1.02 .18 0.85
SL Variability 233 0.009 ± 0.001 0.014 ± 0.003 .04* 2.24
268 0.012 ± 0.002 0.020 ± 0.012 .17 0.93
300 0.015 ± 0.001 0.021 ± 0.011 .20 0.77
Note: P value reported from comparison between groups (1-tailed independent-groups t test). Values are mean ± SD.
*Signicantly different at P < .05.
3). However, there was a clear trend for runners who improved RE
with compression to have lower SF- and SL-variability measures
(Cohen d = 0.77–2.24; Table 4). At the slowest running speed,
subjects with improved RE tended to further reduce gait-variability
measures when wearing compression, while subjects with worsened
RE increased gait variability (d = 1.22, 1.17, P = .09, .10 for SF and
SL variability, respectively; Figure 4). Runners with improved RE
also showed greater consistency in absolute SF and SL measures
from CON to CS than subjects whose RE worsened (d = 1.02, 1.08,
and 0.67, P = .14, .13, .21 for SF across speeds; d = 0.66, 1.08,
and 0.67, P = .20, .13, .21 for SL across speeds; Figure 5 shows
averages). In addition, there was a signicant inverse correlation
between belief scores and changes in VO2 with compression (r =
–.52, P = .04), as runners who exhibited more positive feelings about
compression garments displayed larger decrements in submaximal
VO2 during CS (Figure 6).
This study investigated the impact of wearing lower-leg compres-
sion sleeves on the RE and mechanics of highly trained distance
runners. Our conclusions can be divided into 3 major categories:
RE, running mechanics, and the individual variability in response
to compression. While the use of lower-leg compression sleeves did
not affect group measures of RE or mechanics, subjects who had
a positive or negative change in RE with compression treatment
displayed different biomechanical responses to, and a priori beliefs
regarding, compression.
Running Economy
In the current study we found that lower-leg compression sleeves
do not alter whole-body VO2 during submaximal running. The
Effect of Compression on Gait and Economy 81
absence of a group effect of compression on submaximal VO2 is
consistent with previous ndings. Kemmler et al7 saw no change
in the VO2 of moderately trained runners (VO2max = 52 mL · kg–1 ·
min–1; 10-km best = 40:36) at various workloads (established based
on blood lactate values; submaximal speeds lower than those in the
current study) when wearing compressive stockings as compared
with during control conditions. Bringard et al20 also showed no
effect of compression on submaximal running gross VO2 compared
with regular elastic tights in trained runners (speeds 167–268 m/
min). However, they did observe a signicant reduction in the slow
component of VO2 while compression tights were worn, presumably
indicating improved energetics. Similarly, in subjects with tness
levels more comparable to that of our subjects (VO2max = 70 mL ·
kg–1 · min–1; 10-km best 38:30), there was no effect of compres-
sion on VO2 during a 40-minute run (at a speed corresponding to
the slowest speed, 233 m/min, of our study).6 Our ndings add to
and support the literature regarding compression garments and RE
in healthy individuals, providing additional evidence for no gross
effect of compression on submaximal VO2, specically in a group
of elite runners.
Running Mechanics
Few studies have investigated the effect of compression on the
selected mechanical variables measured in our study.8 However,
previous ndings indicate that lower-body compression garments
may inuence lower-body mechanics by limiting range of motion
(ROM).2,3 Decreased ROM is associated with increased stiffness,17
which, in turn, can alter the selected gait variables measured in the
current study. Furthermore, compression garments appear to allow
greater consistency in mechanics/performance during repetitive
power movements.4 Thus, previous ndings would suggest that
lower-body compression may affect the mechanics of movement.
Bringard et al7 and Kemmler et al20 seem to support this hypothesis
by proposing that compression treatment may act through increased
biomechanical support of the muscle–tendon unit, ultimately result-
ing in greater mechanical efciency. We were unable to conrm
this, however, as we found no overall effect of wearing lower-limb
compression on leg stiffness or running mechanics. The inability of
compression to exert an effect on running mechanics in the current
study could be due to a number of factors including the targeted gait
variables, the level and/or location of compression exerted by the
calf sleeve used, and, perhaps more likely, the subject population.21
Nonetheless, as will be discussed further, our ndings suggest that
there may be distinct individual metabolic and mechanical responses
Figure 4 — Percentage changes in average stride-frequency (SF) and
stride-length (SL) variability from control to compression in individuals
who showed an improvement in running economy (black bars) and those
whose running economy worsened (gray bars) at 233 m/min (d = 1.22,
1.17; P = .09, .10, for SF and SL variability, respectively). No differences
between groups at other speeds (d = 0.05–0.23, P = .38–.49). Values are
mean ± SE.
Figure 5 — Percent changes in stride frequency and stride length from
control to compression at a speed of 233 m/min in individuals who showed
an improvement in running economy (black bars) and those whose running
economy worsened (gray bars). Values are mean ± SE.
Figure 6 — Correlation between change in oxygen consumption (ΔVO2)
from control (CON) to compression (CS) and belief score (r = –.517, P
= .041). Score was determined from answers to pretesting questionnaire
about experience with and opinions on compression garments—positive
values assigned to experience/positive responses; negative values assigned
to no experience/negative responses.
