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A Comparison of the Energetic Cost of Running in Marathon Racing Shoes

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Background Reducing the energetic cost of running seems the most feasible path to a sub-2-hour marathon. Footwear mass, cushioning, and bending stiffness each affect the energetic cost of running. Recently, prototype running shoes were developed that combine a new highly compliant and resilient midsole material with a stiff embedded plate. Objective The aim of this study was to determine if, and to what extent, these newly developed running shoes reduce the energetic cost of running compared with established marathon racing shoes. Methods18 high-caliber athletes ran six 5-min trials (three shoes × two replicates) in prototype shoes (NP), and two established marathon shoes (NS and AB) during three separate sessions: 14, 16, and 18 km/h. We measured submaximal oxygen uptake and carbon dioxide production during minutes 3–5 and averaged energetic cost (W/kg) for the two trials in each shoe model. ResultsCompared with the established racing shoes, the new shoes reduced the energetic cost of running in all 18 subjects tested. Averaged across all three velocities, the energetic cost for running in the NP shoes (16.45 ± 0.89 W/kg; mean ± SD) was 4.16 and 4.01% lower than in the NS and AB shoes, when shoe mass was matched (17.16 ± 0.92 and 17.14 ± 0.97 W/kg, respectively, both p < 0.001). The observed percent changes were independent of running velocity (14–18 km/h). Conclusion The prototype shoes lowered the energetic cost of running by 4% on average. We predict that with these shoes, top athletes could run substantially faster and achieve the first sub-2-hour marathon.
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ORIGINAL RESEARCH ARTICLE
A Comparison of the Energetic Cost of Running in Marathon
Racing Shoes
Wouter Hoogkamer
1
Shalaya Kipp
1
Jesse H. Frank
1
Emily M. Farina
2
Geng Luo
2
Rodger Kram
1
Published online: 16 November 2017
ÓThe Author(s) 2017. This article is an open access publication
Abstract
Background Reducing the energetic cost of running seems
the most feasible path to a sub-2-hour marathon. Footwear
mass, cushioning, and bending stiffness each affect the
energetic cost of running. Recently, prototype running
shoes were developed that combine a new highly compliant
and resilient midsole material with a stiff embedded plate.
Objective The aim of this study was to determine if, and to
what extent, these newly developed running shoes reduce
the energetic cost of running compared with established
marathon racing shoes.
Methods 18 high-caliber athletes ran six 5-min trials (three
shoes 9two replicates) in prototype shoes (NP), and two
established marathon shoes (NS and AB) during three
separate sessions: 14, 16, and 18 km/h. We measured
submaximal oxygen uptake and carbon dioxide production
during minutes 3–5 and averaged energetic cost (W/kg) for
the two trials in each shoe model.
Results Compared with the established racing shoes, the
new shoes reduced the energetic cost of running in all 18
subjects tested. Averaged across all three velocities, the
energetic cost for running in the NP shoes
(16.45 ±0.89 W/kg; mean ±SD) was 4.16 and 4.01%
lower than in the NS and AB shoes, when shoe mass was
matched (17.16 ±0.92 and 17.14 ±0.97 W/kg,
respectively, both p\0.001). The observed percent chan-
ges were independent of running velocity (14–18 km/h).
Conclusion The prototype shoes lowered the energetic cost
of running by 4% on average. We predict that with these
shoes, top athletes could run substantially faster and
achieve the first sub-2-hour marathon.
Key Points
Recently, running shoes were developed that
combine a new highly compliant and resilient
midsole material with a stiff embedded plate.
We showed that these newly developed running
shoes reduce the energetic cost of running by an
average of 4% compared with established marathon
racing shoes.
We predict that with these shoes, top athletes can run
substantially faster and achieve the first sub-2-hour
marathon.
1 Introduction
Like the quest to run the first sub-4-minute mile [1], the
possibility of running a sub-2-hour marathon has captivated
the interest of the public, athletes, and scientists [24]. The
world record for the 42.2 km (26.2 miles) marathon is
2:02:57 and thus a 1:59:59 time would require running
2.5% faster. Three physiological parameters generally
determine and predict the running velocity that can be
&Wouter Hoogkamer
wouter.hoogkamer@colorado.edu
1
Locomotion Lab, Department of Integrative Physiology,
University of Colorado, Boulder, 354 UCB, Boulder, CO
80309-0354, USA
2
Nike Sport Research Lab, One Bowerman Drive, Beaverton,
OR 97005, USA
123
Sports Med (2018) 48:1009–1019
https://doi.org/10.1007/s40279-017-0811-2
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sustained: the maximal rate of oxygen uptake (
_
VO2max), the
lactate threshold, and the energetic cost of running (running
economy) [5,6]. Running economy has traditionally been
defined as the rate of oxygen uptake in mL O
2
/kg/min
required to run at a specified velocity. However, since
oxygen uptake alone does not reflect metabolic substrate
differences [7], we prefer to define running economy as the
energetic cost of running at a specific velocity expressed in
W/kg. Among elite distance runners with a similar
_
VO2max
and lactate threshold, a runner with a better running
economy (i.e., lower energetic cost of running) can be
expected to outperform runners with a higher energetic cost
of running [8]. If an athlete can lower their energetic cost to
run at a specified velocity, then they should be able to run
faster with their existing physiological capacities [9].
Footwear mass, cushioning, and longitudinal bending
stiffness each affect the energetic cost of running. Lighter
running shoes reduce the energetic cost of running [10,11],
likely due to the reduced inertia for leg swing. Such
energetic savings directly translate to faster performance
[9]. Running barefoot might seem optimal since it involves
zero shoe mass, but barefoot running is not energetically
optimal because it requires greater muscular effort for
cushioning the foot–ground impact [12,13]. Experiments
using special treadmills with springy or cushioned surfaces
have demonstrated up to 12% energy savings [13,14] that
are attributed to two factors. First, cushioning allows a
person to run with straighter legs (less knee flexion) and
thus less muscular effort [14,15]. Second, treadmill sur-
faces can store and return mechanical energy [14,16,17].
Virtually all modern running shoes have midsoles made
from various foam materials that, to varying degrees,
cushion impact, store and return mechanical energy. The
amount of energy stored by a foam material depends on its
compliance—the amount of compression that occurs when
loaded with a certain force. Compliant foams are commonly
described as soft. Inevitably, all foams are viscoelastic; i.e.,
they dissipate some energy as heat [18]. The percent of the
stored mechanical energy that is returned is called resilience.
Some materials/surfaces are compliant, but have low resi-
lience (e.g., a sandy beach) and thus increase the energetic
cost of running [19]. However, compliance and resilience
are not mutually exclusive and new materials continue to
advance shoe technology. Recently, more compliant and
resilient shoe midsoles have been shown to reduce the
energetic cost of running by *1% [20]. Taking these
observations together, theoretically, the best running shoe
foam would be lightweight, highly compliant, and resilient.
