ArticlePDF Available

Better economy in field running than on the treadmill: Evidence from high-level distance runners


Abstract and Figures

Given the ongoing interest in ways to improve the specificity of testing elite athletes in their natural environment, portable metabolic systems provide an opportunity to assess metabolic demand of exercise in sport-specific settings. Running economy (RE) and maximal oxygen uptake ([Formula: see text]O2max) were compared between track and treadmill (1% inclination) conditions in competitive level European distance runners who were fully habituated to treadmill running (n = 13). All runners performed an exercise test on running track and on treadmill. While [Formula: see text]O2max was similar on the track and on the treadmill (68.5 ± 5.3 vs. 71.4 ± 6.4 ml·kg(-1)·min(-1), p = 0.105, respectively), superior RE was found on the track compared to the treadmill (215.4 ± 12.4 vs. 236.8 ± 18.0 O2 ml·kg(-1)·km(-1), p < 0.001). RE on the track was strongly correlated with RE on the treadmill (r = 0.719, p = 0.006). The present findings indicate that high-level distance runners have significantly better RE but not [Formula: see text]O2max on the track compared to treadmill. This difference may be due to biomechanical adjustments. As RE is strongly correlated between the two conditions, it would be reasonable to assume that interventions affecting RE on the treadmill will also affect RE on the track.
Content may be subject to copyright.
Biology of Sport, Vol. 32 No2, 2015 155
Running economy and VO
max on track and treadmill
Treadmill running is widely used to assess maximal oxygen uptake
max) and to determine aerobic and anaerobic thresholds by
measuring gas exchange during stepwise incremental tests in distance
runners. Furthermore, running economy (RE) has been traditionally
measured by running on a treadmill in standard laboratory settings.
Although running on a treadmill is not the same as running on a track,
it gives an indication of how economical a runner is and how RE can
change over time [1]. In response to the growing interest in ways to
improve the specicity of physiological testing for elite athletes in
their natural environment, portable metabolic systems which enable
the assessment of the metabolic demand of exercise in a sport-spe-
cic eld environment (e.g. running on a track) have been devel-
Running on a treadmill is inuenced by the lack of air resistance
that results in lower energy cost and therefore better RE compared
with running on an outdoor track at the same velocity [1,3]. In 1996,
Jones and Doust [3] showed that the reason for the difference between
treadmill and outdoor running is the extra work required to move
through the air rather than mechanical factors. They introduced a
1% incline of the treadmill gradient to increase the energy cost in
Better economy in eld running than on the treadmill: evidence from
high-level distance runners
, Tippi B
, Mooses K
, Durussel J
, Mäestu J
Faculty of Sport and Exercise Sciences, University of Tartu, Tartu, Estonia
Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University
of Glasgow, Glasgow, United Kingdom
ABSTRACT: Given the ongoing interest in ways to improve the specicity of testing elite athletes in their
natural environment, portable metabolic systems provide an opportunity to assess metabolic demand of exercise
in sport-specic settings. Running economy (RE) and maximal oxygen uptake (
max) were compared between
track and treadmill (1% inclination) conditions in competitive level European distance runners who were fully
habituated to treadmill running (n = 13). All runners performed an exercise test on running track and on treadmill.
max was similar on the track and on the treadmill (68.5 ± 5.3 vs. 71.4 ± 6.4 ml·kg
, p = 0.105,
respectively), superior RE was found on the track compared to the treadmill (215.4 ± 12.4 vs. 236.8 ±
18.0 O
, p < 0.001). RE on the track was strongly correlated with RE on the treadmill (r = 0.719,
p = 0.006). The present ndings indicate that high-level distance runners have signicantly better RE but
max on the track compared to treadmill. This difference may be due to biomechanical adjustments.
As RE is strongly correlated between the two conditions, it would be reasonable to assume that interventions
affecting RE on the treadmill will also affect RE on the track.
Mooses M, Tippi B, Mooses K, Durussel J, Mäestu J. Better economy in eld running than on the
treadmill: evidence from high-level distance runners Biol Sport. 2015;32(2):155–159.
Received: 2014-04-12; Reviewed: 2014-08-24; Re-submitted: 2014-09-03; Accepted: 2014-11-30; Published: 2015-03-15.
compensation. Other possible reasons for differences between the
two running conditions, such as (i) the runner may gain energy from
the motor-driven treadmill belt and (ii) biomechanical changes in
running technique due to different surfaces or to the instability caused
by visual cues from static rather than moving surroundings, have
been discussed [3,4].
The habituation of running on the treadmill can also signicantly
inuence differences in RE between track and treadmill conditions[5],
except for athletes who are fully habituated to treadmill running [3],
as in the present study. Furthermore, from our personal contact with
recreational up to international level runners, we have observed
lower values on the rating of perceived exertion (RPE) scale in track
running compared to treadmill running at the same velocity. It has
also been shown that higher velocities on the track compared to the
treadmill were attained when athletes were asked to maintain the
same relative effort (RPE score) during both running conditions [6].
The aim of the present study was to compare RE and
max values
between running on a treadmill and on a track in high competitive
level habitual treadmill runners using portable metabolic systems. It
was hypothesised that (i) at the speed of 16 km∙h
high-level distance
Original Paper
Biol. Sport 2015;32:155-159
Key words:
treadmill test
running track
running economy
maximal oxygen uptake
running performance
Corresponding author:
Martin Mooses
Faculty of Sport and Exercise
Sciences, University of Tartu,
Tartu, Estonia
Mooses M. et al.
runners have better RE on the track compared to the treadmill;
max values on the track are not different from those on the
Subjects. A total of 13 European distance runners were recruited for
this study. The best performance of the athletes was established
using the International Association of Athletics Federations (IAAF)
Scoring Tables [7,8,9]. These tables assign a denite score to each
performance, enabling comparison between different events [8].