82 Stickford et al
to compression, perhaps partially explaining the lack of a group
response in our, and previous, studies.
During submaximal running, the majority of stored energy
comes from muscles and tendons supporting the ankle and knee;
for the lower leg, this refers specically to the triceps surae and the
Achilles tendon.22 The lower band of the compression sleeve used
in our study sat immediately superior to the lateral malleolus. Thus,
although it covered most of the triceps surae and a portion of the
tendon, the compression did not cover the entire Achilles tendon,
nor did it surround the ankle joint, itself. In previous investiga-
tions nding decreased ROM, the garment completely covered the
joint about which ROM was reduced.2,3 On the other hand, jump-
performance consistency improves with a garment covering just
the hip joint, despite multiple muscles and joints being involved
in the movement,4 indicating that complete compression about all
involved muscles and joints is not necessary to see changes in global
mechanical variables. As running, too, involves the coordination
of various muscles and joints, it is unlikely that the lack of gross
mechanical effect in the current study was due to the garment not
covering a joint. Also of note, as is the case in the majority of studies
on compression garments,21 the precise level of pressure exerted by
the sleeves on the calf in our study is unknown; we relied fully on
the manufacturer’s statement. As such, the magnitude of compres-
sion used in our study may be different from that of garments used
in previous studies. Direct measurements of compression-garment
pressures have been shown to be comparable to manufacturer rat-
ings,6 so based on available reports, the compression appears to be
similar between our study (15–20 mm Hg) and others (range = 8–26
mm Hg).21 We chose this particular compression-sleeve garment as
it is relatively inexpensive, widely available, and commonly used;
in other words, ndings regarding the garment are quite applicable
to the target athlete population.
The subjects in our study were highly trained distance runners,
whereas many previous studies used less-t subjects and athletes
specializing in other events (eg, sprinters, skiers).2–7,20 Attempts to
alter running mechanics have been successful in clinical popula-
tions and in novice or moderately trained runners,23,24 but it appears
that altering habitual gait patterns in highly trained athletes is more
difcult. It has been demonstrated that highly trained runners con-
sistently select the most economically optimal locomotion style;
deviating from the preferred gait mechanics results in signicant
decrements in economy of locomotion.11,13 Furthermore, trained
runners are able to maintain similar gait patterns by adjusting, for
example, leg stiffness or muscle activity despite external interfer-
ences (eg, changes in surface properties).25 Therefore, our subject
cohort, being highly trained, may have been able to continue to select
the most economical running pattern despite the “interference” of
lower-leg compression.
Individual Response to Compression
Although the group mean metabolic response to compression was
not different from CON, there was substantial interindividual vari-
ability. A change of 1% in submaximal VO2 is reported to have
signicant performance implications, demonstrating a tight link
between RE and running performance.26,27 Therefore, we completed
a post hoc analysis to determine if there were any distinguishing
characteristics that explained these individual responses to com-
pression. When subjects were grouped according to changes in
RE, it became evident that those who improved RE while wearing
compression had lower measures of gait variability, particularly
at the slowest speed during CS (P = .04 [SL], 0.02 [SF]; Table 4).
Variability in intraindividual stride length, already lower in highly
trained runners than in nonrunners,28 decreases with faster running
speeds,29 so it is reasonable that we did not see signicant differences
in gait variability between groups at the faster speeds. In trained
runners, a large proportion of the increased energy cost of running
with fatigue is due to increased step variability,10 so decreased gait
variability may contribute to the decrease in submaximal VO2 with
compression seen in some subjects in our investigation.
Differences between groups in the degree/direction of change
in SL and SF may also have affected RE responses to compression.
Subjects whose economy worsened while wearing compression
tended to decrease SL and increase SF, whereas subjects with
improvements in RE had little to no change in SL and SF across
conditions. As mentioned previously, highly trained athletes typi-
cally select gait patterns that minimize metabolic cost, and devia-
tions from preferred kinematics result in increases in oxygen cost.
If the control condition represents a preferred movement pattern, it
appears that the compression caused some subjects to deviate from
their most economical running mechanics for a given speed. The
underlying cause as to why compression would affect the stride
mechanics and gait variability of some subjects and not others is
unknown. One possible explanation may be subjective percep-
tions of the garment, as runners with personal experience and/or
positive opinions of the garment may have felt more comfortable
(psychologically and/or physically) wearing compression. How-
ever, as there were 4 individuals who exhibited positive responses,
8 showing neutral responses, and 4 exhibiting negative responses
to compression, there is certainly a possibility that the variation in
response occurred by chance, and the sleeves truly have no effect
on metabolic or mechanical variables in highly trained runners.