Running shoes can also enhance how the human foot
acts like a lever [21] to transmit the force developed by the
leg muscles (e.g., the calf) to the ground so that the body is
propelled upward and forward. To do so, scientists have
incorporated carbon-fiber plates into the midsole, thereby
increasing the longitudinal bending stiffness. Such plates
can reduce the energetic cost of running by *1% [22]
through changes in the leverage of the ankle joint and the
foot–toe joint (metatarsophalangeal joint) [2224].
Recently, prototype running shoes were developed by
Nike, Inc. that combine a new highly compliant and resilient
midsole material with a stiff embedded plate (Fig. 1). The
purpose of this study was to determine if, and to what extent,
these newly developed running shoes reduce the energetic
cost of running (i.e. improve running economy) compared
with established marathon racing shoes. We compared both
the energetics and gross biomechanics of running in the
Nike prototype shoes (NP) with those of baseline marathon
racing shoes, the Nike Zoom Streak 6 (NS) and the shoes
used to run the official marathon world record, the adidas
adizero Adios BOOST 2 (AB). The NS and AB or their
predecessors were used to run the 10 fastest marathons prior
to the start of this study (early April 2016).
We hypothesized that the energetic cost of running
would be substantially reduced in the prototype shoes as
compared with the two established marathon racing shoe
models. We had no a priori hypotheses regarding biome-
chanics, but collected the data to possibly explain any
energetic differences found. Furthermore, we set out to
relate any potential reductions in the energetic cost of
running in the prototype shoes to elite marathon running
performance and the sub-2-hour marathon barrier.
2 Materials and Methods
2.1 Shoe Conditions
We compared new prototype shoes (NP, a prototype of the
recently released Nike Zoom Vaporfly) to baseline
Fig. 1 Exploded view of the Nike prototype shoe that incorporates a
newly developed midsole material and a full-length carbon-fiber plate
with forefoot curvature, embedded in the midsole
1010 W. Hoogkamer et al.
123
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marathon racing shoes, the Nike Zoom Streak 6 (NS), and
the shoes that Dennis Kimetto wore when he set the current
marathon world record, the adidas adizero Adios BOOST 2
(AB) (Fig. 3). We added 51 and 47 g of lead pellets to the
NP and NS shoes, respectively, to equalize to the greater
mass of the AB shoes (250 g for size US10). This pre-
vented the confounding effects of shoe mass on the ener-
getic cost of running [911]. To prevent excessive wear
accumulation in the shoes, we used three pairs of each shoe
model in size US10 and two additional pairs of AB size
US9.5, because that model fits a little bigger than the Nike
models. Total running use for any pair of shoes did not
exceed 50 km.
2.2 Mechanical Testing Protocol
To evaluate the relevant midsole properties, we used a
custom mechanical testing method developed in the Nike
Sport Research Lab. Rather than a more conventional
energy-constrained impact test [25], we implemented a
force-constrained mechanical testing approach [20,26].
This method allows for more realistically quantifying of
underfoot mechanical energy storage and return. We per-
formed the shoe mechanical testing after the running tests
to obviate possible cushioning inconsistencies that can
arise during an initial midsole ‘break-in’ period.
To properly execute a force-constrained mechanical
test, the compression force and regional distribution of
force needs to resemble that of human running. To
implement this, we mounted a rigid foot-form (shoe last)
to a material testing machine (Instron 8800 Series Ser-
vohydraulic System, Norwood, MA, USA) and snugly fit
the foot-form into the fully constructed shoes (Fig. 2).
The material testing machine compressed the midsole in
the vertical direction by matching a general time history
of the vertical ground reaction force measured during
running. The force profile had a peak magnitude
of *2000 N and a contact time of *185 ms, which is
similar to the loading that we measured for our subjects
at 18 km/h (Table 2). The foot-form shape and its
material testing machine attachment location produced
insole pressure patterns and magnitudes similar to those
recorded during running. We calculated the amount of
mechanical energy stored and returned for each shoe
condition from the area under the rising (storage) and
falling (return) portions of the force-deformation curves.
This custom test is limited to 1-dimensional actuation of
force over a pre-defined contact region. True running force
fidelity would require 3-dimensional forces, with options
for different loading phases to impart load on different
regions of the midsole. In addition, the way each runner
interacts with a shoe can vary due to many factors
including body mass, running velocity, and foot strike
pattern. Though limited, this simplified testing method
does provide a clean, general characterization of midsole
mechanical energy storage and return capabilities in a
direction relevant to the spring-mass behavior of runners
[27].
The mechanical testing revealed that the NP was
approximately twofold more compliant than the NS and
AB shoes, deforming 11.9 mm versus 6.1 and 5.9 mm,
respectively (Fig. 3). The NP stored substantially more
mechanical energy (area under the top trace). Furthermore,
the NP shoes were more resilient (87.0% energy return)
than the AB (75.9%) and NS (65.5%) shoes. Thus, com-
bined, the NP shoes can return more than twice the amount
of mechanical energy as the other shoes, which is mainly
due to its substantially greater compliance rather than the
greater percent resilience.
2.3 Human Subjects
18 male (aged 23.7 ±3.9 years, mass 64.3 ±4.7 kg, height
177.8 ±4.6 cm) high-caliber runners who wear men’s shoe
size US10 completed the testing protocol (
_
VO2max at the
local altitude *1655 m: 72.1 ±3.4 mL O
2
/kg/min, range
66.4–81.4 mL O
2
/kg/min). All had recently run a sub-
31 minute 10-km race at sea level, a sub-32 minute 10-km
race at the local altitude, or an equivalent performance in a
different distance running event. The study was performed
Fig. 2 A rigid foot-form (shoe last) was mounted to the material
testing machine actuator and snugly fit into a fully-constructed shoe.
The actuated foot-form compressed the midsole in the vertical
direction to match the displayed general time history of the vertical
ground reaction force, producing insole pressure patterns similar to
those recorded during running at 18 km/h
Energetic Cost of Running Shoes 1011
123
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in accordance with the ethical standards of the Declaration
of Helsinki. Ethics approval was obtained from the
University of Colorado Institutional Review Board (Pro-
tocol# 15-0114). Before taking part in the study, partici-
pants provided informed written consent.
2.4 Experimental Protocol
The study comprised four visits for each subject. Visit 1
established that subjects could run below their lactate
threshold [28] at 14, 16, and 18 km/h by measuring blood
lactate concentrations ([La]). During visits 2, 3, and 4, we
measured the subjects’ metabolic energy consumption rates,
ground reaction forces, and [La] at 14, 16, or 18 km/h while
wearing each of the three shoe conditions.
Subjects presented a 24-h dietary, sleep, and training log
before each visit. We strongly encouraged the subjects to
replicate their diet, sleep, and training pattern for all lab-
oratory visits. If replication was not met, we postponed the
testing.
