Content uploaded by Juan Garcia-Lopez
Author content
All content in this area was uploaded by Juan Garcia-Lopez on Jul 26, 2017
Content may be subject to copyright.
Content uploaded by Juan Garcia-Lopez
Author content
All content in this area was uploaded by Juan Garcia-Lopez on May 11, 2017
Content may be subject to copyright.
DIFFERENCES IN SPATIOTEMPORAL PARAMETERS
BETWEEN TRAINED RUNNERS AND UNTRAINED
PARTICIPANTS
JOSUE
´GO
´MEZ-MOLINA,
1
ANA OGUETA-ALDAY,
1
CHRISTOPHER STICKLEY,
2
JESU
´SCA
´MARA,
1
JON CABREJAS-UGARTONDO,
3
AND JUAN GARCI
´A-LO
´PEZ
4
1
Faculty of Education and Sport, University of the Basque Country, UPV/EHU, Vitoria-Gasteiz, Spain;
2
Department of
Kinesiology and Rehabilitation Science, College of Education, University of Hawaii at Manoa, Honolulu, Hawaii;
3
Departament of Internal Medicine, Regional Hospital Santiago Apostol, SACYL, Miranda de Ebro, Spain; and
4
Department
of Physical Education and Sports, Institute of Biomedicine (IBIOMED), University of Leo
´n, Leo
´n, Spain
ABSTRACT
Go
´mez-Molina, J, Ogueta-Alday, A, Stickley, C, Tobalina, JC,
Cabrejas-Ugartondo, J, and Garcı
´a-Lo
´pez, J. Differences in spa-
tiotemporal parameters between trained runners and untrained
participants. J Strength Cond Res 31(8): 2169–2175, 2017—
The aim of this study was to compare the spatiotemporal param-
eters of trained runners and untrained participants with the same
foot strike pattern (rearfoot) during running at controlled speeds.
Twenty-one participants were classified in 2 groups according to
their training experience: Trained (n= 10, amateur runners with
long distance training experience) and Untrained (n= 11, healthy
untrained participants). Anthropometric variables were recorded,
and the participants performed both a submaximal (between 9
and 15 km$h
21
) and a graded exercise running test (from 6
km$h
21
until exhaustion) on a treadmill. Physiological (V
_
O
2
max,
heart rate, running economy [RE], peak speed .)andbiome-
chanical variables (contact and flight times, step rate, and length)
were simultaneously registered. Trained runners showed higher
step rate and shorter step length than the Untrained group at the
same running speeds (between 4 and 7%, p#0.05) and at the
same physiological intensities (between 7 and 11%, p#0.05).
However, there were no differences in contact and flight times
between groups. Significant differences (p#0.05) and large
effect sizes (Cohen’s d) between groups were found for body
mass, sum of 6 skinfolds, V
_
O
2
max, peak speed, and ventilatory
threshold and respiratory compensation threshold speeds. The
Trained group also showed a ;7% better RE (ml$kg
20.75
$km
21
)
than the Untrained group. In conclusion, adopting higher step
rate and shorter step length may be an adaptive mechanism of
the Trained group to reduce injury risk and possibly improve RE.
However, contact and flight times were consistent regardless of
training level.
KEY WORDS endurance running, biomechanics, physiology,
injury risk, energy cost
INTRODUCTION
Long-distance running has increased in popularity in
the last decade. According to the Running USA
annual half-marathon report (32), since 2000, the
number of finishers in half-marathon races
increased from 482,000 to 2,046,600 in 2014. This has led
to great interest within the scientific community in studying
different factors affecting both performance and injury risk in
long-distance runners. The runners’ physiological character-
istics (i.e., V
_
O
2
max, anaerobic threshold, and running econ-
omy [RE]) and their influence on performance have been
widely studied (2,11). Additionally, some biomechanical var-
iables such as leg stiffness and foot strike pattern have been
shown to influence performance (26,33). However, the rela-
tionship between the spatiotemporal parameters of running
(i.e., step rate and length, contact and flight times) and both
performance and injury risk still remains unclear.
Previous studies have compared step rate and length in
varying levels of trained runners (6,31,35). There are indica-
tions that experienced runners self-select higher step rates
than novice ones (6,10), which could be an adaptation to
optimize energy expenditure (18). De Ruiter et al. (10)
observed that untrained individuals self-select a step rate
;10% lower than that which would produce an optimal
RE. Conversely, other authors have found that amateur mar-
athon runners had a higher step rate and shorter step length
than elite marathon runners at various standardized speeds
(31). Only 2 studies analyzed the differences between trained
runners and untrained individuals (10,35), and their results
were also contradictory. Moreover, several studies attempt-
ing to modify runners’ preferred step rate and length showed
decrements in RE (6,25,33). Some other studies tried to
Address correspondence to Josue
´Gomez-Molina, josue.gomez@ehu.es.
