Citation: Cassirame, J.; Godin, A.;
Chamoux, M.; Doucende, G.; Mourot,
L. Physiological Implication of Slope
Gradient during Incremental
Running Test. Int. J. Environ. Res.
Public Health 2022, 19, 12210.
https://doi.org/10.3390/
ijerph191912210
Academic Editor: Luca Paolo Ardigo
Received: 18 August 2022
Accepted: 22 September 2022
Published: 26 September 2022
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International  Journal  of
Environmental Research
and Public Health
Article
Physiological Implication of Slope Gradient during
Incremental Running Test
Johan Cassirame 1,2,3,*
, Antoine Godin 4
, Maxime Chamoux 5
, Gregory Doucende 5,†
and Laurent Mourot 4,†
1
Laboratory Culture Sport Health and Society (C3S−UR 4660), Sport and Performance Department,
University of Bourgogne Franche-Comte, 25000 Besançon, France
2
EA7507, Laboratoire Performance, Santé, Métrologie, Société, 51100 Reims, France
3
Mtraining, R&D Division, 25480 Ecole-Valentin, France
4
EA3920-Prognostic Markers and Regulatory Factors of Heart and Vascular Diseases, and Exercise
Performance, Health, Innovation Platform, University Bourgogne Franche-Comté, 25000 Besançon, France
5
Laboratoire Interdisciplinaire Performance Santé en Environnement de Montagne (LIPSEM), UR-4604,
Université de Perpignan Via Domitia, 7 Avenue Pierre de Coubertin, 66120 Font-Romeu, France
*
Correspondence: johancassirame@free.fr
†
These authors contributed equally to this work.
Abstract: Uphill running induces a higher physiological demand than level conditions. Although
many studies have investigated this locomotion from a psychological point of view, there is no clear
position on the effects of the slope on the physiological variables during an incremental running
test performed on a slope condition. The existing studies have heterogeneous designs with different
populations or slopes and have reported unclear results. Some studies observed an increase in
oxygen consumption, whereas it remained unaffected in others. The aim of this study is to investigate
the effect of a slope on the oxygen consumption, breathing frequency, ventilation and heart rate
during an incremental test performed on 0, 15, 25 and 40% gradient slopes by specialist trail runners.
The values are compared at the ﬁrst and second ventilatory threshold and exhaustion. A one-way
repeated measures ANOVA, with a Bonferroni post-hoc analysis, was used to determine the effects
of a slope gradient (0, 15, 25 and 40%) on the physiological variables. Our study shows that all the
variables are not affected in same way by the slopes during the incremental test. The heart rate
and breathing frequency did not differ from the level condition and all the slope gradients at the
ventilatory thresholds or exhaustion. At the same time, the ventilation and oxygen consumption
increased concomitantly with the slope (p < 0.001) in all positions. The post-hoc analysis highlighted
that the ventilation signiﬁcantly increased between each successive gradient (0 to 15%, 15% to 25%
and 25% to 40%), while the oxygen consumption stopped increasing at the 25% gradient. Our results
show that the 25 and 40% gradient slopes allow the specialist trail runners to reach the highest oxygen
consumption level.
Keywords: trail running; exercise physiology; maximal oxygen consumption; performance; testing
1. Introduction
The physiology of running has been largely investigated in the last century to explore
human physiology and performance [1–4]. The bipedal locomotion speed is commonly
used to prescribe an exercise intensity with the aim of analyzing a physiological request [5].
For the purposes of clinical and sports performance, incremental running tests have been
developed to evaluate the maximal cardiorespiratory capabilities [6] to perform clinical
diagnoses or prescribe physical training programs. Such evaluations have been designed
mainly on treadmill machines, allowing an increase in the exercise intensity by adjusting
the speed, slope or both [7,8]. Such testing procedures are massively used in sports science
because they allow the subject to reach the maximum oxygen uptake (
.