2.4.1 Visit 1
Subjects wore their own shoes to run 5-min trials at
velocities of 14, 16, and 18 km/h on a level treadmill and
took a 5-min break between all trials. We used a hand-held
digital tachometer (Shimpo DT-107A, Electromatic
Equipment Inc., Cedarhurst, NY, USA) to verify the
treadmill velocities. To allow familiarization, subjects
breathed through the expired-gas analysis system during
Fig. 3 We performed mechanical testing on three marathon racing
shoe models. (Top left) The Nike Zoom Streak 6 (NS) midsole
comprises lightweight EVA (ethylene-vinyl acetate) foam, a rearfoot
Zoom air bag, 23 mm heel height, and 15 mm forefoot height. (Top
middle) The adidas adizero Adios BOOST 2 (AB) midsole comprises
BOOST foam made with TPU (thermoplastic polyurethane), 23 mm
heel height, and 13 mm forefoot height. (Top right) The Nike
prototype (NP) midsole comprises a new ZoomX foam made with
PEBA (polyether block amide), an embedded carbon fiber plate,
31 mm heel height, and 21 mm forefoot height. (Bottom) Force-
deformation curves, peak deformation, and energy return metrics for
each shoe during vertical midsole loading with a peak force
of *2000 N and contact time of *185 ms (Table 2). As vertical
force is applied, the shoe midsole deforms (upper trace in each graph).
Then, as the shoe is unloaded, the force returns to zero as the midsole
recoils (lower trace in each graph). The area between loading and
unloading curves indicates the mechanical energy (J) lost as heat. The
area below the lower traces represents the amount of elastic energy
(J) that is returned
1012 W. Hoogkamer et al.
123
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this session (True One 2400, Parvo Medics, Salt Lake City,
UT, USA). Within 1 min after the completion of each 5-min
trial, we obtained a finger-prick blood sample for [La]
determination. We analyzed the blood samples in duplicate
with a YSI 2300 lactate analyzer (YSI, Yellow Springs, OH,
USA). Two individuals were excluded from the study after
Visit 1, reaching [La] values of 5.27 and 5.69 mmol/L at
18 km/h. The remaining 18 subjects were running at an
intensity below the onset of blood lactate accumulation
(OBLA), which specifies an [La] of 4 mmol/L [28], and the
average [La] at 18 km/h was 2.81 ±0.71 mmol/L.
2.4.2 Visits 2, 3, and 4
Subjects began with a 5-min warm-up trial at 14 km/h in
their own shoes. Following the warm up, subjects com-
pleted six 5-min trials at one of the three velocities (14,
16, or 18 km/h, randomized) on a level force-measuring
treadmill with a rigid, reinforced aluminum deck, that
recorded horizontal and vertical ground reaction forces
[29]. We measured the submaximal rates of oxygen
consumption and carbon dioxide production during each
trial using the expired-gas analysis system and calculated
the rate of metabolic energy consumption over the last
2 min of each trial, using the Brockway equation [30]. In
each of the six trials, subjects wore one of the three shoe
conditions. In between trials, subjects took a 5-min break
while they changed shoes. Note that runners mechanically
adapt their biomechanics very quickly in response to
changes in surface stiffness [31]. Subjects wore each shoe
model twice per visit, in a mirrored order, which was
counterbalanced and randomly assigned. With three shoe
conditions, there were six possible shoe orders and we
randomly assigned three subjects to each order. One
example of a mirrored order is AB, NS, NP, NP, NS, AB.
For all metrics, we averaged the two trials for each shoe
condition.
During the last 30 s of each trial, we recorded high-
speed video (240 frames/s, 1/1000 s shutter) using a Casio
EX-FH20 camera (Casio America, Inc., Dover, NJ, USA).
During the same 30 s, we recorded horizontal and vertical
ground reaction forces using a National Instruments
6009-DAQ and custom-written LabView software (Na-
tional Instruments, Austin, TX, USA). We low-pass filtered
the ground reaction force data at 25 Hz using a recursive
4th order Butterworth digital filter and used a 30 N
threshold to determine foot-strike and toe-off events. We
used the video recordings to help determine the foot strike
patterns of the runners during all trials (rearfoot strike vs.
mid/forefoot strike). This was done by two raters (SK and
JHF) independently. When the video-based classification
disagreed between raters (n=4), strike pattern was
classified based on visual inspection of the vertical ground
reaction force traces by a third rater (WH).
Following the sixth trial on each day, subjects ran an
additional trial at 14 km/h in a pair of control shoes (Nike
Zoom Streak LT 2). This allowed us to measure the indi-
vidual day-to-day variation in energetic cost of the subjects.
Only during visit 4, after a 10-min break, the subjects
completed a
_
VO2max test on a classic Quinton 18–60
treadmill. We set the treadmill velocity to 16 km/h and
increased the incline by 1% each minute until exhaustion
[32]. Subjects wore their own shoes or the control shoes. We
continuously measured the rate of oxygen consumption and
defined
_
VO2max as the highest 30-s mean value obtained.
Our criterion for reaching
_
VO2max was a plateau in oxygen
consumption rate after an increase in incline [33].
2.5 Statistics
We compared energetic cost, peak vertical ground reaction
force, step frequency and contact time while running in the
three shoe conditions over three velocities using a two-way
ANOVA with repeated measures. When we observed a
significant main effect for shoe, we performed Tukey’s
honest significant difference post hoc analyses to determine
which shoe-by-shoe comparisons differed significantly. To
evaluate any potential effects of foot strike pattern, we
compared energetic cost, peak vertical ground reaction
force, step frequency, and contact time using a three-way
ANOVA with repeated measures (shoe 9veloc-
ity 9strike pattern). Furthermore, we applied multiple
regression analyses to evaluate potential relationships
between changes in biomechanical measures and in ener-
getic cost of running. We used a traditional level of sig-
nificance (p\0.05) and performed analyses with
MATLAB (The MathWorks, Inc., Natick, MA, USA) and
STATISTICA (Statsoft, Tulsa, OK, USA).
To estimate how much of an improvement in marathon
running performance would be predicted from a specific
reduction in energetic cost, we used the curvilinear rela-
tionship between running velocity and energy cost estab-
lished by Tam et al. [34]. Their model was based on
overground running data in top-level Kenyan marathon
runners:
_
VO2(mL O
2
/kg/min) =5.7 ?9.8158 V ?0.0537 V
3
with velocity (V) in m/s.
3 Results
The prototype shoes substantially lowered the energetic
cost of running by 4% on average. Notably, at all three
running velocities, energetic cost was lower in NP for each
Energetic Cost of Running Shoes 1013
123
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and every subject compared with both NS and AB (Fig. 4).
Averaged across all three velocities, the energetic cost for
running in the NP shoes (16.45 ±0.89 W/kg; mean ±SD)
was 4.16 and 4.01% lower than in the NS and AB shoes
(17.16 ±0.92 and 17.14 ±0.97 W/kg, respectively, both
p\0.001). The NS and AB shoes were similar (p=0.34).