31(8)/2169–2175
Journal of Strength and Conditioning Research
Ó2016 National Strength and Conditioning Association
VOLUME 31 | NUMBER 8 | AUGUST 2017 | 2169
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
identify an optimal relationship between these variables and
RE, without satisfactory results (19,36,39).
The examination of the relationship between contact and
flight times with RE yields similarlyconflictingresults.Some
studies argue that for a given running speed, increased contact
time is related to a better RE and performancebecauseahigher
contact time implies a lower ground reaction force, which
explains between 70 and 90% of energy cost of running (13,15).
Conversely, others associated a lower contact time with a better
performance (15,30), possibly because running speeds and foot
strike patterns were not always well-controlled. To address this
issue, it has been suggested that foot strike pattern and running
speed should be standardized when comparing RE and spa-
tiotemporal parameters of running between different level of
runners or untrained individuals (29).
Modifications in step rate and length have also been
associated with increased injury risk while running (34) prob-
ably because of association with the magnitude and rate of
impact force loading during the stance phase in some running
injuries (23). Research suggests that increased step rate, and
subsequent reduction in step length, decreases the magnitude
of several key biomechanical factors associated with running
injuries (34), such as the center of mass vertical excursion,
ground reaction force, and impact shock, and may ameliorate
energy absorption at the hip, knee, and ankle joints (34). Thus,
increasing step rate during running has been commonly advo-
cated as an injury prevention mechanism (34). Previous stud-
ies (7,16,34) have shown that the minimum change in step
length required to observe biomechanical changes was 5%,
although an increase of around 10% was required in step rate
to elicit biomechanical differences (7,16,23,34). Curiously, De
Ruiter et al. (10) reported that trained runners had a step rate
;9% higher than untrained participants.
Taking into account the influence of spatiotemporal
parameters of running on performance and injury risk, and
the conflicting research relative to differences between
trained runners and untrained individuals, the aim of this
study was to compare the spatiotemporal parameters (i.e.,
contact and flight times, step rate and length) of trained long
distance runners and untrained participants with the same
foot strike pattern (rearfoot) during running at controlled
speeds. Additionally, RE was examined and compared
between groups. It was hypothesized that step rate would
be higher and step length shorter in trained runners
compared with untrained participants, regardless of running
speed. Conversely, no differences in either contact or flight
times at the same absolute velocities were expected between
groups based on the standardized rearfoot strike pattern
among participants.
METHODS
Experimental Approach to the Problem
Spatiotemporal parameters of running (i.e., step rate and
length, contact and flight times) and physiological variables
(V
_
O
2
max, ventilatory threshold [VT], respiratory compensa-
tion threshold [RCT], and RE) among trained runners and
untrained participants with the same foot strike pattern (i.e.,
rearfoot strikers) were compared in the present study. Sub-
maximal running test and graded exercise were performed,
allowing comparison of biomechanical and physiologic pa-
rameters between groups at standard speeds and at the same
physiological intensities.
Subjects
Twenty-one participants took part in the present study.
They were divided into 2 groups according to their training
experience: Untrained group were 11 healthy untrained
participants (age: 25.6 64.8 years; height: 176.7 65.3 cm;
S6 skinfolds: 61.5 625.4 mm; body mass: 73.2 66.3 kg;
body mass index: 23.4 62.1 kg$m
22
) who performed 2–3
days per week of moderate physical activity but not specific
running training. The trained groups consisted of 10 amateur
runners with at least 2 years of training experience in long
distance running, a training frequency of at least 3 days per
week and a personal best time on a half marathon between
1:10:00 and 1:26:00 hh:mm:ss (age: 26.6 66.6 years; height:
174.7 64.9 cm; S6 skinfolds: 41.0 69.3 mm; body mass:
65.9 64.2 kg; body mass index: 21.6 61.0 kg$m
22
; weekly
training volume: 57.5 622.6 km). None of them were
involved in strength training programs at the time of partic-
ipation in the study. The protocol was approved by the
University Ethics Committee, in accordance with the Dec-
laration of Helsinki for human research. All participants
signed a written informed consent to participate in the study
and were informed of the objectives, procedures, benefits,
and possible risks involved in the study.