Study procedures and protocols were approved by the Ethics Com-
mittee of the University of Tartu (Tartu, Estonia) and conformed to
the Declaration of Helsinki. All testing procedures and related risks
were described before providing written informed consent to par-
ticipate in the study.
Study design
A cross-sectional analysis of 13 distance runners was performed. On
the rst visit to the laboratory, the main anthropometric parameters
were measured. Runners performed the rst test on an outdoor track
and the second one on a treadmill (see specic protocols below).
Track and treadmill tests were separated by at least 48 h. Athletes
were requested to maintain their usual dietary intake and to refrain
from alcohol throughout the study period [10]. They were also asked
to abstain from hard training and/or competition for at least 24 h
before testing. Athletes wore the same shoes and running clothes for
both of the tests.
Exercise testing
A maximal running test on a 400 m outdoor track was performed.
The athlete ran next to a cyclist who set a speed for each stage using
a speedometer (Cateye Velo 05, Osaka, Japan). The bicycle speed-
ometer was calibrated according to the instructions of the manufac-
turer and checked using the treadmill (HP Cosmos Quasar, Nussdorf-
Traunstein, Germany) speed and 12-channel GPS (Garmin eTrex,
Garmin Ltd, Kansas, USA). Two additional recording GPS devices
(Polar RS800cx G5, Polar Electro Oy, Kempele, Finland and Garmin
Forerunner 405 Garmin Ltd, Kansas, USA) were attached to the
runner to calculate the average running speed of each running stage.
Before commencement of the exercise test, each athlete remained
stationary on the track for three minutes and pre-test cardio-respira-
tory data were collected. Initial running speed was set at 8 km∙h
and then increased by 2 km∙h
every three minutes up to 20 km∙h
The speed at 20 and 22 km∙h
was maintained for two minutes.
From that point on, the speed was increased by 1 km∙h
every two minutes until voluntary exhaustion.
Following familiarisation with the treadmill, participants performed
an incremental running test on a motorized treadmill (HP Cosmos
Quasar, Nussdorf-Traunstein, Germany) until voluntary exhaustion.
Before commencement of the exercise test, each athlete remained
stationary on the treadmill for three minutes and cardio-respiratory
data were collected. The initial running speed was set at 8 km∙h
with a gradient of 1% [3,11] and then increased by 2km∙h
three minutes until 14 km∙h
. The speed of the 16 km∙h
stage on
the treadmill was replaced by the speed measured during the track
test calculated from the average of the values of the two GPS de-
vices rounded to the nearest decimal point (i.e. if the average speed
on the track was 15.7 km∙h
, then the treadmill speed was set to
15.7 km∙h
instead of 16 km∙h
). Following the 3 min 17 km∙h
stage, the speed remained constant and elevation increased 1%
after every one minute until voluntary exhaustion [12].
During track and treadmill tests, expired gases and heart rate(HR)
were measured using the same Metamax 3B device (Cortex Biophysik
GmbH, Leipzig, Germany), which was calibrated before each test
according to instructions of the manufacturer.
was dened as
the highest average
during a 30 s period and a failure to increase
further despite an increase in work rate [13]. RE was measured
during the last two minutes of the speed during
the 16 km∙h
RE was expressed as oxygen cost (O
) and was calcu-
lated as follows:
is steady-state oxygen uptake (ml∙kg
) and v is
running velocity (m∙min
) [14]. Steady state was dened as an in-
crease of less than 100 ml O
over the nal two minutes of the re-
spective running stage [15]. During the treadmill test, ambient tem-
perature and relative humidity in the laboratory were regulated with
an air conditioning device to correspond to conditions on the outdoor
Statistical analysis
Treadmill and track conditions within the group were compared with
the paired t-test or Wilcoxon signed-rank test. Linear relationships
between the two conditions were assessed with Pearson’s correlation
coefcient. Calculations were performed using IBM SPSS v.20 soft-
ware for Windows (SPSS Inc, Chicago, IL, USA). Effect size was
calculated with G*Power v.3.1.7 (University of Düsseldorf, sseldorf,
Germany). Cohen’s d [16] was calculated to indicate effect size and
practical meaningfulness. The effect size was evaluated using Lipsey’s
criteria and considered medium when d was between 0.45 and 0.89,
and large when d was higher than 0.90 [17]. The level of signicance
was set at p < 0.05.
The main characteristics of the runners are presented in table 1.
was similar between track and treadmill conditions
(68.5 ± 5.3 vs. 71.4 ± 6.4 ml∙kg
, p = 0.105, d = 0.49
respectively), superior RE was found on the track compared to the
treadmill (215.4 ± 12.4 vs. 236.8 ± 18.0 O
p < 0.001, d = 1.72) (Figure 1). In other words, runners were 8.8%
more economical on the track than on the treadmill. RE on the track
was strongly correlated with RE on the treadmill (r = 0.719,
Biology of Sport, Vol. 32 No2, 2015
Running economy and VO
max on track and treadmill
p = 0.006). Runners presented signicantly lower VE
(102.3 ±
16.6 vs. 115.5 ± 19.2 l∙min
, p < 0.001, d = 2.19) but not HR
(169 ± 10 vs. 171 ± 8 bpm, p = 0.269, d = 0.32) on the track
compared with the treadmill during the 16 km∙h
stage. VE on the
treadmill was 11.2% higher than that on the track.