The percent differences between shoes were similar at the
three running velocities (all p[0.56). Among the 18 sub-
jects, the mean difference in energetic cost over the three
velocities between the NP and NS shoes ranged from -1.59
to -6.26% and from -1.97 to -6.08% for NP versus AB,
indicating considerable inter-individual variation in the
amount of energetic saving the NP shoes provided. For
reference, rates of oxygen uptake, energetic cost of trans-
port, and the oxygen cost of transport for each of the three
shoe models at all three velocities are listed in Table 1.
Respiratory exchange ratios (
_
VCO2/
_
VO2)
remained\0.9 for all trials and [La] values after six trials
were\3 mmol/L for all velocities, but we did detect a
slight slow component in our recordings of oxygen con-
sumption. Across all conditions, the rate of oxygen con-
sumption averaged 1.0% greater during minute 5 versus
minute 4 (p\0.001). This was independent of shoe con-
dition and running velocity, and all the differences between
conditions were consistent for both minutes (all p[0.39).
For the control shoes at 14 km/h, the mean day-to-day
difference in energetic cost was 2.7%, the mean minimum
day-to-day difference was 1.0% and the mean maximum
day-to-day difference was 4.3%. Recall that we random-
ized and counterbalanced the order in which subjects ran at
each of the three velocities (14, 16, 18 km/h) to balance out
this day-to-day variation. Since subjects wore each pair of
shoes twice per visit, in a mirrored order, we could quantify
within-day variation. The mean absolute variation over all
running velocities and shoe conditions was 1.7%.
While running in the NP shoes, the subjects generally
ran with slightly greater peak vertical ground reaction
forces, slower step frequencies, and longer contact times
than in the control shoes (Fig. 5; Table 2). Peak vertical
ground reaction force (F
z
) was 1.1% greater in the NP
shoes than in the NS shoes (p=0.002) and increased at
faster running velocities in all shoes (all p\0.001). Step
frequency was 0.8 and 0.6% slower in the NP shoes than in
the NS and AB shoes, respectively; that is, slightly longer
steps in NP (both p\0.001). Step frequency increased at
the faster running velocities in all shoes (all p\0.001).
Contact time was slightly (0.6%) longer in the NP shoes
than in the NS shoes (p=0.020) and decreased at faster
running velocities in all shoes (all p\0.001). Together, the
percent changes in peak F
z
, step frequency, and contact
time explained 20% of the variance in the reductions in
energetic cost between NS and NP (p=0.009). Peak F
z
was the only individual biomechanical factor contributing
significantly and energetic savings were paradoxically
correlated to increases in peak F
z
. The changes in energetic
cost between AB and NP or between NS and AB were not
significantly correlated to changes in biomechanical mea-
sures (p=0.095 and p=0.8, respectively).
Although we did not set out to evaluate the foot strike
pattern interaction on the energetic cost differences
between shoes, our sample of runners did allow for such an
analysis. Eight of our subjects landed on their heels and ten
landed on their mid/forefoot. Overall, the energetic cost of
running was not different between rearfoot strikers and
mid/forefoot strikers (p=0.9; Table 3). However, a
shoe 9foot strike pattern interaction effect (p=0.0502)
suggests that the savings in the NP shoes were likely
somewhat greater for rearfoot strikers (NP vs. NS: 4.78%;
NP vs. AB: 4.63%) than for mid/forefoot strikers (3.67 and
3.50%, respectively). We did not observe significant
shoe 9foot strike interactions for any of the biomechani-
cal parameters, but rearfoot strikers ran with longer contact
times than mid/forefoot strikers (p=0.001; Table 3).
4 Discussion
The prototype shoes substantially lowered the energetic
cost of running by 4% on average. Shoe properties such as
mass, midsole compliance, resilience, and longitudinal
bending stiffness have all been shown to affect the ener-
getic cost of running [20,22]. However, reported energetic
savings due to running shoe properties are typically trivial
to small [35]. For every 100 g of added mass per shoe, the
energetic cost of running increases by *1.0%. To prevent
the confounding effects of shoe mass on the energetic cost
NS AB NP
12
14
16
18
20
22
24
NS AB NP NS AB NP
Energetic Cost (W/kg)
14 km/h 16 km/h 18 km/h
Fig. 4 Over the three velocities tested, runners in the NP shoes used
an average of 4.16% less metabolic energy than the NS shoes and
4.01% less than in the AB shoes (both p\0.001). The AB and NS
shoes were similar (p=0.34). Values are the gross energetic cost of
running. NS Nike Zoom Streak 6, AB adidas adizero Adios BOOST 2,
NP Nike prototype
1014 W. Hoogkamer et al.
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of running [911], we added 51 and 47 g of lead pellets to
the NP and NS shoes, respectively, to equalize to the
greater mass of the AB shoes. This suggests that
unweighted NP shoes would likely save an average
of *4.4% versus AB; assuming a conservative 0.8%
savings per 100 g of shoe mass [9,10]. Midsole air bag and
BOOST foam (made with thermoplastic polyurethane)
cushioning have each been shown to reduce the energetic
cost of running by 1–2.8% [12,36] or 1.1% [20], respec-
tively, as compared with conventional EVA (ethylene-
vinyl acetate) foam. Here, we compared the NP shoes to
two established marathon racing shoe models, which
incorporate either an air bag or BOOST foam, and find an
additional 4% savings with the new shoes.
While the observed differences in energetic cost of
running between shoe conditions were as substantial as 4%,
the differences in our gross biomechanical measures (i.e.,
peak F
z
, step frequency, and contact time) were on the
order of only 1% (Table 2). Subjects ran with slower step
frequency, taking longer steps in the NP shoes. This is in
line with the observed higher peak F
z
and longer contact
time in the NP shoes compared with the NS shoes. How-
ever, differences of\1% in these variables seem too small
to have a substantial influence on energetic cost of running.
This was confirmed by the multiple regression analyses
between the percent changes in each of the biomechanical
measures and in the energetic cost. A significant correlation
was only observed for the differences between NS and NP,
with changes in biomechanics explaining\20% of the
energetic differences. Further, the differences in peak F
z
and in contact time were only significant between NP and
NS, not between NP and AB, even though energetic sav-
ings for NP were similar to those for NS and AB.
Although gross measures of biomechanics showed little
differences between the different shoes, a biomechanical
explanation for the energetic savings is important to con-
sider. When running on compliant surfaces, people main-
tain their center of mass mechanics by reducing knee
flexion during the stance period, which increases leg
stiffness [31]. This improves the mechanical advantage of
the muscles acting around the joints, which reduces the
energetic cost of body weight support [14,37]. This same
mechanism likely contributes to the energy savings of the
very compliant NP shoes. However, we did not record joint
kinematics in the present study and thus cannot yet quan-
tify any differences in peak knee flexion during stance in
the different shoes.