The foot strike pattern was considered as an inclusion
criteria for both groups because it has been shown that this
variable affects contact and flight times (29). All the partic-
ipants were rearfoot strikers, which is the most common foot
strike pattern in long distance runners (15).
Procedures
All the participants were evaluated during the same period of
the year (May to June) in a single data collection session.
First, their anthropometric characteristics and the weight of
their shoes were collected. After this, they performed
10 minutes of running warm-up on a treadmill at ;10
km$h
21
, followed by 5 minutes of free stretching of the
lower limbs. Second, a submaximal running test followed
by a graded exercise test were performed with 25-minute
rest in-between. All testing sessions were conducted at the
same time of day (between 10 AM and 1 PM), under similar
environmental conditions (;600 m altitude, 20–248C and
45–55% relative humidity). All subjects were instructed on
proper hydration and carbohydrate intake before testing
(21), and they were instructed to not perform hard training
in the 48 hours before testing.
All runners wore the same running shoes (250–300 g
weight for each shoe) in both submaximal and graded tests
to prevent this variable from affecting RE (28,29). Runners’
Differences Between Trained Runners Vs. Untrained
2170
Journal of Strength and Conditioning Research
the
TM
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
body mass and height were recorded, together with 6 skin-
fold measurements (triceps, subscapular, suprailiac, abdomi-
nal, front thigh, and medial calf ) using standard equipment
(Harpender; CMS Instruments, London, United Kingdom).
All measurements were made by the same researcher fol-
lowing the guidelines of the International Society for the
Advancement of Kineanthropometry (27).
Running tests were performed on a calibrated treadmill
(ERGelek EG2, Vitoria-Gasteiz, Spain) with a 1% of slope to
mimic the effects of air resistance on the metabolic cost on
a flat outdoor running track (21). In both running tests,
respiratory gases were collected via open-circuit indirect cal-
orimetry (Medisoft Ergocard; Medisoft Group, Sorinnes,
Belgium) and heart rate (HR) was monitored (Polar
RS800; Polar Electro Oy, Kempele, Finland). Equally, a con-
tact laser platform, previously validated and used in other
studies (28,29), was installed in the treadmill to obtain the
spatiotemporal parameters of running (SportJUMP System
PRO; DSD Inc., Leo
´n, Spain), allowing the analysis of con-
tact and flight times, step rate, and length during running.
Spatiotemporal parameters were registered during the last 30
seconds of each stage to obtain at least 32–64 consecutive
steps and thus reduce the effect of intraindividual step vari-
ability (3). To determine the runners’ foot strike pattern,
a high-speed video camera recording at 600 Hz (Casio
Exilim Pro EX-F1; Casio Europe GMBH, Norderstedt, Ger-
many) was placed on the right side of the treadmill (;1 m),
perpendicular to the sagittal plane (28,29). All runners were
analyzed by the same researcher, who identified their foot
strike pattern at speeds corresponding to the runners’ race
pace for the Trained group (15–18 km$h
21
) and for the
Untrained group (12–14 km$h
21
). Only the runners who
landed on the ground with the heel first (i.e., rearfoot strik-
ers) were included for further analysis.
The submaximal test consisted of 3 running sets of
5 minutes with 5-minute rest in-between. Untrained Group
ran at 9, 11, and 13 km$h
21
and Trained Group ran at 11, 13,
and 15 km$h
21
.V
_
O
2
and HR registry of the last 3 minutes of
each set were considered as representative values and used for
analysis (29). Running economy was determined as the V
_
O
2
cost at a given running speed expressed in ml$kg
21
$min
21
and ml$kg
20.75
$min
21
(4). As previously reported by Helger-
ud et al. (17), there is no difference between RE at velocities
representing intensities between 60 and 90% of V
_
O
2
max;
therefore, the better RE value between these intensities was
chosen as representative value.
The graded exercise test started at 6 km$h
21
and increased 1
km$h
21
every 1 minute until volitional exhaustion. Achieve-
ment of V
_
O
2
max was determined based on the attainment of
at least 2 of the following 3 criteria: a plateau in V
_
O
2
with
increasing speeds; a respiratory exchange ratio above 1.15; par-
ticipants reaching their age-predicted maximal HR (220 2age)
(12). The VT and the RCT were identified according to the
criteria of Davis (9). The V
_
O
2
max/RE ratio was calculated as
the quotient between V
_
O
2
max and RE, both expressed in
ml$kg
21
$min
21
(19,36,39). Biomechanical parameters were
TABLE 1. Anthropometric and physiological characteristics (mean 6SD) of trained and untrained participants.