The novel nding of the present study was that high-level distance
runners have signicantly better RE on the track compared to the
treadmill with the widely used 1% inclination. The treadmill is not
only a popular research instrument in studying human locomotion
and exercise capacity, but has also been used for training and con-
ditioning purposes for a long time [18,19]. At the same time, as
there is a growing interest in the use of treadmill running as part of
regular training for high-level distance runners, it has been debated
whether the changes observed in laboratory-based
and RE
tests would automatically translate into actual changes in running
performance in the eld. Coaches are looking for reliable sport-spe-
cic tests, which reect the real status of their athletes. Therefore,
assessment of the differences between treadmill and track running
using a modern, portable metabolic system would give the necessary
insight before generalizing the results of treadmill studies to outdoor
running. This is the rst study to use a modern, portable metabolic
measurement system to compare track and treadmill running in high
competitive level distance runners in their everyday training condi-
Several studies have concluded that air resistance is the only
cause of the observed differences between track and treadmill loco-
motion [3,4]. However, Pugh [20] designed a wind screen to allevi-
ate air resistance and still observed higher energy cost in track run-
ning than on the treadmill. This indicated that other factors might
be responsible for the differences in RE between the two running
conditions, such as biomechanical adjustments [19]. Running in a
more “natural” environment on a track compared to a more “articial”
environment on a treadmill led to a better RE of 8.8%. This better
RE may be partly explained by the signicantly lower VE on the track
compared to the treadmill. As ventilatory work accounts for 7–8%
of the overall energy cost of exercise [21], a decrease in VE leads to
a decrease in
(i.e. better RE) [22,23,24]. The technique of run-
ning on a treadmill is different to that running over ground where the
hamstrings are used to a greater extent to produce propulsive forc-
es[1]. The slightly different muscle recruitment patterns on the
treadmill can then lead to an increase in ventilation, especially at
submaximal stages on a treadmill [25]. The ndings of the present
study are in agreement with the signicantly higher energy expendi-
ture observed during treadmill running at submaximal stages com-
pared to track running [25]. On the other hand, contradictory results
showing no signicant differences or impairment in RE between track
and treadmill conditions have previously been reported [3,20,26,27].
However, these studies were conducted with the Douglas bag meth-
od for eld measurements, which likely interfered with running move-
ments and thus limited the submaximal values [25]. While it seems
that there is a consensus that biomechanical adjustments occur
between treadmill and track conditions and can consequently alter
Europeans (N = 13)
Age (years) 25.4 ± 4.4
Mass (kg) 69.0 ± 5.9
Height (m) 1.81 ± 0.05
BMI (kg∙m
) 21.0 ± 1.2
IAAF (p) 786 ± 111
Regular training (years) 8.3 ± 5.3
Note: BMI – body mass index; IAAF (p) – International Amateur Athletic
Federation scoring table points.
Characteristics of participants (mean ± SD).
Mean (thick lines with triangles) and individual results for running economy (A), ventilation (B) and heart rate (C).
Note: * – signicant difference between track and treadmill.
Mooses M. et al.
energy expenditure, the conclusion on whether these biomechanical
adjustments are advantageous on the treadmill or on the track may
differ due to the characteristics of the group studied (e.g. sprinters
vs. endurance runners) [19]. The slightly higher RE values at the
speed of 16 km∙h
reported in the present study compared to previ-
ously published data [11,28,29,30] are most likely due to the por-
table device MetaMax 3B used to measure
. However, and im-
portantly, although the MetaMax 3B has been shown to overestimate
by up to 10% when compared to the primary criterion Douglas
bag method [2,31] and secondary criterion Jaeger Oxycon Pro sys-
tem[31], it has excellent reproducibility, with a typical error of 2–3%
and VE
Using a modern portable metabolic system, the present study also
conrmed that identical
results are obtained during tests
conducted in both treadmill and track running conditions. This indi-
cates that
in running is independent of the execution of the
test whether on the track or on the treadmill, if an equal amount of
effort is spent [25]. Finally, the practical implications of the ndings
of the present study give condence for running coaches that training
methods resulting in an improvement in RE and
in treadmill
tests would lead to a similar improvement in running on the track in
high-level distance runners. However, the 1% inclination on the tread-
mill is likely to be too high to reproduce similar efforts to those in
track running.
In the present study we demonstrated in high-level distance runners
that (i) RE is signicantly better on the track compared to the tread-
mill, and (ii)
values do not depend on whether the test was
conducted on a treadmill or on a track. Finally, as RE was strongly
correlated between conditions, it is reasonable to assume that inter-
ventions affecting RE on the treadmill will also affect RE on the track.
The authors wish to specially thank the subjects for their participation
and cooperation. We would also like to thank the Prof. Toivo Jürimäe,
Prof. Jaak Jürimäe, Prof. Priit Kaasik, Dr. Priit Purge, Dr. Evelin Lätt
and Dr. Helena Liiv who helped with some aspects of data collection,
technical assistance and logistic support during the study. The study
was funded by grant from the Estonian Ministry of Education and
Science Institutional Grant TKKSP 14058I.
Conict of interests: the authors declared no conict of interests
regarding the publication of this manuscript.
1. Saunders PU, Pyne DB, Telford RD,
Hawley JA. Factors affecting running
economy in trained distance runners.
Sports Med. 2004;34:465-485.
2. Vogler AJ, Rice AJ, Gore CJ. Validity and
reliability of the cortex MetaMax3B
portable metabolic system. J Sports Sci.
3. Jones AM, Doust JH. A 1% treadmill
grade most accurately reects the
energetic cost of outdoor running.
J Sports Sci. 1996;14:321-327.
4. van Ingen Schenau GJ. Some
fundamental aspects of the biomechanics
of overground versus treadmill
locomotion. Med Sci Sports Exerc.
5. Lavcanska V, Taylor NF, Schache AG.
Familiarization to treadmill running in
young unimpaired adults. Hum Mov Sci.
6. Ceci R, Hassmen P. Self-monitored
exercise at three different RPE intensities
in treadmill vs eld running. Med Sci
Sports Exerc 1991;23:732-738.
7. Lucia A, Olivan J, Bravo J, Gonzalez-
Freire M, Foster C. The key to top-level
endurance running performance: A
unique example. Br J Sports Med.
8. Legaz A, Eston R. Changes in
performance, skinfold thicknesses, and
fat patterning after three years of intense
athletic conditioning in high level
runners. Br J Sports Med. 2005;39:851-
9. Spiriev B. IAAF Scoring Tables of
Athletics. Revised ed. Monaco:
Multiprint; 2011.