For now, the elastic properties of the NP shoes provide
the best explanation for the metabolic energy savings. Our
mechanical testing quantified that the NP shoes returned
7.46 J of mechanical energy per step versus 3.38 and 3.56 J
for the NS and AB shoes, respectively (Fig. 3). The greater
mechanical energy return in the NP shoes is mainly due to
Table 1 Energetic costs, rates of oxygen uptake (
_
VO2), energetics cost of transport (ECOT) and oxygen costs of transport (O
2
COT) for each of the three shoe models at all three speeds
14 km/h 16 km/h 18 km/h
NS AB NP NS AB NP NS AB NP
Energetic cost (W/kg) 14.17 ±0.82 14.13 ±0.84 13.57 ±0.76 17.07 ±1.02 17.03 ±1.02 16.36 ±0.99 20.26 ±1.06 20.25 ±1.18 19.42 ±1.08
VO
2
(mL O
2
/kg/min) 41.97 ±2.39 41.87 ±2.45 40.24 ±2.19 50.30 ±2.91 50.19 ±2.92 48.27 ±2.87 59.62 ±3.08 59.57 ±3.40 57.26 ±3.10
ECOT (J/kg/m) 60.72 ±3.52 60.57 ±3.59 58.15 ±3.25 64.00 ±3.83 63.85 ±3.84 61.36 ±3.71 67.52 ±3.55 67.49 ±3.94 64.72 ±3.60
O
2
COT (mL O
2
/kg/km) 179.9 ±10.3 179.4 ±2.5 172.5 ±9.4 188.6 ±10.9 188.2 ±10.9 181.0 ±10.6 198.7 ±10.3 198.6 ±11.3 190.9 ±10.4
NS Nike Zoom Streak 6, AB adidas adizero Adios BOOST 2, NP Nike prototype
Values presented are mean ±SD
Energetic Cost of Running Shoes 1015
123
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its substantially greater compliance rather than the greater
percent resilience. For context, the arch of the human foot
and Achilles tendon return 17 and 35 J of stored energy,
respectively, during running at 16.2 km/h [38]. Other
ligaments and tendons of the leg store and return additional
energy [39,40]. Thus, regardless of the shoes worn, in
human running, the vast majority of the mechanical energy
storage and return occurs within our natural biological
structures. However, to operate the tendons as springs, the
muscles that connect tendons to bones must actively con-
tract, which consumes metabolic energy [41]. In contrast,
running shoes with elastic midsoles and stiffening plates
may reduce rather than require the generation of muscular
force.
How much of an improvement in running performance
would be predicted from a 4% reduction in energetic cost?
Hoogkamer et al. [9] established that percent changes in
the energetic cost of running due to altered shoe mass
translate to similar percent changes in 3000-m running
performance, when both are evaluated at the same running
velocity. But, as recently summarized by Hoogkamer et al.
[3], the energetic cost of overground running increases
curvilinearly with velocity, due in part to air resistance.
Such curvilinearity implies that a 4% average energetic
savings observed should translate to *3.4% improvement
in running velocity at marathon world record pace
(20.59 km/h) [3,34]. Consistent with that calculation, in
the two years leading up to her amazing world record in the
women’s marathon in 2003, directed training allowed
Mid/forefoot strikers
0
1
2
3
Rearfoot strikers
time (ms)
0 50 100 150 200
time (ms)
0 50 100 150 200
-0.5
0
0.5
NP
NS
AB
F
z
(BW)
F
y
(BW)
Fig. 5 Average vertical (F
z
; top) and anterior–posterior ground
reaction force traces (F
y
; bottom) in the three different shoe models
for runners with rearfoot strike pattern (n=8) (left) and midfoot or
forefoot strike pattern (n=10) (right) during the 16-km/h trials.
Force traces are normalized to body weight (BW). Initial impact and
active F
z
peaks were greater for the rearfoot strikers in the NP shoes.
F
z
recordings for mid/forefoot strikers were similar in the three shoes.
NS Nike Zoom Streak 6, AB adidas adizero Adios BOOST 2, NP Nike
prototype
Table 2 While running in the NP shoe, the subjects generally ran with slightly greater peak vertical ground reaction forces, slower step
frequencies and longer contact times than in the control shoes
NS AB NP
Peak F
z
(BW) *
14 km/h 2.88 ±0.19 2.89 ±0.20 2.92 ±0.20
16 km/h 2.98 ±0.19 3.00 ±0.19 3.00 ±0.17
18 km/h 3.11 ±0.18 3.14 ±0.18 3.13 ±0.18
Step frequency (Hz) * *
14 km/h 2.90 ±0.14 2.89 ±0.15 2.87 ±0.14
16 km/h 2.97 ±0.15 2.97 ±0.16 2.96 ±0.15
18 km/h 3.05 ±0.16 3.04 ±0.16 3.02 ±0.16
Contact time (ms) *
14 km/h 212 ±8 212 ±8 213 ±8
16 km/h 197 ±8 196 ±7 197 ±7
18 km/h 180 ±5 181 ±5 182 ±5
Peak vertical ground reaction forces (F
z
) are normalized to body weight (BW)
NS Nike Zoom Streak 6, AB adidas adizero Adios BOOST 2, NP Nike prototype
Values presented are mean ±SD
*Indicates significantly different from NP shoes across running velocities
1016 W. Hoogkamer et al.
123
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Paula Radcliffe to reduce her energetic cost of running at
16 km/h by 2.8% and marathon performance by 2.4% [42].
An acute 3.4% improvement in the marathon world record
would be historic. For example, it took nearly 29 years for
the men’s marathon record to be reduced by *3.4% to the
current 2:02:57, and not since 1952 has the men’s marathon
record been broken by more than 3.4% in one race.
Note that we empirically compared the shoes up to a
running velocity of 18 km/h, about 13% slower than the
average marathon world record velocity. It was challenging
to recruit 18 runners who could sustain 18 km/h below
lactate threshold and also fit the available size US10 pro-
totypes. Therefore, we tested a range of velocities to
determine if any energy savings were dependent on running
velocity. Over the tested velocity range of 14–18 km/h, the
percent savings were constant. The energetic cost of run-
ning for elite marathon runners is likely lower than in our
high-caliber, sub-elite runners [43,44], and the energetic
cost of running may slowly increase over the duration of a
marathon [45], due to slow component increases in oxygen
uptake kinetics [46] and muscle damage [47], as compared
with the energy cost values we observed. How the 4%
savings we observed, interact with all these variables
remains to be determined.
In conclusion, the new running shoes described herein
provide 4% energetic savings. Our extrapolations suggest
that with these shoes the technology is in place to break the
2-h marathon barrier. Now, it is up to the athletes to make
it happen.
Acknowledgements We thank the subjects for participating, Sewan
Kim for his help with analyzing the blood samples, Xu Cheng for
helping set up the mechanical testing, Joel Greenspan for his help
with the illustrations, and Max Donelan and Andrew Jones for helpful
feedback and comments regarding an earlier version of this
manuscript.