Variables Trained (n= 10) Untrained (n= 11) pES
Anthropometric
Mass (kg) 65.9 64.2†73.2 66.3 0.006 1.37
Height (cm) 174.7 64.9 176.7 65.3 0.940 —
BMI (kg$m
22
) 21.6 61.0* 23.4 62.1 0.012 1.12
S6 skinfolds (mm) 41.0 69.3* 61.5 625.4 0.028 1.07
Graded test
V
_
O
2
max (ml$kg
21
$min
21
) 61.8 65.4†54.1 65.8 0.006 1.38
HR
max
(b$min
21
) 184.4 69.0 190.0 69.5 0.274 —
Peak speed (km$h
21
) 20.0 61.0z16.5 61.2 0.000 3.14
VT speed (km$h
21
) 12.2 61.1z9.4 60.9 0.000 2.79
RCT speed (km$h
21
) 16.1 61.1z13.2 60.7 0.000 3.16
Submaximal test
RE (ml$kg
21
$km
21
) 207.6 617.4 217.6 613.9 0.120 -
RE (ml$kg
20.75
$km
21
) 591.1 648.0* 635.5 636.0 0.031 1.05
V
_
O
2
max/RE (min$m
21
) 298.2 615.1z248.4 620.2 0.000 2.79
ES = effect size; BMI = body mass index; S6 skinfolds = triceps, subscapular, abdominal, suprailiac, mid-thigh, and medial calf;
V
_
O
2
max = maximum oxygen uptake rate; HR
max
= maximum heart rate; peak speed = maximal speed reached during the test; VT
speed = speed at ventilatory threshold; RCT speed = speed at respiratory compensation threshold; RE = running economy.
*Significant differences between both groups: p#0.05.
†Significant differences between both groups: p,0.01.
zSignificant differences between both groups: p,0.001.
Journal of Strength and Conditioning Research
the
TM
|
www.nsca.com
VOLUME 31 | NUMBER 8 | AUGUST 2017 | 2171
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
recorded during each stage above 10 km$h
21
to ensure that all
subjects were running (identified by the presence of flight time)
(28,29).
Statistical Analyses
All values are expressed as mean 6SD, and in some vari-
ables, 95% confidence intervals (95% CIs) were also calcu-
lated. The Kolmogorov-Smirnov test was applied to ensure
a normal distribution of all results. A 1-way analysis of
variance was used to analyze the differences between both
groups. The magnitude of differences or effect sizes (ES)
were calculated according to Cohen’s d(8) and interpreted
as small (0.2 #ES ,0.5), moderate (0.5 #ES ,0.8), and
large (ES $0.8). Intraclass correlation coefficient (ICC)
was used to assess the validity of spatiotemporal parame-
ters between both running tests (submaximal test and
graded exercise test) at 11 and 13 km$h
21
.TheICCwas
greater than or equal to 0.90 for all parameters (contact and
flight time, step rate, and length) at both speeds. SPSS
version 23.0 statistical software (SPSS, Inc., Chicago, IL,
USA) was used. Values of p#0.05 were considered statis-
tically significant.
RESULTS
Table 1 shows the participants’ anthropometric characteristics
and their physiological variables during the graded and sub-
maximal tests. Significant differences (p#0.05) and large ES
between groups were found for body mass, body mass index,
sum of 6 skinfolds, V
_
O
2
max, peak speed, VT speed, RCT
speed, RE expressed in ml$kg
20.75
$km
21
, and the quotient
V
_
O
2
max/RE. No significant differences were found in HR
max
,
height, and RE expressed in ml$kg
21
$km
21
.
Table 2 shows the step rate and length of both groups
during the graded exercise test. Overall (i.e., considering all
the speeds), the Trained group showed 5.2 60.9% higher step
rate than Untrained group (2.94 60.1 and 2.81 60.2 Hz,
respectively; p#0.05 and ES = 0.97) and 5.6 61.2% shorter
step length (1.36 60.05 and 1.46 60.09 m, respectively; p#
0.05 and ES = 1.37) than the Untrained group. Moderate to
large ES were observed for speeds from 10 to 17 km$h
21
.
Figure 1 shows no significant differences between groups in
contact and flight times during the graded exercise test.
Figure 2 shows significant differences (p,0.01) in step
rate between both groups at similar physiological intensities.
Figure 1. Contact (top marks) and flight times (bottom marks) of trained
and untrained participants during the graded exercise test (from 10 to 17
km$h
21
).