10. Santos-Concejero J, Granados C,
Irazusta J, Bidaurrazaga-Letona I,
Zabala-Lili J, Tam N, Gil SM. Differences
in ground contact time explain the less
efcient running economy in north
african runners. Biol Sport.
11. Lucia A, Esteve-Lanao J, Olivan J,
Gomez-Gallego F, San Juan AF,
Santiago C, Perez M, Chamorro-Vina C,
Foster C. Physiological characteristics of
the best eritrean runners-exceptional
running economy. Appl Physiol Nutr
Metab. 2006;31:530-540.
12. Mooses M, Mooses K, Haile DW,
Durussel J, Kaasik P, Pitsiladis YP.
Dissociation between running economy
and running performance in elite Kenyan
distance runners. J Sports Sci.
13. Wasserman K, Hansen JE, Sue DY,
Stringer WE, Whipp BJ. Measurements
during integrative cardiopulmonary
exercise testing. In: Wasserman K,
Hansen E, Sue Y, Stringer E, Whipp J,
editors. Principles of exercise testing and
interpretation. Including pathophysiology
and clinical applications. 4th ed.
Philadelphia:Lippincott Williams &
Wilkins; 2005. p. 100-105.
14. Bragada JA, Santos PJ, Maia JA,
Colaco PJ, Lopes VP, Barbosa TM.
Longitudinal study in 3,000 m male
runners: Relationship between
performance and selected physiological
parameters. J Sports Sci Med.
15. Fletcher JR, Esau SP, Macintosh BR.
Economy of running: Beyond the
measurement of oxygen uptake. J Appl
Physiol. 2009;107:1918-1922.
16. Cohen J. Statistical power analysis for
the behavioural sciences. Hillsdale, NJ:
Lawrence Erlbaum Associates;1988.
17. Lipsey MW. Design sensitivity: Statistical
power for experimental research.
Newbury Park, CA: Sage;1990.
18. Riley PO, Dicharry J, Franz J, Croce UD,
Wilder RP, Kerrigan DC. A kinematics and
kinetic comparison of overground and
treadmill running. Med Sci Sports Exerc.
19. Frishberg BA. An analysis of overground
and treadmill sprinting. Med Sci Sports
Exerc. 1983;15:478-485.
20. Pugh LG. Oxygen intake in track and
treadmill running with observations on
the effect of air resistance. J Physiol.
21. Milic-Emili G, Petit JM, Deroanne R.
Mechanical work of breathing during
exercise in trained and untrained
subjects. J Appl Physiol. 1962;17:43-
22. Bailey SP, Pate RR. Feasibility of
improving running economy. Sports Med.
23. Pate RR, Macera CA, Bailey SP,
Bartoli WP, Powell KE. Physiological,
Biology of Sport, Vol. 32 No2, 2015
Running economy and VO
max on track and treadmill
anthropometric, and training correlates of
running economy. Med Sci Sports Exerc.
24. Thomas DQ, Fernhall B, Grant H.
Changes in running economy during a
5km run in trained men and women
runners. J Strength Cond Res.
25. Meyer T, Welter JP, Scharhag J,
Kindermann W. Maximal oxygen uptake
during eld running does not exceed that
measured during treadmill exercise. Eur J
Appl Physiol. 2003;88:387-389.
26. McMiken DF, Daniels JT. Aerobic
requirements and maximum aerobic
power in treadmill and track running.
Med Sci Sports. 1976;8:14-17.
27. Bassett DR, Giese MD, Nagle FJ,
Ward A, Raab DM, Balke B. Aerobic
requirements of overground versus
treadmill running. Med Sci Sports Exerc.
28. Tam E, Rossi H, Moia C, Berardelli C,
Rosa G, Capelli C, Ferretti G. Energetics
of running in top-level marathon runners
from kenya. Eur J Appl Physiol.
29. Billat V, Lepretre PM, Heugas AM,
Laurence MH, Salim D, Koralsztein JP.
Training and bioenergetic characteristics
in elite male and female kenyan runners.
Med Sci Sports Exerc. 2003;35:297-
30. Weston AR, Mbambo Z, Myburgh KH.
Running economy of african and
caucasian distance runners. Med Sci
Sports Exerc. 2000;32:1130-1134.
31. Macfarlane DJ, Wong P. Validity,
reliability and stability of the portable
cortex metamax 3B gas analysis system.
Eur J Appl Physiol. 2012;112:2539-
... However, some studies have come to the opposite conclusion. A study with 13 high-level competitive athletes suggests that running in a natural environment in the wild may be more economical than running on a treadmill [23]. This discrepancy may be related to biomechanical adjustments. ...
... Second, the order of the two testing sessions may also have a potential effect on the outcome of the test. In some studies, the testing order of treadmill running and ground running was not random [1,23], and the interval between two running tests was too short, which could affect the final test results. In addition, most studies did not include important indicators for monitoring aerobic exercise intensity such as blood glucose and blood lactate [15], as well as parameters for muscle contractile properties [22], which may reflect the state of the muscle or the fatigue level [2,21]. ...