Compliance with Ethical Standards
Ethical approval The study was performed in accordance with the
ethical standards of the Declaration of Helsinki. Ethics approval was
obtained from the University of Colorado Institutional Review Board
(Protocol# 15-0114).
Informed consent Informed consent was obtained from all individ-
ual participants included in the study.
Funding This study was supported by a contract from Nike, Inc. with
the University of Colorado, Boulder.
Conflict of interest Wouter Hoogkamer, Shalaya Kipp, and Jesse H.
Frank have no conflicts of interest relevant to the content of this
article. Emily M. Farina and Geng Luo are employees of Nike, Inc.
Rodger Kram is a paid consultant to Nike, Inc.
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted
Table 3 Energetic costs and biomechanics variables for each of the three shoe models at all three speeds, separated by foot strike type
14 km/h 16 km/h 18 km/h
NS AB NP NS AB NP NS AB NP
Energetic cost (W/kg) rearfoot strike 14.21 ±0.91 14.17 ±0.81 13.54 ±0.82 17.09 ±0.96 17.01 ±0.98 16.25 ±0.95 20.40 ±1.27 20.44 ±1.41 19.43 ±1.31
Energetic cost (W/kg) mid/forefoot strike 14.13 ±0.79 14.10 ±0.90 13.59 ±0.75 17.05 ±1.12 17.04 ±1.11 16.45 ±1.06 20.15 ±0.92 20.10 ±1.01 19.40 ±0.93
Peak F
z
(BW) rearfoot strike 2.81 ±0.16 2.82 ±0.16 2.85 ±0.16 2.93 ±0.13 2.95 ±0.12 2.97 ±0.12 3.05 ±0.12 3.09 ±0.14 3.09 ±0.13
Peak F
z
(BW) mid/forefoot strike 2.93 ±0.21 2.94 ±0.24 2.98 ±0.24 3.02 ±0.23 3.04 ±0.23 3.03 ±0.21 3.15 ±0.23 3.17 ±0.21 3.17 ±0.21
Step frequency (Hz) rearfoot strike 2.86 ±0.14 2.85 ±0.13 2.84 ±0.14 2.93 ±0.13 2.92 ±0.13 2.89 ±0.13 3.00 ±0.13 2.99 ±0.13 2.96 ±0.12
Step frequency (Hz) mid/forefoot strike 2.93 ±0.15 2.93 ±0.16 2.90 ±0.16 3.02 ±0.16 3.01 ±0.18 3.01 ±0.16 3.09 ±0.18 3.08 ±0.18 3.07 ±0.17
Contact time (ms) rearfoot strike 218 ±3 218 ±5 220 ±2 203 ±5 201 ±5 202 ±4 184 ±3 185 ±4 186 ±3
Contact time (ms) mid/forefoot strike 207 ±8 208 ±8 208 ±7 192 ±8 193 ±7 193 ±7 177 ±5 178 ±5 178 ±4
NS Nike Zoom Streak 6, AB adidas adizero Adios BOOST 2, NP Nike prototype, F
z
vertical ground reaction force, BW body weight
Values presented are mean ±SD
Energetic Cost of Running Shoes 1017
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... Unauthorized reproduction of this article is prohibited. (32), which have subsequently contributed to an improvement in elite endurance running performance (33). ...
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Purpose: Acute ingestion of a ketone monoester, with and without co-ingestion of carbohydrate, was investigated for effects on running economy (RE), time to exhaustion (TTE), and other related indices of endurance running performance. Methods: Using a three condition, placebo-controlled, randomized crossover design, eleven male middle- and long- distance runners ran at five submaximal speeds (10 to 14 km.h-1) on a motorized treadmill for 8 min each, immediately followed by a ramp test to volitional exhaustion. Participants consumed either a 10% carbohydrate solution (CHO), a 10% carbohydrate solution with 750 mg.kg-1 body mass of a (R)-3-hydroxybutyl (R)-3-hydroxybutyrate ketone monoester (CHO + KE), or 750 mg.kg-1 body mass of the ketone monoester in flavored water (KE) before (2/3 of the dose) and during (1/3 of the dose) exercise. Results: βHB concentration averaged 1.8 ± 0.3 mM and 2.1 ± 0.3 mM during exercise in CHO + KE and KE, respectively. RE was lower at each submaximal running speed (ES = 0.48 to 0.98) by an average of 4.1% in KE compared to CHO, but not between CHO + KE and CHO. TTE did not differ between CHO (369 ± 116 s), CHO + KE (342 ± 99 s), or KE (333 ± 106 s) (P = 0.093). Conclusions: Acute ingestion of a ketone monoester without carbohydrate, but not when co-ingested with carbohydrate, improved RE in middle- and long- distance runners at a range of submaximal running speeds, and did not alter TTE in a short duration ramp test to volitional exhaustion. Further investigation is required to examine if these differences translate into positive performance outcomes over longer durations of exercise.
... movement. While several passive [1]- [4] and powered [5]- [10] wearable devices have successfully reduced the energy cost of walking and running, designing novel assistive devices remains time consuming. It is challenging to predict how a device and human will interact, and, counterintuitively, the most effective devices do not simply replicate biological joint moments [11], [12]. ...
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Connecting the legs with a spring attached to the shoelaces, called an exotendon, can reduce the energetic cost of running, but how the exotendon reduces the energetic burden of individual muscles remains unknown. We generated muscle-driven simulations of seven individuals running with and without the exotendon to discern whether savings occurred during the stance phase or the swing phase, and to identify which muscles contributed to energy savings. We computed differences in muscle-level energy consumption, muscle activations, and changes in muscle-fiber velocity and force between running with and without the exotendon. The seven of nine participants who reduced energy cost when running with the exotendon reduced their measured energy expenditure rate by 0.9 W/kg (8.3%). Simulations predicted a 1.4 W/kg (12.0%) reduction in the average rate of energy expenditure and correctly identified that the exotendon reduced rates of energy expenditure for all seven individuals. Simulations showed most of the savings occurred during stance (1.5 W/kg), though the rate of energy expenditure was also reduced during swing (0.3 W/kg). The energetic savings were distributed across the quadriceps, hip flexor, hip abductor, hamstring, hip adductor, and hip extensor muscle groups, whereas no changes were observed in the plantarflexor or dorsiflexor muscles. Energetic savings were facilitated by reductions in the rate of mechanical work performed by muscles and their estimated rate of heat production. By modeling muscle-level energetics, this simulation framework accurately captured measured changes in whole-body energetics when using an assistive device. This is a useful first step towards using simulation to accelerate device design by predicting how humans will interact with assistive devices that have yet to be built.