Practical Applications
In general, previous research and the current investigation indicate
that wearing lower-leg compression sleeves has no substantial
effect on distance-running performance.5–8,21 However, if, in fact,
differences do exist in metabolic response to lower-leg compression
among individuals, the performance implications could be particu-
larly important for highly trained runners. In the current study, the
average percentage change in submaximal VO2 with compression
treatment ranged from –4.8% to +5.1%. A 5% improvement in
RE has been shown to induce ~3.8% improvement in distance-
running performance, and a 10% improvement in RE results in ~7%
improvement in 3000-m performance,27,28 indicating that there could
certainly be a range of performance implications for the subjects in
our study when choosing to wear compression garments.
Finally, it is not unreasonable to suspect that the different
responses to compression are due to psychological effect. A sig-
nicant correlation was found between overall viewpoints on the
efcacy of compression and metabolic changes while wearing
compression, and the 2 subjects in our study with the greatest
improvements in RE with compression treatment were the only sub-
jects who had worn compression sleeves themselves and believed
that compression aided in training, racing, and recovery. Thus, in
determining whether an athlete should use compression garments
for training, competitive, and/or recovery purposes, coaches would
be well-advised to consider the athlete’s expectations, whether
positive or negative, of the garment.
Effect of Compression on Gait and Economy 83
Wearing lower-leg compression sleeves does not alter running
mechanics or economy in highly trained distance runners during
submaximal running. However, while there is no group difference
with the sleeves, it appears that the individual response to wearing
lower-leg compression varies greatly; as such, future research should
examine underlying physiological, anatomical, and psychological
characteristics in relation to the metabolic and/or kinematic out-
comes of wearing leg-compression garments.
Supported by a grant from USA Track and Field. We would like to
acknowledge Dr Dave Tanner for his work on the accelerometric gait-
analysis program and Dr S. Lee Hong for input regarding study design
and theoretical implications.
None of the authors of this article has any conicts of interest or nan-
cial conicts to report. The results of the current study do not constitute
endorsement of the product by the authors or the journal.
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... As participants could not be blinded to wearing compression tights, a questionnaire was completed defining their a priori beliefs and experiences regarding compression garments. 15 Two separate running tests took place during the session to assess the impact of compression tights on RE, muscle oxygenation, running kinematics, heart rate (HR) and skin temperature. Participants wore compression tights and control garments for each test in a counterbalanced, crossover design. ...
... Participants were asked seven dichotomous questions and answers were summed to give an overall belief score. 15 Higher scores would indicate positive opinions on the effectiveness of compression garments. ...
... The present study is the first to investigate the influence of compression tights on running kinematics. Previous studies have included compression stockings only 15,24,25 or a combination of calf and thigh sleeves 26 and reported higher leg stiffness, lower contact time and lower stride length during constant rate running. 25,26 The present study revealed no differences in vertical oscillation or step frequency, however, in support of Kerherve et al., 25 a shorter GCT was observed with compression. ...
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The aim of the present study was to examine whether full leg-length compression tights modify physiological and kinematic measures during treadmill running at a competitive race pace in moderately trained runners. Thirteen males and five females completed two 15-minute running tests at a speed corresponding to a recent race time wearing compression tights or loose-fitting running shorts. Running economy (RE) was determined by oxygen consumption and carbon dioxide expiration during the final 3 minutes of treadmill running. Muscle oxygenation, skin temperature, heart rate (HR), vertical oscillation, step frequency and ground contact time (GCT) were measured continuously. GCT was shorter with compression compared with control trials (p = 0.03), however, no differences in RE, muscle oxygenation, vertical oscillation, step frequency, HR or skin temperature were revealed. Despite a shorter GCT with compression tights, the findings suggest that moderately trained runners do not benefit nor limit physiological responses at a competitive race pace.
... 85 and 115% preferred speed) [21,98]. The remaining three studies used physiological measures to determine speed used [19, 70, [20, 21, 28, 29, 31, 33-35, 51, 59, 70, 72, 77, 80, 82, 87, 90, 91, 93, 101, 102, 105, 106, 108, 110, 111, 117, 119, 120, 125, 128, 131, 132, 135, 139, 147] Step/stride length n = 29 The distance between successive points of initial contact of the same foot (stride) or opposite foot (step) [20, 33-35, 42, 49, 50, 54, 59, 61, 70, 80, 85, 87, 90-92, 98, 100-102, 105, 106, 108, 119, 128, 132, 139, 143] Step/stride time n = 16 The time between two consecutive heel strikes of the same foot (stride) or opposite foot (step) [27,34,42,48,59,72,75,85,90,92,100,101,106,107,128,143,144] Foot strike pattern/strike index/foot strike angle n = 15 The moment, way or angle when the foot first makes contact with the ground [21, 26, 33, 40, 59, 68, 69, 80, 84, 87-89, 93, 116, 144] Flight time n = 15 The time between toe-off from one foot to initial contact of the other foot [50,77,87,89,90,92,95,96,101,105,110,124,128,139,144] Acceleration* n = 15 The rate of change of the velocity of any segment (excluding tibia) [19,35,38,62,64,73,74,78,93,97,116,119,121,129,130] Speed/velocity ...
... The amount that the torso or COM moves vertically with each step or stride [20,21,28,29,59,90,93,134,139] Swing time ...
... The period during which the foot is not in contact with the ground [27,39,59,89,124,125,139] Cycle time ...