Full-text available
Purpose This study aimed to compare the effects of ground and treadmill running on energy metabolism and muscle contractile properties, providing a basis for the general public to choose running venues. Methods Ten male college students (age, 20.10 ± 1.53 years; height, 176.20 ± 5.49 cm; weight, 72.14 ± 8.25 kg; body fat percent, 12.41% ± 4.65%) were recruited in this study. Energy expenditure (EE) was measured using the accelerometer (GT9X) combined with specific estimation equations. Average heart rate (HR) was measured using a heart rate band (Polar). Muscle contractile properties were assessed by measuring muscle displacement (Dm) and contraction velocity (Vc) using tensiomyography (TMG-S1). Blood glucose (Glu) and lactate (Lac) were measured by portable devices (eB-G and Lactate Scout). The running speed was 9 km/h and the duration was 25 min. Two-way ANOVA (protocol × time) was used to analyze the effect of running protocols on energy metabolism and muscle contractile properties. Results EE of treadmill running was significantly higher than EE of ground running (protocol main effect, P < 0.001), and HR of treadmill running was significantly higher than that of ground running in the first testing time (protocol simple effect, P = 0.026; protocol × time interaction P = 0.043). The decrease in Dm of the rectus femoris after treadmill running was significantly higher than that of ground running (protocol main effect, P = 0.009). The interaction of different running protocols and testing times on Lac was significant ( P = 0.025), but all results of the simple effects analysis were not statistically significant ( P > 0.05). Conclusion Our study found a difference in energy expenditure between treadmill and ground running at 9 km/h with duration of 25 min. In addition, treadmills are more likely to cause a decrease in muscle displacement distance of the rectus femoris measured after exercise than ground running. Future studies are needed to further investigate whether the differences are induced by internal metabolism or the environmental conditions of running.
... Third, compared to outdoor running, running on the treadmill shows some differences in terms of biomechanical parameters, such as sagittal foot strike angle or knee flexion at foot strike [56]. These small differences could be due to insufficient experience running on a treadmill, surface stiffness, and differences in air resistance, and result in limited transferability to outdoor measurements, since there is evidence that RE differs between treadmill and track running [57]. Future studies should be conducted under field conditions to achieve more realistic results. ...
Full-text available
Footwear properties can influence physiological and biomechanical variables, which may lead to positive changes in distance running performance. One innovative development in running shoe technology is adding carbon fiber plates to increase midsole bending stiffness. However, there are only a few studies investigating the influence of shoe conditions on both physiological and biomechanical variables, simultaneously, when running for longer than 5 min or for distances > 1 km. Hence, the purpose of the current study was to investigate the influence of different running shoe concepts with carbon fiber plates on physiological and biomechanical parameters during a 10 km treadmill run. Twenty-three athletes participated in the study, which comprised four measurement days for each subject. On the first day, subjects performed a treadmill exhaustion test to determine maximum oxygen uptake. On the second, third, and fourth days, each subject ran 10 km at 70% of their maximum oxygen uptake in one of three shoe models. Significant differences were found between the shoe conditions for the biomechanical parameters, but not for the physiological parameters. It seems that runners adjusted their running styles to the shoe conditions during the 10 km run to reduce the load on the lower extremities without compromising their endurance performance. These results may have practical implications for runners, coaches, and shoe manufacturers.
... Bassett et al. (1985) reported that HR and V O 2 measured when running on a horizontal treadmill are higher than those observed during flat overground running at a given velocity (Bassett et al., 1985). This discrepancy, which increases with the velocity, alters the running economy when using a treadmill (Mooses et al., 2015). All these observations highlight the specificities of treadmill running that might have under-estimated the importance of the effect of the terrain condition (vs. ...
The objectives of this thesis were to investigate the performance determinants of trail running, and to evaluate the changes in running economy following prolonged endurance running exercise. First, we tested elite road and trail runners for differences in performance factors. Our results showed that elite trail runners are stronger than road runners, but they have greater cost of running when running on flat ground. In the second study, we evaluated the performance factors that predicted performance in trail running races of different distances, ranging from 40 to 170 km. We found that maximal aerobic capacity was a determinant factor of performance for races up to 100 km. Performance in shorter races, up to approximately 55 km, was also predicted by lipid utilization at slow speed, while performance in the 100 km race was also predicted by maximal strength and body fat percentage. The most important factors of performance for races longer than 100 km are still debated. We also tested the effects of trail running race distance on cost of locomotion, finding that cost of running increased after races up to 55 km, but not after races of 100-170 km. Finally, we tested the. effects of two different exercise modalities, cycling and running, on cost of locomotion, after 3 hours of intensity-matched exercise. Cost of locomotion increased more following cycling than running, and the change in cost of locomotion was related to changes in cadence and loss of force production capacity.
... Because the product of muscle force and moment arm length is muscle moment, it is reasonable to expect that individuals with longer AT-MA would generate higher plantar flexors moments with lower and faster force generation hence greater efficiency. Against such expectations, experimental data seem to suggest that sprint performance (Kumagai et al., 2000;Lee and Piazza, 2009;Baxter et al., 2012) and running economy are associated with shorter instead of longer AT-MA [1,36,41]. ...
... heart-rate in case of fitness trackers) enables their widespread use in many areas. The previously mentioned popular Garmin Forerunner (FR) series has in the recent decade been used in (1) sports: FR model 405 -average and maximum speeds in football referees [6], FR 110training volume in runners [7], FR 305 -running time-trial [8], assessment of heart-rate, pace, speed on various surfaces in orienteering runners [9]; FR 910xt and FR 610 -reporting on the training duration and heart-rate in cross-country skiing [10]; FR 310xt -speed control, and assessment of the beginning and end of test sections for canoeists [11]; FR 920xt -recording the heart-rate, height, position and the speed of cross-country skiers [12]; unspecified FRobtaining additional running parameters for athletes training at various heights [13,14], (2) studies on physical activity of various social groups: FR 305 -youth [15] and children [16], FR 910xt -special operations forces [17]; FR 220children [18,19], and (3) in other studies: FR 920xt -estimation of energy expenditure [20], FR 225 -as a heart-rate monitoring device [21] or FR 405 -monitoring speed [22]. ...
The article attempts to assess the positioning accuracy of a series of twelve low-cost, code GNSS receivers, manufactured by a single producer (Garmin) in the years 2003-2019, dedicated to runners. The use of such devices in recreation and sports is widespread, but they differ from each other depending on Global Navigation Satellite Systems used and individual characteristics. The surveys were carried out with the use of experimental railway measurement platform, at three speeds (10, 30, 50 km/h). The position accuracy measures commonly used in geodesy and navigation were calculated, as well as Cross Track Error measure for two confidence levels of 68% and 95%. The results demonstrated improvements in accuracy, primarily because of the number of GNSS systems used; e.g. 2011 GPS-only receiver 2DRMS=10.35 m; 2015 GPS/GLONASS 2DRMS=8.14 m and 2019 GPS/GLONASS/Galileo 2DRMS=4.29 m. The test speed did not have a significant effect on the accuracy of the devices.