TABLE 2. Step rate and length (mean 6SD) of trained (n= 10) and untrained participants (n= 11) during the graded
exercise test (from 10 to 17 km$h
21
).
Speed (km$h
21
)
Step rate (Hz) Step length (m)
Trained Untrained pES Trained Untrained pES
10 2.79 60.13* 2.67 60.14 0.048 0.88 0.99 60.05* 1.04 60.05 0.049 1.00
11 2.82 60.11 2.71 60.13 0.057 0.91 1.08 60.04 1.11 60.05 0.055 0.66
12 2.86 60.11* 2.73 60.14 0.036 1.03 1.16 60.05* 1.22 60.06 0.037 1.08
13 2.91 60.10* 2.76 60.15 0.021 1.17 1.24 60.04* 1.31 60.07 0.021 1.22
14 2.95 60.09* 2.79 60.14 0.011 1.35 1.32 60.04* 1.40 60.07 0.012 1.40
15 2.99 60.08†2.82 60.15 0.008 1.41 1.39 60.04†1.47 60.08 0.009 1.26
16 3.05 60.09†2.85 60.15z0.005 1.61 1.45 60.04†1.56 60.09z0.006 1.57
17 3.10 60.11†2.98 60.17§ 0.001 0.83 1.52 60.05†1.58 60.09§ 0.001 0.82
ES = effect size.
*Significant differences between both groups: p#0.05.
†Significant differences between both groups: p,0.01.
zNumber of untrained runners in this stages: n=9.
§Number of untrained runners in this stages: n=7.
Differences Between Trained Runners Vs. Untrained
2172
Journal of Strength and Conditioning Research
the
TM
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
The Trained group used higher step rate at VT and RCT
(2.82 60.13 Hz, 95% CI: 2.74–2.90 Hz; and 3.01 60.12 Hz,
95% CI: 2.94–3.07 Hz, respectively) than Untrained group
(2.62 60.12 Hz, 95% CI: 2.55–2.70 Hz; and 2.75 60.14 Hz,
95% CI: 2.66–2.85 Hz, respectively).
DISCUSSION
The main outcome of the present study was that trained
runners demonstrated a higher step rate and shorter step
length (between 4 and 7%) than untrained participants at all
running speeds above 10 km$h
21
(Table 2). These differences
were more pronounced (between 7 and 11%) at the same
physiological intensities (Figure 2). This could be an adapta-
tion to reduce loading at the hip and knee joints during run-
ning, which may be an adaptive mechanism to prevent some
of the most common running-related injuries (16). Addition-
ally, the present study demonstrated that when both foot
strike pattern and velocity were controlled, contact and flight
times were independent of running experience (Figure 1).
Only 2 previous studies analyzed the differences in step rate
among trained and untrained participants (10). Slawinski and
Billat (35) observed that highly trained runners used a step
rate ;7–8% greater than well trained and untrained runners at
the same running speed, but that there were no differences
between the latter 2 groups. Their findings conflict with the
results of the present study (Table 2), possibly because their
experiment was performed in the field (i.e., real conditions),
and the ability to control speed (i.e., it was between ;5and
7% different among groups) and record a representative
number of steps (i.e., only 2 steps were analyzed) was limited.
Conversely, de Ruiter et al. (10) have reported that trained
runners had a step rate ;9% higher than untrained partic-
ipants at the same physiological intensity (80% of RCT).
These differences are similar to those reported in the present
study (between 7 and 11%) at different physiological
intensities (Figure 2), demonstrating a clear preference in
experienced runners to self-select higher step rates than
untrained ones.
The higher step rate and shorter step length found in the
experienced runners when compared with untrained par-
ticipants could be associated with, among other factors, an
adaptive mechanism to reduce injury risk by increasing step
rate (35). Previous studies (16,20) have observed that at
a given running speed, a shorter step length decreases the
impact of the foot on the ground, thereby reducing injury
risk (23,34). Considering the running-related injury rate
among those who begin a running program (ranging from
19.4 to 79.3%) (37), the findings of the present study, when
viewed in context with previous research examining injury
risk, indicate that some technical strategies could be adop-
ted (i.e., cadence training with feedback) in an attempt to
decrease injury risk and positively affect RE (14).