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Background Running gait assessment has traditionally been performed using subjective observation or expensive laboratory-based objective technologies, such as 3D motion capture or force plates. However, recent developments in wearable devices allow for continuous monitoring and analysis of running mechanics in any environment. Objective measurement of running gait is an important (clinical) tool for injury assessment and provides measures that can be used to enhance performance. Objectives To systematically review available literature investigating how wearable technology is being used for running gait analysis in adults. Methods A systematic search of literature was conducted in the following scientific databases: PubMed, Scopus, WebofScience, and SportDiscus. Information was extracted from each included article regarding the type of study, participants, protocol, wearable device(s), main outcomes/measures, analysis, and key findings. Results A total of 131 articles were reviewed: 56 investigated the validity of wearable technology, 22 examined the reliability and 77 focused on applied use. Most studies used inertial measurement units (IMU) (n=62) (i.e., a combination of accelerometers, gyroscopes, and magnetometers in a single unit) or solely accelerometers (n=40), with one using gyroscopes alone and 31 using pressure sensors. On average, studies used one wearable device to examine running gait. Wearable locations were distributed among the shank, shoe and waist. The mean number of participants was 26 (± 27), with an average age of 28.3 (± 7.0) years. Most studies took place indoors (n =93), using a treadmill (n =62), with the main aims seeking to identify running gait outcomes or investigate the effects of injury, fatigue, intrinsic factors (e.g., age, sex, morphology) or footwear on running gait outcomes. Generally, wearables were found to be valid and reliable tools for assessing running gait compared to reference standards. Conclusions This comprehensive review highlighted that most studies that have examined running gait using wearable sensors have done so with young adult recreational runners, using one IMU sensor, with participants running on a treadmill and reporting outcomes of ground contact time, stride length, stride frequency and tibial acceleration. Future studies are required to obtain consensus regarding terminology, protocols for testing validity and reliability of devices and suitability of gait outcomes.
... The predominant modality of exercise that has been examined is running, accounting for 47% of all performance studies included in the present review. Most studies described little to no benefit of lower body CGs on measures of running performance, including finishing time in competitive marathons [20,21], ultramarathons [22], and trail runs [23,24]; distance run in a multi-stage fitness test [25]; outdoor time trials of 5 and 10 km [26,27], and measures of running economy, pace, oxygen consumption, and time to fatigue during various treadmill running protocols [28][29][30][31][32]. However, compression socks appear to result in a small improvement in time to exhaustion [33] and small, significant improvements to maximum speed, the speed at aerobic and anaerobic thresholds, and total work [34]. ...
... Step length and frequency were unchanged with the use of compression socks and calf sleeves during treadmill running and outdoor trail running, respectively [23,29]. In contrast, waist-to-ankle tights (of a novel design, with inner adhesive stripes around musculature) significantly increased step length but not step frequency during repeated 30-m sprints [45]. ...
... Another way to account for the placebo effect in an unblinded research design is to record participants' a priori beliefs about compression garments, as in Stickford et al. [29], where positive or negative beliefs about CGs were seen to influence biomechanical and metabolic responses to submaximal running. However, while placebo effects have historically been seen as a nuisance that needs to be controlled for in research, emerging neurobiological theory suggests that researchers and practitioners can leverage this effect to improve athletic performance [114,115]. ...
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Background: Compression garments (CGs) are a popular tool that may act on physiological, physical, neuromuscular, biomechanical, and/or perceptual domains during exercise and recovery from exercise, with varying levels of efficacy. While previous reviews have focused on the effects of CGs during running, high-intensity exercise, and exercise recovery, a comprehensive systematic review that assesses the effectiveness of garment use both during and after exercise has not been recently conducted. Methods: A systematic search of the literature from the earliest record until May 2022 was performed based on the PRISMA-P guidelines for systematic reviews, using the online databases PubMed, SPORTDiscus, and Google Scholar. Results: 160 articles with 2530 total participants were included for analysis in the systematic review, comprised of 103 ‘during exercise’ studies, 42 ‘during recovery’ studies, and 15 combined design studies. Conclusions: During exercise, CGs have a limited effect on global measures of endurance performance but may improve some sport-specific variables (e.g., countermovement jump height). Most muscle proteins/metabolites are unchanged with the use of CGs during exercise, though measures of blood lactate tend to be lowered. CGs for recovery appear to have a positive benefit on subsequent bouts of endurance (e.g., cycling time trials) and resistance exercise (e.g., isokinetic dynamometry). CGs are associated with reductions in lactate dehydrogenase during recovery and are consistently associated with decreases in perceived muscle soreness following fatiguing exercise. This review may provide a useful point of reference for practitioners and researchers interested in the effect of CGs on particular outcome variables or exercise types.
... 36 Conversely, reductions in stride length due to CGs were associated with poorer economy in highly trained runners. 37 Novice runners demonstrate greater variability in gait characteristics. The physical support offered by compression, or the pressure-induced stimulation of mechanoreceptors 38 may, therefore, limit this variability. ...