VO2max), which
Int. J. Environ. Res. Public Health 2022, 19, 12210. https://doi.org/10.3390/ijerph191912210
https://www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2022, 19, 12210
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is an important contributor to performance in many sports [3,9,10]. These procedures
also allow the determination of physiological landmarks, such as ventilatory thresholds,
that allow the setting of intensity levels during a training program [11,12]. On a level
condition, the protocols designed to assess the
.
VO2max during running could differ, but
may lead to similar
.
VO2max values [13–15] if the progressivity and starting intensity are
appropriately set.
In recent decades, the increase in popularity of trail running races [16] has attracted
interest in uphill and downhill running evaluations, including the
.
VO2max [17–19]. Physio-
logically speaking, the running economy and energy cost of uphill running has been largely
described [2,20–22]. However, few studies have investigated the speciﬁc effect of a slope
on the maximal physiological values, such as the
.
VO2max, during incremental running
tests. The existing literature provides contrasting or opposite results as the studies have
been conducted with different populations and/or testing protocols. The studies using a
constantly increasing slope, [23] or with slopes from +7% to +25% [24–26] did not reported
an alteration in the
.
VO2max with a positive slope, whereas others pointed out an increase
in the
.
VO2max with a slope of up to 35% [27–29]. Hence, based on the current literature, it
is not clear if a slope gradient can induce a signiﬁcant alteration in the cardiopulmonary
variables, especially with well-adapted athletes, such as trail runners, or if an optimal
slope can be identiﬁed to reach the highest cardiorespiratory involvement, without being
impacted by peripheral limitations, such as a lack of muscular force. Speciﬁcally, with trail
runners, Balducci et al.’s or Schöfﬂ et al.’s studies compared the maximal cardiorespiratory
performance while running at 12.5, 16, and 25% on a treadmill and in ecological ﬁeld
situations [24,26]. They reported no signiﬁcant change in the
.
VO2max but a progressive
increase in the ventilation (
.
VE) with the slope. Contrary to this result, Scheer et al. reported
a larger
.
VO2max and blood lactate concentration post-exhaustion (3 min) [28]. However,
the protocol used for this study included a concomitant speed and slope increment during
testing (+0.5 km·h−1 and +1% per minute) and provided a ﬁnal slope of only around a
+10% gradient.
Hence, the aim of this study was to examine the effects of different gradient slopes
(from level to +40%) on the cardiorespiratory variables reached at exhaustion and the
ventilatory thresholds during maximum incremental tests in specialist trail runners. Based
on the previous studies, and especially on the physiological limitations of the
.
VO2max [30],
we hypothesized that the steeper the slope, the higher the
.
VO2max, since a steeper slope
will require a larger muscular mass to elevate the body mass [31,32]. However, we also
hypothesized that this phenomenon would tend to a plateau, so that a further increase in
the slope would not lead to an increase and could lead to a decrease in the
.
VO2, due to the
peripheral limitations.
2. Methodology
2.1. Participants
Fourteen young trail runners, free of injury in the last six months, were involved
in this study, with a training volume (8.4 ± 3.2 h) in last two months: four females (age:
20.2 ± 2.8 years, size 1.73 ± 0.03 m, weight 61 ± 7.1 kg), and ten males (age: 20.6 ± 2.2 years,
size 1.76 ± 0.04 m, weight 65.1 ± 5.2 kg). The measurement period took place in the second
part of the racing season, with no competitions in last two weeks preceding the measure-
ments. All the athletes have more than four years of active practice of trail running, and
the training volumes for both genders are, respectively, 8.7 ± 3 h and 8.9 ± 2.5 h. All the
participants were informed of the design and aim of the study and provided their written
consent to participate in this study. The experiment was conducted in accordance with the
Declaration of Helsinki and received the approval ID-RCB: 2019-A03012-55 from “COMITE
DE PROTECTION DES PERSONNES SUD MEDITERRANEE IV”.