Both Trained and Untrained groups in the present study
exhibited a rearfoot strike pattern and demonstrated no
differences in the contact or flight times (Figure 2). These
results disagree with previous research suggesting an associ-
ation between shorter contact times and better performance
(15,30) or level of expertise (10). However, not all previous
research has controlled for factors that may effect this asso-
ciation. Because of the effect of foot strike pattern and run-
ning speed on contact and flight times, both variables were
controlled in the present study, as in some previous studies
(28,29). Additionally, at running speeds of 12, 14, and 16
km$h
21
, contact times (0.276 60.017, 0.249 60.014, and
0.228 60.013 seconds, respectively) were similar to those
reported (0.278 60.017, 0.252 60.014, and 0.230 60.011
seconds, respectively) in a previous study, which involved
highly trained runners with a rearfoot strike pattern (half
marathon time lower than 1:15:00 hh:mm:ss) (29). These
results suggest that for the same submaximal running speed,
contact and flight times do not seem to vary with the level of
training or running experience. In other words, at submaxi-
mal speeds, timing is very consistent in humans while run-
ning. This new finding warrants further investigation (i.e.,
neural mechanisms associated with this phenomenon).
In the present study, there were no significant differences in
RE between trained runners and untrained participants if this
variable was expressed in ml$kg
21
$km
21
, and the contrary
when it was expressed in ml$kg
20.75
$km
21
(Table 1). Because
V
_
O
2
at a submaximal speed does not increase linearly in pro-
portion to body mass, if the V
_
O
2
isexpressedinml$kg
21
$km
21
,
lighter runners may be classified as less efficient than heavier
runners (4). Given the differences in mass between the 2
groups, and following the recommendations of Bergh et al.
(4),itcouldbeassumedthatREexpressedinml$kg
20.75
$km
21
more accurately reflects the differences between groups. Several
studies associated RE with running performance (1,5,26,33),
although in homogeneous groups of runners, the ES of this
Figure 2. Step rate at ventilatory threshold (VT), respiratory
compensation threshold (RCT), and peak speed for both groups (Trained
vs. Untrained). Significant differences between both groups: **p,0.01;
***p,0.001.
Journal of Strength and Conditioning Research
the
TM
|
www.nsca.com
VOLUME 31 | NUMBER 8 | AUGUST 2017 | 2173
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
association has been questioned (24). The present study found
that trained runners were between 5 and 7% more economical
than the untrained ones. These values are in line with the
reduction in aerobic demand (6–7%) observed between trained
and untrained adults undergoing extended training programs
(38,39). Specifically, Morgan et al. (26) noted that subelite run-
ners were 3% more economical than moderately trained run-
ners, and these were 9% more economical than untrained.
However, economical and uneconomical runners could be
identified at all levels of performance (22,26) and possibly
between trained and untrained subjects.
Some limitations of the present study were as follows: (a)
the analysis of treadmill running instead of track running.
Although it can be assumed that kinematics and kinetics are
very similar, instruments’ accuracy and environmental condi-
tions are better controlled in the laboratory (28); (b) the dif-
ferentiation between the effect of both running experience and
step rate on RE. Because of the collinearity of these variables,
it is difficult to know the real effect of running experience on
the other 2 variables. However, according to previous studies,
RE in untrained participants who increased step rate ;9%
only improved 1–2% (9).
In conclusion, this study examined differences in spatio-
temporal parameters between trained long distance runners
and untrained participants, which can be applied to benefit
novice runners. Besides possessing a decreased physiological
capacity (e.g., lower V
_
O
2
max and RE, higher percent body
fat), untrained runners also demonstrated lower step rate and
longer step length compared with trained runners at the
same running speeds (between 4 and 7%) and at the same
physiological intensities (between 7 and 11%). These differ-
ences may represent an adaptive mechanism to reduce the
injury risk while running that may be trained in novice run-
ners to improve function and reduce injury risk. However,
there were no differences in contact and flight times at the
same submaximal speeds, showing a consistent timing for
runners with the same foot strike pattern, independent of
the level of training. The underlying mechanisms for this
similarity between runners of different training levels warrant
further investigation.
PRACTICAL APPLICATIONS
Because high step rate has been related to a decrease in
running injuries, specific intervention, strategies, and
technical exercises used by coaches to increase step rate
of their runners may be advantageous. This is particularly
important for novice runners given their tendency to use
lower step rates at all speeds, but can also be applied for
experienced runners, when this pattern is detected.
According to the results of this study, step rate values in
experienced runners should be near 2.82 60.13 Hz at VT
(95% CI: 2.74–2.90 Hz) and 3.01 60.12 Hz at RCT (95%
CI: 2.94–3.07 Hz). In this regard, step rate and length
could be easily registered by means of portable
and miniaturized sensors (e.g., Polar Sensor Running,
Garmin HRM-Run, Suunto Foot POD) and compared
with these reference values, which may help coaches
and athletes monitor these parameters and determine
their adequacy during training and competitions.