... However, already in 1980, the Dutch biomechanist van Ingen Schenau showed that there are no mechanical differences between treadmill and overground locomotion as long as the belt's speed remains constant (van Ingen Schenau, 1980). Yet, other factors might affect the physiological determinants of treadmill walking and running: the compliance of the surface, the lack of air resistance, the fixed rather than moving visual feedback, the degree of habituation, among others (Jones and Doust, 1996;Parvataneni et al., 2009;Mooses et al., 2014;Miller et al., 2019;Van Hooren et al., 2019). For instance, when comparing the energetics and performance outcomes of treadmill and overground running in humans, a great variability across studies arises, some of which is related to the different speeds used for the investigation . ...
Full-text available
The use of motorized treadmills as convenient tools for the study of locomotion has been in vogue for many decades. However, despite the widespread presence of these devices in many scientific and clinical environments, a full consensus on their validity to faithfully substitute free overground locomotion is still missing. Specifically, little information is available on whether and how the neural control of movement is affected when humans walk and run on a treadmill as compared to overground. Here, we made use of linear and non-linear analysis tools to extract information from electromyographic recordings during walking and running overground, and on an instrumented treadmill. We extracted synergistic activation patterns from the muscles of the lower limb via non-negative matrix factorization. We then investigated how the motor modules (or time-invariant muscle weightings) were used in the two locomotion environments. Subsequently, we examined the timing of motor primitives (or time-dependent coefficients of muscle synergies) by calculating their duration, the time of main activation, and their Hurst exponent, a non-linear metric derived from fractal analysis. We found that motor modules were not influenced by the locomotion environment, while motor primitives were overall more regular in treadmill than in overground locomotion, with the main activity of the primitive for propulsion shifted earlier in time. Our results suggest that the spatial and sensory constraints imposed by the treadmill environment might have forced the central nervous system to adopt a different neural control strategy than that used for free overground locomotion, a data-driven indication that treadmills could induce perturbations to the neural control of locomotion.
... dropping jump), similar in their motor pathways to the chosen test. The specificity of training-related mechanism could explain the high effectiveness of the plyometric training in these tests (Mooses et al., 2015). ...
The aim of the study was to evaluate the effects of 6-weeks accentuated eccentric training, using a rotary inertial device, on range of motion, assessed with Inter Malleolar Distance test, anthropometry, lower limb explosive and reactive strength, assessed with Squat Jump, Countermovement Jump and 7-Repeated Hop tests, in young elite fencers. Moreover, the effects on hamstring eccentric strength and two technical fencing movements, lunge and advance-advance lunge, were evaluated with motion analysis. The second aim was to evaluate the duration of the accentuated eccentric training residual effects, 6 weeks after the end of the training. Fifty-four male fencers were randomly assigned either to the Inertial Group (IG; n = 26; aged 17.3 ± 1.9 years) such as experimental group, or to the Plyometric Group (PG; n = 28; aged 17.6 ± 2.7 years) such as control group. IG carried out four exercises using the rotary inertial device attached to their waist by a rope. PG carried out several plyometric exercises at the same time in which the IG performed the accentuated eccentric training. MANOVA showed significant improvements in the vertical jumps height post training, with no differences between IG and PG. Significant improvements for technical movements, lunge distance (p = 0.006) and advance-advance lunge distance (p = 0.00005), were found within-group and between-groups (p = 0.00001), with higher improvements in IG than in PG. The univariate analysis showed a significant improvement in lower limb range of motion with higher increase in IG than in PG. The main findings were the significant improvement in lunge and advance-advance lunge distance, maintaining with the same execution time. These results suggested that it is important to apply accentuated eccentric load on specific sport movements.
... How-298 ever, despite the evidence, the findings were ambigu-299 ous when comparing both methods of measuring VO 2 300 max [34-37]. Mooses et al. [36] found differences in 301 favor of laboratory evaluation (68.5 ± 5.3 and 71.4 ± 302 6.4 mLO 2 ·min −1 ·Kg −1 in the field and the laboratory, 303 respectively, p = 0.105), whereas Schram et al. [37] 304 evidenced higher values for evaluation in the field than 305 in the laboratory (+5.28%, p = 0.03). A third study 306 by Floriano et al. [35] revealed a higher VO 2 max in 307 the field than in the laboratory (Tlim test: 51.1 ± 4.7 308 and 49.6 ± 4.7 mLO 2 ·min −1 ·Kg −1 , respectively, p = 309 0.10). ...
Full-text available
BACKGROUND: The maintenance of maximal aerobic speed (MAS) until exhaustion is an important parameter for the evaluation of sports performance and prescription and planning of training. OBJECTIVE: To validate a 6-minute race test (6MRT) as a predictor of MAS in university endurance athletes. METHODS: Twenty two university endurance athletes (12 males and 10 females) were part of the study. The design was pre-experimental. The primary variables were the time of maintenance of the MAS on the field through a Time Limit Test (Tlim test), and the VO2 max (laboratory and field). The statistical analysis of the time and ventilatory variables was carried out using descriptive statistics; the comparison between males and females for all variables was carried out through a t-Student test for independent samples (p< 0.05). RESULTS: The performance in the Tlim test was 356.4 ± 52.9 and 327.0 ± 120.2 s in males and females, respectively. CONCLUSION: Based on the time of maintenance of the MAS (Tlim test), the 6MRT is a valid test to determine the MAS in university endurance male athletes. However, the MAS in university endurance female athletes must be evaluated with a shorter test (between 5 and 5.30 minutes long).