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Endurance exercise performance is known to be closely associated with the three physiological pillars of maximal O2 uptake ( V ̇ O 2 max $\dot{V}_{{\rm O}_{2}{\rm max}}$ ), economy or efficiency during submaximal exercise, and the fractional utilisation of V ̇ O 2 max $\dot{V}_{{\rm O}_{2}{\rm max}}$ (linked to metabolic/lactate threshold phenomena). However, while 'start line' values of these variables are collectively useful in predicting performance in endurance events such as the marathon, it is not widely appreciated that these variables are not static but are prone to significant deterioration as fatiguing endurance exercise proceeds. For example, the 'critical power' (CP), which is a composite of the highest achievable steady-state oxidative metabolic rate and efficiency (O2 cost per watt), may fall by an average of 10% following 2 h of heavy intensity cycle exercise. Even more striking is that the extent of this deterioration displays appreciable inter-individual variability, with changes in CP ranging from <1% to ∼32%. The mechanistic basis for such differences in fatigue resistance or 'physiological resilience' are not resolved. However, resilience may be important in explaining superlative endurance performance and it has implications for the physiological evaluation of athletes and the design of interventions to enhance performance. This article presents new information concerning the dynamic plasticity of the three 'traditional' physiological variables and argues that physiological resilience should be considered as an additional component, or fourth dimension, in models of endurance exercise performance.
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There are concerns about the risk of injuries caused by marathons in China. Since male and female runners have different injury risks, gender differences in running shoe functionality should be further complemented. A supervised questionnaire survey of 626 marathon runners was collected. The questionnaire was categorized into four sections: (1) participant profile, (2) importance of shoe properties, (3) functional evaluation of shoe properties and (4) importance ranking of shoe properties. The Mann–Whitney U test, Fisher’s exact test of cross tabulation and Chi-square test, and two-way ANOVA were used to analyze the results of this survey. The significance level was set at P < 0.05. The full marathon participants were older than the half marathon participants. There was no gender difference in the importance of shoe features to elite runners. In addition, women are more concerned about upper elasticity and have higher requirements for running shoes than men. Women were more focused on injury prevention, while men were more focused on running performance. Heel cushioning was identified by all participants as the most important running shoe feature. There were no gender differences between elite players’ demand for running shoes, but significant gender differences were found between genders at other running levels.
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A sub-2-hour marathon requires an average velocity (5.86 m/s) that is 2.5% faster than the current world record of 02:02:57 (5.72 m/s) and could be accomplished with a 2.7% reduction in the metabolic cost of running. Although supporting body weight comprises the majority of the metabolic cost of running, targeting the costs of forward propulsion and leg swing are the most promising strategies for reducing the metabolic cost of running and thus improving marathon running performance. Here, we calculate how much time could be saved by taking advantage of unconventional drafting strategies, a consistent tailwind, a downhill course, and specific running shoe design features while staying within the current International Association of Athletic Federations regulations for record purposes. Specifically, running in shoes that are 100 g lighter along with second-half scenarios of four runners alternately leading and drafting, or a tailwind of 6.0 m/s, combined with a 42-m elevation drop could result in a time well below the 2-hour marathon barrier.
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The mechanical stiffness of running-specific prostheses likely affects the functional abilities of athletes with leg amputations. However, each prosthetic manufacturer recommends prostheses based on subjective stiffness categories rather than performance based metrics. The actual mechanical stiffness values of running-specific prostheses (i.e. kN/m) are unknown. Consequently, we sought to characterize and disseminate the stiffness values of running-specific prostheses so that researchers, clinicians, and athletes can objectively evaluate prosthetic function. We characterized the stiffness values of 55 running-specific prostheses across various models, stiffness categories, and heights using forces and angles representative of those measured from athletes with transtibial amputations during running. Characterizing prosthetic force-displacement profiles with a 2nd degree polynomial explained 4.4% more of the variance than a linear function (p<0.001). The prosthetic stiffness values of manufacturer recommended stiffness categories varied between prosthetic models (p<0.001). Also, prosthetic stiffness was 10% to 39% less at angles typical of running 3 m/s and 6 m/s (10°-25°) compared to neutral (0°) (p<0.001). Furthermore, prosthetic stiffness was inversely related to height in J-shaped (p<0.001), but not C-shaped, prostheses. Running-specific prostheses should be tested under the demands of the respective activity in order to derive relevant characterizations of stiffness and function. In all, our results indicate that when athletes with leg amputations alter prosthetic model, height, and/or sagittal plane alignment, their prosthetic stiffness profiles also change; therefore variations in comfort, performance, etc. may be indirectly due to altered stiffness.
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Purpose: Our goal was to quantify if small (1 - 3%) changes in running economy quantitatively affect distance-running performance. Based on the linear relationship between metabolic rate and running velocity and on earlier observations that added shoe mass increases metabolic rate by ~1% per 100 grams per shoe, we hypothesized that adding 100 and 300 grams per shoe would slow 3,000m time-trial performance by 1% and 3%, respectively. Methods: 18 male, sub-20 minute 5km runners completed treadmill testing, and three 3,000m time-trials wearing control shoes and identical shoes with 100 and 300 grams of discreetly added mass. We measured rates of oxygen consumption and carbon dioxide production and calculated metabolic rates for the treadmill tests and we recorded overall running time for the time-trials. Results: Adding mass to the shoes significantly increased metabolicrate at 3.5 m·s by 1.11% per 100grams per shoe (95% CI: 0.88-1.35%). While wearing the control shoes, participants ran the 3,000m time-trial in 626.1 ± 55.6s. Times averaged 0.65 ± 1.36% and 2.37 ± 2.09% slower for the +100g and +300g shoes respectively (p<0.001). Based on a linear fit of all the data, 3,000m time increased 0.78% per added 100 grams per shoe (95% CI: 0.52-1.04%). Conclusion: Adding shoe mass predictably degrades running economy and slows 3,000m time-trial performance proportionally. Our data demonstrate that laboratory-based running economy measurements can accurately predict changes in distance running race performance due to shoe modifications.
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Metabolic measurement is still the criterion for investigation of the efficiency of mechanical work and for analysis of endurance performance in running. Metabolic demand may be expressed either as the energy spent per unit distance (energy cost of running, C r) or as energy demand at a given running speed (running economy). Systematic studies showed a range of costs of about 20 % between runners. Factors affecting C r include body dimensions: body mass and leg architecture, mostly calcaneal tuberosity length, responsible for 60–80 % of the variability. Children show a higher C r than adults. Higher resting metabolism and lower leg length/stature ratio are the main putative factors responsible for the difference. Elastic energy storage and reuse also contribute to the variability of C r. The increase in C r with increasing running speed due to increase in mechanical work is blunted till 6–7 m s−1 by the increase in vertical stiffness and the decrease in ground contact time. Fatigue induced by prolonged or intense running is associated with up to 10 % increased C r; the contribution of metabolic and biomechanical factors remains unclear. Women show a C r similar to men of similar body mass, despite differences in gait pattern. The superiority of black African runners is presumably related to their leg architecture and better elastic energy storage and reuse.