ACKNOWLEDGMENTS
The authors thank the runners who participated in this study
for their collaboration. This work was supported by the
Basque Country Government under a predoctoral grant
number reference PRE_2013_1_1109. The authors have no
conflicts of interest to disclose, and the mention of the
SportJump System Pro in this manuscript does not constitute
endorsement by the National Strength and Conditioning
Association.
REFERENCES
1. Anderson, T. Biomechanics and running economy. Sports Med 22:
76–89, 1996.
2. Barnes, KR and Kilding, AE. Strategies to improve running
economy. Sports Med 45: 37–56, 2015.
3. Belli, A, Lacour, J R, Komi, PV, Candau, R, and Denis, C. Mechanical
step variability during treadmill running. Eur J Appl Physiol Occup
Physiol 70: 510–517, 1995.
4. Bergh, U, Sjodin, B, Forsberg, A, and Svedenhag, J. The relationship
between body-mass and oxygen-uptake during running in humans.
Med Sci Sports Exerc 23: 205–211, 1991.
5. Bransford, DR and Howley, ET. Oxygen cost of running in trained
and untrained men and women. Med Sci Sports Exerc 9: 41–44, 1977.
6. Cavanagh, PR and Williams, KR. The effect of stride length
variation on oxygen-uptake during distance running. Med Sci Sports
Exerc 14: 30–35, 1982.
7. Clarke, TE, Cooper, LB, Hamill, CL, and Clark, DE. The effect of
varied stride rate upon shank deceleration in running. J Sports Sci 3:
41–49, 1985.
8. Cohen, J. Statistical Power Analysis for the Behavioral Sciences. New
York, NY: Hillsdale, 1988.
9. Davis, JA. Anaerobic threshold—Review of the concept and
directions for future-research. Med Sci Sports Exerc 17: 6–18,
1985.
10. de Ruiter, CJ, Verdijk, PW, Werker, W, Zuidema, MJ, and de Haan, A.
Stride frequency in relation to oxygen consumption in experienced
and novice runners. Eur J Sport Sci 14: 251–258, 2014.
11. Dellagrana, RA, Guglielmo, LGA, Santos, BV, Hernandez, SG,
da Silva, SG, and de Campos, W. Physiological, anthropometric,
strength, and muscle power characteristics correlates with
running performance in young runners. J Strength Cond Res 29:
1584–1591, 2015.
12. Duncan, GE, Howley, ET, and Johnson, BN. Applicability of
VO2max criteria: Discontinuous versus continuous protocols. Med
Sci Sports Exerc 29: 273–278, 1997.
13. Gruber, AH, Umberger, BR, Braun, B, and Hamill, J. Economy and
rate of carbohydrate oxidation during running with rearfoot and
forefoot strike patterns. J Appl Physiol 115: 194–201, 2013.
14. Hafer, JF, Brown, AM, deMille, P, Hillstrom, HJ, and Garber, CE. The
effect of a cadence retraining protocol on running biomechanics and
efficiency: A pilot study. J Sports Sci 33: 724–731, 2015.
15. Hasegawa, H, Yamauchi, T, and Kraemew, WJ. Foot strike patterns
of runners at the 15-km point during an elite-level half marathon.
J Strength Cond Res 21: 888–893, 2007.
16. Heiderscheit, BC, Chumanov, ES, Michalski, MP, Wille, CM, and
Ryan, MB. Effects of step rate manipulation on joint mechanics
during running. Med Sci Sports Exerc 43: 296–302, 2011.
Differences Between Trained Runners Vs. Untrained
2174
Journal of Strength and Conditioning Research
the
TM
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
17. Helgerud, J, Støren, Ø, and Hoff, J. Are there differences in running
economy at different velocities for well-trained distance runners? Eur
J Appl Physiol 108: 1099–1105, 2010.
18. Hunter, I and Smith, GA. Preferred and optimal stride frequency,
stiffness and economy: Changes with fatigue during a 1-h high-
intensity run. Eur J Appl Physiol 100: 653–661, 2007.
19. Kyrolainen, H, Belli, A, and Komi, PV. Biomechanical factors affecting
running economy. Med Sci Sports Exerc 33: 1330–1337, 2001.
20. Lenhart, RL, Thelen, DG, Wille, CM, Chumanov, ES, and
Heiderscheit, BC. Increasing running step rate reduces
patellofemoral joint forces. Med Sci Sports Exerc 46: 557–564, 2014.