The goal of this study was to analyze the effects of ground technicity on cardio-respiratory and biomechanical responses during uphill running. Ten experienced male trail-runners ran ∼ 10.5 min at racing pace on two trails with different (high and low) a priori technicity levels. These two runs were replicated (same slope, velocity, and distance) indoor on a motor-driven treadmill. Oxygen uptake, minute ventilation (VE), heart rate as well as step frequency and medio-lateral feet accelerations (i.e. objective indices of uneven terrain running patterns adjustments) were continuously measured throughout all sessions. Rating of perceived exertion (RPE) and perceived technicity were assessed at the end of each bout. Oxygen cost of running (O2Cr) (+10.5%; p<0.001), VE (+21%; p<0.004) and the range and variability of feet medio-lateral accelerations (+116% and +134%, respectively; p<0.001), were significantly greater when running on trail compared to treadmill, regardless of the a priori technicity level. Despite perceived technicity being lower on treadmill (p<0.001), RPE was not different between trail and treadmill runs (p < 0.68). It is concluded that running uphill on a trail vs. a treadmill significantly elevates both O2Cr and magnitude/variability of feet medio-lateral accelerations but no difference could be identified between trails of different a priori technicities. These results strengthen the need for trainers and race organizers to consider terrain technicity per se as a challenging cardio-respiratory and biomechanical component in uphill trail running.
Full-text available
Objectives; the aim of this study was evaluate the association between a predictive test of maximum oxygen consumption (V O2max) and performance in a national competition in Chilean CrossCountry athletes. Methods; 18 athletes participated. The V O2max was measured with ergospirometer test (ET), and was estimated with the Cooper and Klissouras test. V O2max was compared between the three methods and were correlated to the competition performance. The SPSS v.22 program was used (p<0.05). Results; there were differences in the V O2max between the three methods [F (2. 53) = 14.147; p<0,001)], between the ET with the Klissouras test (p<0.001), but no with the Cooper test (p=0.355). The V O2max in the Cooper test was the best correlation with the competition (r =-0.908; p<0.001). Discussion; some studies have found no differences between the direct measurement of V O2max on the treadmill and athletic track test. However, there are inverse correlations between an incremental treadmill test V O2max and a field test, where when performing less time on the running track there was a higher oxygen consumption in the laboratory. Conclusions; it is concluded that, Cooper's test is the best related to competition, so it could predict performance.
Full-text available
Abstract The purpose of this study was to investigate the relationship between running economy (RE) and performance in a homogenous group of competitive Kenyan distance runners. Maximal aerobic capacity (VO2max) (68.8 ± 3.8 ml∙kg(-1)∙min(-1)) was determined on a motorised treadmill in 32 Kenyan (25.3 ± 5.0 years; IAAF performance score: 993 ± 77 p) distance runners. Leg anthropometry was assessed and moment arm of the Achilles tendon determined. While Achilles moment arm was associated with better RE (r(2) = 0.30, P = 0.003) and upper leg length, total leg length and total leg length to body height ratio were correlated with running performance (r = 0.42, P = 0.025; r = 0.40, P = 0.030 and r = 0.38, P = 0.043, respectively), RE and maximal time on treadmill (tmax) were not associated with running performance (r = -0.01, P = 0.965; r = 0.27; P = 0.189, respectively) in competitive Kenyan distance runners. The dissociation between RE and running performance in this homogenous group of runners would suggest that RE can be compensated by other factors to maintain high performance levels and is in line with the idea that RE is only one of many factors explaining elite running performance.
Full-text available
The purpose of this study was to investigate the relationship between biomechanical variables and running economy in North African and European runners. Eight North African and 13 European male runners of the same athletic level ran 4-minute stages on a treadmill at varying set velocities. During the test, biomechanical variables such as ground contact time, swing time, stride length, stride frequency, stride angle and the different sub-phases of ground contact were recorded using an optical measurement system. Additionally, oxygen uptake was measured to calculate running economy. The European runners were more economical than the North African runners at 19.5 km · h(-1), presented lower ground contact time at 18 km · h(-1) and 19.5 km · h(-1) and experienced later propulsion sub-phase at 10.5 km · h(-1),12 km · h(-1), 15 km · h(-1), 16.5 km · h(-1) and 19.5 km · h(-1) than the European runners (P < 0.05). Running economy at 19.5 km · h(-1) was negatively correlated with swing time (r = -0.53) and stride angle (r = -0.52), whereas it was positively correlated with ground contact time (r = 0.53). Within the constraints of extrapolating these findings, the less efficient running economy in North African runners may imply that their outstanding performance at international athletic events appears not to be linked to running efficiency. Further, the differences in metabolic demand seem to be associated with differing biomechanical characteristics during ground contact, including longer contact times.
Full-text available
The purpose of the present study was to analyze longitudinal changes in 3,000 m running performance and the relationship with selected physiological parameters. Eighteen well-trained male middle-distance runners were measured six times (x3 per year) throughout two consecutive competitive seasons. The following parameters were measured on each occasion: maximal oxygen uptake (VO2max), running economy (RE), velocity at maximal oxygen uptake (vVO2max), velocity at 4mmol L-1 blood lactate concentration (V4), and performance velocity (km·h-1) in 3,000 m time trials. Values ranged from 19.59 to 20.16 km·h-1, running performance; 197 to 207 mL·kg-1·km-1. RE; 17.2 to 17.7 km·h-1, V4; 67.1 to 72.5 mL·kg-1·min-1, VO2max; and 19.8 to 20.2 km·h-1, vVO2max. A hierarchical linear model was used to quantify longitudinal relationships between running performance and selected physiological variables. Running performance decreased significantly over time, between each time point the decrease in running velocity was 0.06 km·h-1. The variables that significantly explained performance changes were V4 and vVO2max. Also, vVO2max and V4 were the measures most strongly correlated with performance and can be used to predict 3,000 m race velocity. The best prediction formula for 3,000 m running performance was: y = 0.646 + 0.626x + 0.416z (R2=0.85); where y = V3,000 m velocity (km·h-1), x = V4 (km·h-1) and z = vVO2max (km·h-1). The high predictive power of vVO2max and V4 suggest that both coaches and athletes should give attention to improving these two physiological variables, in order to improve running performance.