... 2 While compression stockings were shown to increase leg stiffness during flat and hilly trail running, 39 they elicited no change during submaximal treadmill running. 37 Despite these findings, the influence of compression tights on running leg stiffness is yet to be investigated and may help explain the observed improvement in economy. Surface EMG studies report lower activation of leg musculature during sub-max running with compression stockings 40 and long tights. ...
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The effect of compression tights on running economy is unclear. The purpose of this investigation was to assess the influence of compression tights on economy. Following an incremental test to exhaustion to determine aerobic capacity (V̇O 2max) and peak running speed (vV̇O 2max), twenty-six moderately endurance-trained males (28 ± 7 years; 76.1 ± 8.4 kg; V̇O 2max = 54.7 ± 4.8 mL·kg −1 ·min −1) were allocated to either a 60% (n = 8), 62.5% (n = 9) or 65% vV̇O 2max group (n = 9) using block randomisation. Participants ran for 15 min at the allocated vV̇O 2max with compression tights and a non-compression control condition in a randomised, counterbalanced order, separated by seven days. Oxygen consumption (V̇O 2) and expired carbon dioxide (V̇CO 2) was measured to determine economy as caloric unit cost. No difference was observed between conditions for the 60% and 62.5% vV̇O 2max groups, however economy was improved with compression at 65% vV̇O 2max (P < 0.01). Combined analysis of all participants revealed ΔRE (Δ = control − compression) correlated with relative aerobic capacity (%V̇O 2max) (r = 0.50, P < 0.01) but not running speed (r = 0.04, P < 0.84). These data suggest that compression tights influence economy at 65% vV̇O 2max or at relative exercise intensities of approximately 75-85%V̇O 2max .
... A high-speed camera (Olympus TG-5) was placed 4-meter away paralleled from the treadmill to obtain a sagittal view of the running movements (Jefry, Hasan, Azhan, Misnon, Azidin & Ismail, 2019) and the video footage was set at 240 frames per second. Kinematics parameters measurements which included ground contact time (GCT), stride length (SL), swing time (ST), and heel strike (HS) were taken during the last 30 seconds of every 3 minutes' stages of the treadmill running test which is adopted from the study by (Stickford, Chapman, Johnston, & Stager, 2015). Movements of the foot during running were analyzed using Kinovea 0.8.24, (France) movement analysis software. ...
Full-text available
This study was conducted to determine running kinematics while using compression socks (CS) and smooth socks (SS) among 16 recreational runners. They were required to complete a maximal treadmill test with two different running sock conditions (smooth and compression). All kinematic parameters (ground contact time, heel strike, stride length and swing time) were reported in an average of the four stages of Bruce protocol. Results showed more significant correlations (p<0.05) among the kinematic variables in the compression socks condition as compared to the smooth socks. In conclusion, wearing compression socks improves movement kinematics while running may be due to the enriched somatosensory information received by the foot. Keywords: Running; Compression socks; Movement kinematics; Somatosensory feedback eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license ( Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI:
... Some research has found positive effects of wearing compression garments on exercise performance, or during recovery from exercise [7][8][9][10][11][12]. However, other research has not been able to demonstrate such effects [13][14][15][16][17][18]. Consequently, with such equivocal research findings, it is unknown whether compression garments aid exercise performance and recovery. ...
Full-text available
The purpose of this study was to make made-to-measure compression garments that elicit pressures within and below clinical standards. The study also examined whether pressures and gradients can be replicated within and between participants' legs, and between separate compression garment conditions. Ten males volunteered to participate. Based on three-dimensional scans of the participants' lower body, three different made-to-measure garments were manufactured: control, symmetrical and asymmetrical. Garment pressures were assessed from the malleolus to the gluteal fold using a pressure monitoring device. A root mean squared difference analysis was used to calculate the in vivo linear graduation parameters. Linear regression showed that peak pressure at the ankle in the left and right leg were: control garment, 13.5 ± 2.3 and 12.9 ± 2.6; asymmetrical garment, 12.7 ± 2.5 and 26.3 ± 3.4; symmetrical garment, 27.7 ± 2.2 and 27.5 ± 1.6 (all mmHg, mean ± standard deviation). Pressure reduction from the ankle to the gluteal fold in the left and right leg were: control, 8.9 ± 3.5 and 7.4 ± 3.0; asymmetrical , 7.8 ± 3.9 and 21.9 ± 3.2; symmetrical, 25.0 ± 4.1 and 22.3 ± 3.6 (all mmHg, mean ± standard deviation). Made-to-measure compression garments can be made to elicit pressures within and below clinical standards, and to elicit equivalent pressures and gradients in different participants.
... The claimed benefits of CG in terms of enhanced exercise performance (Ali et al. 2010;MacRae et al. 2012) and recovery (Chatard et al. 2004;Driller and Halson 2013;Menetrier et al. 2013) remain controversial, Communicated by George Havenith. with contradictory findings from studies (Ali et al. 2007;Chan et al. 2016;Goto et al. 2017;Stickford et al. 2015) due to diverse experimental settings and the type of CG used. Although recent reviews suggest that sports CG may enhance recovery performance, reduce perceived exertion and the severity of delayed onset muscle soreness (DOMS), the potential mechanisms and relationship between sports CG and enhanced recovery remain elusive (Beliard et al. 2015;Brown et al. 2017;Engel et al. 2016;Hill et al. 2014a). ...