21. Lucia, A, Esteve-Lanao, J, Olivan, J, Gomez-Gallego, F, San Juan, AF,
Santiago, C, Pe
´rez, M, Chamorro-Vin
˜a, C, and Foster, C. Physiological
characteristics of the best eritrean runners—Exceptional running
economy. Appl Physiol Nutr Metab 31: 530–540, 2006.
22. McGregor, SJ, Busa, MA, Yaggie, JA, and Bollt, EM. High resolution
MEMS accelerometers to estimate VO2 and compare running
mechanics between highly trained inter-collegiate and untrained
runners. PLoS One 4: e7355, 2009.
23. Mercer, JA, Devita, P, Derrick, TR, and Bates, BT. Individual effects
of stride length and frequency on shock attenuation during running.
Med Sci Sports Exerc 35: 307–313, 2003.
24. Mooses, M, Mooses, K, Haile, DW, Durussel, J, Kaasik, P, and
Pitsiladis, YP. Dissociation between running economy and running
performance in elite Kenyan distance runners. J Sports Sci 33: 136–
144, 2015.
25. Morgan, D, Martin, P, Craib, M, Caruso, C, Clifton, R, and
Hopewell, R. Effect of step length optimization on the aerobic
demand of running. J Appl Physiol 77: 245–251, 1994.
26. Morgan, DW, Bransford, DR, Costill, DL, Daniels, JT, Howley, ET,
and Krahenbuhl, GS. Variation in the aerobic demand of running
among trained and untrained subjects. Med Sci Sports Exerc 27: 40 4–
409, 1995.
27. Norton, K, Whittingham, N, Carter, L, Kerr, D, Gore, C, and
Marfell-Jones, M. Measurement techniques in anthropometry. In:
K, Norton and T, Olds, eds. Anthropometrica. Sydney, Australia:
UNSW; 1996. pp. 25–75.
28. Ogueta-Alday, A, Morante, JC, Rodriguez-Marroyo, JA, and Garcia-
Lopez, J. Validation of a new method to measure contact and flight
times during treadmill running. J Strength Cond Res 27: 1455–1462, 2013.
29. Ogueta-Alday, A, Rodrı
´guez-Marroyo, JA, and Garcı
´a-Lo
´pez, J.
Rearfoot striking runners are more economical than midfoot
strikers. Med Sci Sports Exerc 46: 580–585, 2014.
30. Paavolainen, LM, Nummela, AT, and Rusko, HK. Neuromuscular
characteristics and muscle power as determinants of 5-km running
performance. Med Sci Sports Exerc 31: 124–130, 1999.
31. Padulo, J, Annino, G, Migliaccio, GM, D’Ottavio, S, and Tihanyi, J.
Kinematics of running at different slopes and speeds. J Strength Cond
Res 26: 1331–1339, 2012.
32. Running USA. Annual half-marathon report. Available at: http://
www.runningusa.org/annual-reports. Accessed: June 1, 2015.
33. Saunders, PU, Pyne, DB, Telford, RD, and Hawley, JA. Factors
affecting running economy in trained distance runners. Sports Med
34: 465–485, 2004.
34. Schubert, AG, Kempf, J, and Heiderscheit, BC. Influence of stride
frequency and length on running mechanics: A systematic review.
Sports Health 6: 210–217, 2014.
35. Slawinski, JS and Billat, VL. Difference in mechanical and energy
cost between highly, well, and nontrained runners. Med Sci Sports
Exerc 36: 1440–1446, 2004.
36. Støren, Ø, Helgerud, J, and Hoff, J. Running stride peak forces
inversely determine running economy in elite runners. J Strength
Cond Res 25: 117–123, 2011.
37. van Gent, RN, Siem, D, van Middelkoop, M, van Os, AG, Bierma-
Zeinstra, SMA, and Koes, BW. Incidence and determinants of lower
extremity running injuries in long distance runners: A systematic
review. Br J Sports Med 41: 469–480, 2007.
38. Wilcox, AR and Bulbulian, R. Changes in running economy relative
to VO2max during a cross-country season. J Sports Med Phys Fitness
24: 321–326, 1984.
39. Williams, KR and Cavanagh, PR. Relationship between distance
running mechanics, running economy, and performance. J Appl
Physiol 63: 1236–1245, 1987.
Journal of Strength and Conditioning Research
the
TM
|
www.nsca.com
VOLUME 31 | NUMBER 8 | AUGUST 2017 | 2175
Copyright © National Strength and Conditioning Association Unauthorized reproduction of this article is prohibited.