Full-text available
On ten top-level Kenyan marathon runners (KA) plus nine European controls (EC, equivalent to KA), we measured maximal oxygen consumption ([Formula: see text]) and the energy cost of running (C (r)) on track during training camps at moderate altitude, to better understand the KA dominance in the marathon. At each incremental running speed, steady-state oxygen consumption ([Formula: see text]) was measured by telemetric metabolic cart, and lactate by electro-enzymatic method. The speed requiring [Formula: see text] provided the maximal aerobic velocity (v (max)). The energy cost of running was calculated by dividing net [Formula: see text] by the corresponding speed. The speed at lactate threshold (v (ΘAN)) was computed from individual Lâ(b) versus speed curves. The sustainable [Formula: see text] fraction (F (d)) at v (ΘAN) (F (ΘAN)) was computed dividing v (ΘAN) by v (max). The F (d) for the marathon (F (mar)) was determined as F (mar) = 0.92 F (ΘAN). Overall, [Formula: see text] (64.9 ± 5.8 vs. 63.9 ± 3.7 ml kg(-1) min(-1)), v (max) (5.55 ± 0.30 vs. 5.41 ± 0.29 m s(-1)) and C (r) (3.64 ± 0.28 vs. 3.63 ± 0.31 J kg(-1) m(-1)) resulted the same in KA as in EC. In both groups, C (r) increased linearly with the square of speed. F (ΘAN) was 0.896 ± 0.054 in KA and 0.909 ± 0.068 in EC; F (mar) was 0.825 ± 0.050 in KA and 0.836 ± 0.062 in EC (NS). Accounting for altitude, running speed predictions from present data are close to actual running performances, if F (ΘAN) instead of F (mar) is taken as index of F (d). In conclusion, both KA and EC did not have a very high [Formula: see text], but had extremely high F (d), and low C (r), equal between them. The dominance of KA over EC cannot be explained on energetic grounds.
Full-text available
This study investigated the performance of the portable Cortex Metamax 3B (MM3B) automated gas analysis system during both simulated and human exercise using adolescents. Repeated measures using a Gas Exchange System Validator (GESV) across a range of simulated metabolic rates, showed the MM3B to be adequately reliable (both percentage errors, and percentage technical error of measurements <2%) for measuring expired ventilation (V (E)), oxygen consumption (VO(2)), and carbon dioxide production (VCO(2)). Over a 3 h period, the MM3B was shown to be acceptably stable in measuring gas fractions, as well as V (E), VO(2), and VCO(2) generated by the GESV, especially at moderate and high metabolic rates (drifts <2% and of minor physiological significance). Using eight healthy adolescents during rest, moderate, and vigorous cycle ergometry, the validity of the MM3B was tested against the primary criterion Douglas bag method (DBM) and a secondary criterion machine known to be accurate, the Jaeger Oxycon Pro system. No significant errors in V (E) were noted, yet the MM3B significantly overestimated both VO(2) and VCO(2) by approximately 10-17% at moderate and vigorous exercise as compared to the DBM and at all exercise levels compared to the Oxycon Pro. No significant differences were seen in any metabolic variable between the two criterion systems (DBM and Oxycon Pro). It is concluded the MM3B produces acceptably stable and reliable results, but is not adequately valid during moderate and vigorous exercise without some further correction of VO(2) and VCO(2).
Applied experimental research investigates the effects of deliberate intervention in situations of practical importance. The basic elements of experimental research are well-known. To ensure that the conclusions about intervention effects drawn from experimental design are correct, the design must have both sensitivity and validity. My goal in this chapter is to help researchers to "tune" experimental design to maximize sensitivity. However, before I can offer a close examination of the practical issues related to design sensitivity, I need to present a refined framework for describing and assessing the desired result—a high probability of detecting a given magnitude of effect if it exists. Topics discussed in this chapter are: the statistical power framework; optimizing statistical power; design strategy to enhance power; and what effect size is worth detecting. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Research indicates that running economy (RE) changes during a 5-km run. However, the mechanisms accounting for this variation have not been identified. This study explored the effects of a 5-km run on the RE, minute ventilation (VE), blood lactate (LA), and core temperature (CT) of 40 distance runners (21 men and 19 women). After an initial testing session to determine maximum oxygen consumption (VO2max), each subject (age: 30.8 years, range: 21-48 years; VO2max: 54.9 ml?kg-1?minr-1, SD +/- 6.9) performed a 5-km run on a treadmill at a constant pace selected to elicit an intensity equivalent to 80-85% of their VO2max. The data provide response characteristics for an early run phase (P1, 5 minutes into the run) and an end-of-the-run phase (P2, during the last minute of the run). Oxygen consumption was used to determine RE. Heart rate (HR), VE, LA, and CT were measured during both phases. All variables increased significantly between P1 and P2 (p < 0.01), and the increases were similar for men and women. During the 5-km run, changes in RE and VE were significantly related (r = 0.64; p < 0.05). When the data were analyzed by sex, stronger correlations were found for the women for RE and VE (r = 0.80; p < 0.05) compared with men (r = 0.59; p < 0.05). The changes in RE and LA (r = 0.45; p < 0.05) and LA and VE (r = 0.61; p < 0.05) were significantly related only in the women runners, whereas the men runners did not demonstrate these relationships. The combined contributions of changes in VE, LA, CT, and sex were evaluated through stepwise regression. The multiple regression, using all subjects, showed that only the change in VE was included as an independent variable (p < 0.05). None of the other variables contributed significantly to the change in VO2. Conducting the same multiple regression on the men and women separately produced the same results for both groups, i.e., only the change in VE was included as an independent variable, and none of the other changes contributed significantly to the change in VO2. (C) 1999 National Strength and Conditioning Association