Full-text available
PurposeTo investigate sports compression garment (CG)-induced recovery hemodynamics and their potential impact on subsequent cycling performance.Methods In a randomized crossover design, 13 physically active men (20.9 ± 1.4 years; 65.9 ± 7.8 kg; 173.3 ± 4.8 cm; peak power output 254.2 ± 27.2 W) underwent 2 experimental trials. During each experimental trial, the subjects performed 20-min fatiguing preload cycling followed by 60-min passive recovery wearing either a sports CG (28.6 ± 9.4 mmHg) or gymnastic pants (CON). A 5-min all-out cycling performance test was subsequently conducted and power output and cadence were recorded. Cardiac output (CO) and stroke volume (SV) were measured using Doppler ultrasound (USCOM®). Heart rate (HR), blood lactate [BLa−], ratings of perceived exertion (RPE), leg muscle soreness (LMS), mean arterial pressure (MAP) and systemic vascular resistance (SVR) were monitored at 5, 15, 30, 45, 60 min during passive recovery.ResultsDuring the subsequent 5-min all-out cycling performance test, power output (215.2 ± 24.0 vs. 210.8 ± 21.5 W, CG vs. CON) and cadence (72.5 ± 3.8 vs. 71.2 ± 4.8 rpm, CG vs. CON) were higher in CG than CON (P < 0.05). SV was higher at 15, 30 and 45 min (P < 0.05), CO was higher at 5 and 45 min (P < 0.05), HR was lower at 15 and 30 min (P < 0.05) and [BLa−] was lower at 5 and 15 min (P < 0.05) during passive recovery, while LMS was lower at all time-points (P < 0.05) compared with CON.Conclusion Sports CG improves subsequent cycling performance by enhancing hemodynamic responses and attenuating perceived muscle soreness during passive recovery in physically active men.
La survenue d’altérations neuromusculaires et musculo tendineuses lors d’épreuves de course à pied de fond s’avère être délétère sur la capacité de performance d’endurance et la période de récupération des athlètes. Par ailleurs, la sévérité de ces perturbations peut être exacerbée par les caractéristiques du terrain, et plus particulièrement par la présence de dénivelé négatif. En course à pied de descente, l’amplitude plus importante de ces altérations est sous-tendue par la prédominance du régime de contraction excentrique à l’exercice. Dès lors, la course à pied de descente constitue un challenge pour les coureurs dans leur quête d’excellence athlétique, aussi bien à l’entraînement que lors d’épreuves compétitives. L’exploration de stratégies préventives, ayant pour objectif de mieux tolérer les sections de course à pied en descente, apparaît donc pleinement justifiée dans le domaine de l’optimisation des réponses adaptatives en course à pied. Dans ce contexte, une première analyse prospective de la littérature a focalisé sur l’exploration des stratégies de répétitions de sessions (c.-à-d., usage chronique de la course à pied en descente) et du port in situ de textiles vestimentaires à visée ergogénique (e.g., textiles de compression et réflecteurs de rayons infrarouges lointains). Étant donné que l’usage chronique de la course à pied en descente pourrait également permettre l’instauration d’adaptations bénéfiques sur la capacité de performance des athlètes, il convenait au préalable de préciser les adaptations neuromusculaires et musculo-tendineuses à l’entraînement de course à pied en descente. Ainsi, les objectifs du travail de thèse étaient de caractériser les adaptations neuromusculaires et musculo-tendineuses à l’entraînement de course à pied en descente d’une part, et d’enrichir nos connaissances sur l’apport de stratégies préventives dans le domaine de la course à pied de fond, d’autre part. Les résultats de ce travail ont montré que : (i) l’entraînement de course à pied en descente (4 semaines) peut instaurer de rapides adaptations neuromusculaires (e.g., gains de force, hypertrophie musculaire) et tendineuses (par exemple, augmentation de la raideur du tendon patellaire), sans pour autant atténuer la sévérité des perturbations neuromusculaires à l’issue d’une session de course à pied en descente ; (ii) que le port de textiles de compression à l’exercice peut exercer un « effet protecteur dynamique » sur les groupes musculaires compressés, sans pour autant atténuer les perturbations de la capacité de performance d’endurance des athlètes ; et (iii) que le port de textiles réflecteurs de rayons infrarouges à l’exercice pourrait générer certains effets ergogéniques mais que la compréhension de leurs effets reste à ce jour globalement limitée.