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Background: The effect of footwear on running economy has been investigated in numerous studies. However, no systematic review and meta-analysis has synthesised the available literature and the effect of footwear on running performance is not known. Objective: The aim of this systematic review and meta-analysis was to investigate the effect of footwear on running performance and running economy in distance runners, by reviewing controlled trials that compare different footwear conditions or compare footwear with barefoot. Methods: The Web of Science, Scopus, MEDLINE, CENTRAL (Cochrane Central Register of Controlled Trials), EMBASE, AMED (Allied and Complementary Medicine), CINAHL and SPORTDiscus databases were searched from inception up until April 2014. Included articles reported on controlled trials that examined the effects of footwear or footwear characteristics (including shoe mass, cushioning, motion control, longitudinal bending stiffness, midsole viscoelasticity, drop height and comfort) on running performance or running economy and were published in a peer-reviewed journal. Results: Of the 1,044 records retrieved, 19 studies were included in the systematic review and 14 studies were included in the meta-analysis. No studies were identified that reported effects on running performance. Individual studies reported significant, but trivial, beneficial effects on running economy for comfortable and stiff-soled shoes [standardised mean difference (SMD) <0.12; P < 0.05), a significant small beneficial effect on running economy for cushioned shoes (SMD = 0.37; P < 0.05) and a significant moderate beneficial effect on running economy for training in minimalist shoes (SMD = 0.79; P < 0.05). Meta-analysis found significant small beneficial effects on running economy for light shoes and barefoot compared with heavy shoes (SMD < 0.34; P < 0.01) and for minimalist shoes compared with conventional shoes (SMD = 0.29; P < 0.01). A significant positive association between shoe mass and metabolic cost of running was identified (P < 0.01). Footwear with a combined shoe mass less than 440 g per pair had no detrimental effect on running economy. Conclusions: Certain models of footwear and footwear characteristics can improve running economy. Future research in footwear performance should include measures of running performance.
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A mathematical model for terrestrial running is presented, based on a leg with the properties of a simple spring. Experimental force-platform evidence is reviewed justifying the formulation of the model. The governing differential equations are given in dimensionless form to make the results representative of animals of all body sizes. The dimensionless input parameters are: U, a horizontal Froude number based on forward speed and leg length; V, a vertical Froude number based on vertical landing velocity and leg length, and KLEG, a dimensionless stiffness for the leg-spring. Results show that at high forward speed, KLEG is a nearly linear function of both U and V, while the effective vertical stiffness is a quadratic function of U. For each U, V pair, the simulation shows that the vertical force at mid-step may be minimized by the choice of a particular step length. A particularly useful specification of the theory occurs when both KLEG and V are assumed fixed. When KLEG = 15 and V = 0.18, the model makes predictions of relative stride length S and initial leg angle θ0 that are in good agreement with experimental data obtained from the literature.
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A local minimum for running energetics has been reported for a specific bending stiffness, implying that shoe stiffness assists in running propulsion. However, the determinant of the metabolic optimum remains unknown. Highly stiff shoes significantly increase the moment arm of the ground reaction force (GRF) and reduce the leverage effect of joint torque at ground push-off. Inspired by previous findings, we hypothesized that the restriction of the natural metatarsophalangeal (MTP) flexion caused by stiffened shoes and the corresponding joint torque changes may reduce the benefit of shoe bending stiffness to running energetics. We proposed the critical stiffness, kcr, which is defined as the ratio of the MTP joint (MTPJ) torque to the maximal MTPJ flexion angle, as a possible threshold of the elastic benefit of shoe stiffness. 19 subjects participated in a running test while wearing insoles with five different bending stiffness levels. Joint angles, GRFs, and metabolic costs were measured and analyzed as functions of the shoe stiffness. No significant changes were found in the take-off velocity of the center of mass (CoM), but the horizontal ground push-offs were significantly reduced at different shoe stiffness levels, indicating that complementary changes in the lower-limb joint torques were introduced to maintain steady running. Slight increases in the ankle, knee, and hip joint angular impulses were observed at stiffness levels exceeding the critical stiffness, whereas the angular impulse at the MTPJ was significantly reduced. These results indicate that the shoe bending stiffness is beneficial to running energetics if it does not disturb the natural MTPJ flexion.
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Exercise testing on motorised treadmills provides valuable information about running performance and metabolism; however, the impact of treadmill type on these tests has not been investigated. This study compared the energy demand of running on two laboratory treadmills: an HP Cosmos (C) and a Quinton (Q) model, with the latter having a 4.5 times stiffer running platform. Twelve experienced runners ran identical bouts on these treadmills at a range of four submaximal velocities (reported data is for the velocity that approximated 75-81% VO2max). The stiffer treadmill elicited higher oxygen consumption (C: 46.7 ± 3.8; Q: 50.1 ± 4.3 ml·kg(-1) · min(-1)), energy expenditure (C: 16.0 ± 2.5; Q: 17.7 ± 2.9 kcal · min(-1)), carbohydrate oxidation (C: 9.6 ± 3.1; Q: 13.0 ± 3.9 kcal · min(-1)), heart rate (C: 155 ± 16; Q: 163 ± 16 beats · min(-1)) and rating of perceived exertion (C: 13.8 ± 1.2; Q: 14.7 ± 1.2), but lower fat oxidation (C: 6.4 ± 2.3; Q: 4.6 ± 2.5 kcal · min(-1)) (all analysis of variance treadmill comparisons P < 0.01). This study confirms that caution is required when comparing performance and metabolic results between different treadmills and suggests that treadmills will vary in their comparability to over-ground running depending on the running platform stiffness.
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Adopting an integrated achievement goal (Nicholls, J. G. (1989). The competitive ethos and democratic education. Cambridge, MA: Harvard University Press.) and self-determination theory (Deci, E. L., & Ryan, R. M. (2000). The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, 227-268. doi:10.1207/S15327965PLI1104_01) perspective as proffered by Duda, J. L. (2013). (The conceptual and empirical foundations of empowering coaching(TM): Setting the stage for the PAPA project. International Journal of Sport and Exercise Psychology, 11, 311-318. doi:10.1080/1612197X.2013.839414), the aim of the current study was to observe empowering and disempowering features of the multidimensional motivational coaching environment in training and competition in youth sport. Seventeen grass-roots soccer coaches were observed and rated in training and competitive settings using the multidimensional motivational climate observation system (MMCOS; Smith, N., Tessier, D., Tzioumakis, Y., Quested, E., Appleton, P., Sarrazin, P., … Duda, J. L. (2015). Development and validation of the multidimensional motivational climate observation system (MMCOS). Journal of Sport and Exercise Psychology, 37, 4-22. doi:10.1123/jsep.2014-0059). In line with our hypotheses, coaches created different motivational environments in the two contexts. More specifically, coaches were observed to create a less empowering and more disempowering environment in competition compared to in training. The observed differences were underpinned by distinctive motivational strategies used by coaches in the two contexts. Findings have implications for the assessment of the coach-created motivational environment and the promotion of quality motivation for young athletes taking part in grass-roots-level sport.