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Inertial measurement units (IMUs) can be used to monitor running biomechanics in real-world settings, but IMUs are often used within a laboratory. The purpose of this scoping review was to describe how IMUs are used to record running biomechanics in both laboratory and real-world conditions. We included peer-reviewed journal articles that used IMUs to assess gait quality during running. We extracted data on running conditions (indoor/outdoor, surface, speed, and distance), device type and location, metrics, participants, and purpose and study design. A total of 231 studies were included. Most (72%) studies were conducted indoors; and in 67% of all studies, the analyzed distance was only one step or stride or <200 m. The most common device type and location combination was a triaxial accelerometer on the shank (18% of device and location combinations). The most common analyzed metric was vertical/axial magnitude, which was reported in 64% of all studies. Most studies (56%) included recreational runners. For the past 20 years, studies using IMUs to record running biomechanics have mainly been conducted indoors, on a treadmill, at prescribed speeds, and over small distances. We suggest that future studies should move out of the lab to less controlled and more real-world environments.
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Background Compression garments are regularly worn during exercise to improve physical performance, mitigate fatigue responses, and enhance recovery. However, evidence for their efficacy is varied and the methodological approaches and outcome measures used within the scientific literature are diverse. Objectives The aim of this scoping review is to provide a comprehensive overview of the effects of compression garments on commonly assessed outcome measures in response to exercise, including: performance, biomechanical, neuromuscular, cardiovascular, cardiorespiratory, muscle damage, thermoregulatory, and perceptual responses. Methods A systematic search of electronic databases (PubMed, SPORTDiscus, Web of Science and CINAHL Complete) was performed from the earliest record to 27 December, 2020. Results In total, 183 studies were identified for qualitative analysis with the following breakdown: performance and muscle function outcomes: 115 studies (63%), biomechanical and neuromuscular: 59 (32%), blood and saliva markers: 85 (46%), cardiovascular: 76 (42%), cardiorespiratory: 39 (21%), thermoregulatory: 19 (10%) and perceptual: 98 (54%). Approximately 85% ( n = 156) of studies were published between 2010 and 2020. Conclusions Evidence is equivocal as to whether garments improve physical performance, with little evidence supporting improvements in kinetic or kinematic outcomes. Compression likely reduces muscle oscillatory properties and has a positive effect on sensorimotor systems. Findings suggest potential increases in arterial blood flow; however, it is unlikely that compression garments meaningfully change metabolic responses, blood pressure, heart rate, and cardiorespiratory measures. Compression garments increase localised skin temperature and may reduce perceptions of muscle soreness and pain following exercise; however, rating of perceived exertion during exercise is likely unchanged. It is unlikely that compression garments negatively influence exercise-related outcomes. Future research should assess wearer belief in compression garments, report pressure ranges at multiple sites as well as garment material, and finally examine individual responses and varying compression coverage areas.
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Running performance depends on maximal oxygen uptake (V̇O2max), the ability to sustain a high percentage of V̇O2max for an extended period of time and running economy. Running economy has been studied relatively less than the other factors. Running economy, measured as steady state oxygen uptake V̇O2) at intensities below the ventilatory threshold is the standard method. Extrapolation to a common running speed (268 m/min) or as the V̇O2 required to run a kilometer is the standard method of assessment. Individuals of East African origin may be systematically more economical, although a smaller body size and a thinner lower leg may be the primary factors. Strategies for improving running economy remain to be developed, although it appears that high intensity running may be a common element acting to improve economy.
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Compression garments (CGs) provide a means of applying mechanical pressure at the body surface, thereby compressing and perhaps stabilizing/supporting underlying tissue. The body segments compressed and applied pressures ostensibly reflect the purpose of the garment, which is to mitigate exercise-induced discomfort or aid aspects of current or subsequent exercise performance. Potential benefits may be mediated via physical, physiological or psychological effects, although underlying mechanisms are typically not well elucidated. Despite widespread acceptance of CGs by competitive and recreational athletes, convincing scientific evidence supporting ergogenic effects remains somewhat elusive. The literature is fragmented due to great heterogeneity among studies, with variability including the type, duration and intensity of exercise, the measures used as indicators of exercise or recovery performance/physiological function, training status of participants, when the garments were worn and for what duration, the type of garment/body area covered and the applied pressures. Little is known about the adequacy of current sizing systems, pressure variability within and among individuals, maintenance of applied pressures during one wear session or over the life of the garment and, perhaps most importantly, whether any of these actually influence potential compression-associated benefits. During exercise, relatively few ergogenic effects have been demonstrated when wearing CGs. While CGs appear to aid aspects of jump performance in some situations, only limited data are available to indicate positive effects on performance for other forms of exercise. There is some indication for physical and physiological effects, including attenuation of muscle oscillation, improved joint awareness, perfusion augmentation and altered oxygen usage at sub-maximal intensities, but such findings are relatively isolated. Sub-maximal (at matched work loads) and maximal heart rate appears unaffected by CGs. Positive influences on perceptual responses during exercise are limited. During recovery, CGs have had mixed effects on recovery kinetics or subsequent performance. Various power and torque measurements have, on occasions, benefitted from the use of CGs in recovery, but subsequent sprint and agility performance appears no better. Results are inconsistent for post-exercise swelling of limb segments and for clearance of myocellular proteins and metabolites, while effects on plasma concentrations are difficult to interpret. However, there is some evidence for local blood flow augmentation with compression. Ratings of post-exercise muscle soreness are commonly more favourable when CGs are worn, although this is not always so. In general, the effects of CGs on indicators of recovery performance remain inconclusive. More work is needed to form a consensus or mechanistically-insightful interpretation of any demonstrated effects of CGs during exercise, recovery or - perhaps most importantly - fitness development. Limited practical recommendations for athletes can be drawn from the literature at present, although this review may help focus future research towards a position where such recommendations can be made.
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We investigated the effect of gradual-elastic compression stockings (GCSs) on running economy (RE), kinematics, and performance in endurance runners. Sixteen endurance trained athletes (age: 34.73 ± 6.27 years; VO2max: 62.83 ± 9.03 ml·kg(-1)·min(-1); 38 minutes in 10 km; 1 hour 24 minutes in half marathon) performed in random order 4 bouts of 6 minutes at a recent half-marathon pace on a treadmill to evaluate RE with or without GCSs. Subsequently, 12 athletes were divided into 2 equal groups matched by their VO2max, and they performed a time limit test (T(lim)) on a treadmill at 105% of a recent 10-km pace with or without GCSs for evaluation of physiological responses and running kinematics. There were no significant differences in the RE test in all of the variables analyzed for the conditions, but a moderate reproducibility for some physiological responses was detected in the condition with GCSs. In the T(lim), the group that wore GCSs reached a lower % of maximum heart rate (HRmax) compared with the control group (96.00 ± 2.94 vs. 99.83 ± 0.40) (p = 0.01). Kinematics did not differ between conditions during the T(lim) (p > 0.05). There were improvement trends for time to fatigue (337 vs. 387 seconds; d = 0.32) and a lower VO2peak (≈53 vs. 62 ml·kg(-1)·min(-1); d = 1.19) that were detected with GCSs during the T(lim). These results indicate that GCSs reduce the % of HRmax reached during a test at competition pace. The lower reproducibility of the condition with GCSs perhaps suggests that athletes may possibly need an accommodation period for systematically experiencing the benefits of this garment, but this hypothesis should be further investigated.
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The aim of this study was to examine the effects of wearing different grades of graduated compression stockings (GCS) on 10-km running performance. After an initial familiarization run, 9 male and 3 female competitive runners (VO₂max 68.7 ± 5.8 ml·kg⁻¹·min⁻¹) completed 4 10-km time trials on an outdoor 400-m track wearing either control (0 mm Hg; Con), low (12-15 mm Hg; Low), medium (18-21 mm Hg; Med), or high (23-32 mm Hg; Hi) GCS in a randomized counterbalanced order. Leg power was assessed pre and postrun via countermovement jump using a jump mat. Blood-lactate concentration was assessed pre and postrun, whereas heart rate was monitored continuously during exercise. Perceptual scales were used to assess the comfort, tightness, and any pain associated with wearing GCS. There were no significant differences in performance time between trials (p = 0.99). The change in pre to postexercise jump performance was lower in Low and Med than in Con (p < 0.05). Mean heart rate (p = 0.99) and blood lactate (p = 1.00) were not different between trials. Participants rated Con and Low as more comfortable than Med and Hi (p < 0.01), Med and Hi were rated as tighter than Low (p < 0.01), all GCS were rated as tighter than Con (p < 0.01), and Hi was associated with the most pain (p < 0.01). In conclusion, GCS worn by competitive runners during 10-km time trials did not affect performance time; however Low and Med GCS resulted in greater maintenance of leg power after endurance exercise. Athletes rated low-grade GCS as most comfortable garments to wear during exercise.
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The current study examined variability and fluctuation in the running gait cycle, focusing on differences between trained distance runners and non-runners. The two groups of participants performed treadmill running at 80%, 100%, and 120% of their preferred speed for 10 min. Stride-interval time-series were recorded during running using footswitches. The average preferred speed was significantly higher for the trained runners than for the non-runners. The trained runners showed significantly smaller variability of stride interval than did the non-runners, and at the same time the scaling exponent alpha evaluated by detrended fluctuation analysis tended to be smaller for the trained runners. These results suggest that expert runners can reduce variability in the trained movement without loosing dynamical degrees of freedom for spatiotemporal organization of the gait pattern.
The purpose of this study was to determine whether compression shorts affected vertical jump performance. Subjects, 18 men and 18 women varsity volleyball players, were thoroughly familiarized with the jump tests and experimental techniques. Testing utilized compression shorts of normal fit (CS), undersized compression shorts (UCS), and loose fitting gym shorts as the control garment (CT). All tests were conducted on the same day using a balanced, randomized block design to remove day-to-day variation. Jumps were performed on an AMTI force plate interfaced to a computer with customized software to determine jump force and power. Ten consecutive maximal countermovement jumps with hands held at waist level were evaluated. The garments had no effect on maximal force or power of the highest jump. However, mean force and power production over the 10 jumps when wearing the CS were significantly (p < 0.05) higher than CT for both men and women. In men the UCS mean power production was also higher than the CT. The data indicate that compression shorts, while not improving single maximal jump power, have a significant effect on repetitive vertical jumps by helping to maintain higher mean jumping power.