Int. J. Environ. Res. Public Health 2022, 19, 12210
3 of 12
2.2. Experiential Design
All the athletes involved in this study performed, in random order, four incremental
test sessions with different constant slopes. All the sequence possibilities (24 different
randomizations) were assigned to the athletes by a draw, eliminating successive sequences
to avoid each athlete performing a similar sequence. The tests were completed in a period
of two weeks, respecting at least three days of rest after each assessment and avoiding other
strenuous activities. The protocols were designed with 0%, 15%, 25% and 40% positive
slopes in ecological ﬁeld conditions. The level protocol was performed on a track and ﬁeld
loop, whereas the slope protocols were performed on a regular track with a constant slope
in a ski resort. The level protocol starts at 8 km·h−1 and increases by 0.5 km·h−1 every
minute [33]; the 15% slope protocol starts at 3.37 km·h−1 and increases by 0.41 km·h−1; the
25% slope protocol starts at 2 km·h−1 and increases by 0.34 km·h−1; and the 40% protocol
starts at 1.35 km·h−1 and increases by 0.27 km·h−1 (Figure 1). The uphill protocols were
designed, based on previous experiments, in order to reach similar test durations whatever
the slope, in line with the current recommendations [34]. These protocols start at the same
ascending speed (AS) of 500 m per hour and with increments of 50 m per hour for the
15% slope condition, and of 100 m per hour for the 25% and 40% conditions. The speed
control was performed using an audio soundtrack read by a mobile MP3 player. For the
level condition, the pacing was done by a soundtrack reading a sound every 20 m [33].
Regarding the uphill test, the ﬁxed pacing was done every 15 s. To maintain the right speed,
the athlete must be at the ﬂag position when the signal sounds. The test was interrupted
if athletes deviated more than 5 m difference from the appropriate position during two
successive intervals.
Int. J. Environ. Res. Public Health 2022, 19, x  
3 of 13 
 
 
2.2. Experiential Design 
All the athletes involved in this study performed, in random order, four incremental 
test sessions with different constant slopes. All the sequence possibilities (24 different ran-
domizations) were assigned to the athletes by a draw, eliminating successive sequences 
to avoid each athlete performing a similar sequence. The tests were completed in a period 
of two weeks, respecting at least three days of rest after each assessment and avoiding 
other strenuous activities. The protocols were designed with 0%, 15%, 25% and 40% pos-
itive slopes in ecological field conditions. The level protocol was performed on a track and 
field loop, whereas the slope protocols were performed on a regular track with a constant 
slope in a ski resort. The level protocol starts at 8 km·h−1 and increases by 0.5 km·h−1 every 
minute [33]; the 15% slope protocol starts at 3.37 km·h−1 and increases by 0.41 km·h−1; the 
25% slope protocol starts at 2 km·h−1 and increases by 0.34 km·h−1; and the 40% protocol 
starts at 1.35 km·h−1 and increases by 0.27 km·h−1 (Figure 1). The uphill protocols were 
designed, based on previous experiments, in order to reach similar test durations what-
ever the slope, in line with the current recommendations [34]. These protocols start at the 
same ascending speed (AS) of 500 m per hour and with increments of 50 m per hour for 
the 15% slope condition, and of 100 m per hour for the 25% and 40% conditions. The speed 
control was performed using an audio soundtrack read by a mobile MP3 player. For the 
level condition, the pacing was done by a soundtrack reading a sound every 20 m [33]. 
Regarding the uphill test, the fixed pacing was done every 15 s. To maintain the right 
speed, the athlete must be at the flag position when the signal sounds. The test was inter-
rupted if athletes deviated more than 5 m difference from the appropriate position during 
two successive intervals. 
 
Figure 1. Graphical representation of each protocol performed by participants. The grey area repre-
sents the speed in km·h, while the black solid line represents the slope gradient in degrees. Protocol 
designs are displayed from 0° to 40° from left to right. ((A): 0°, (B): 15°, (C): 25° and (D): 40°). 
2.3. Physiological Measurements 
During the incremental testing, the physiological parameters were measured using a 
portable gas exchange system, the Metamax 3B-R2 (Cortex Biophysics, Leipzig, Ger-
many), previously validated by Marcfarlane et al. [35]. This system was installed on par-
ticipants with a vest in a thoracic position and carefully placed on the clavicula to permit 
free arm movement while running. An oronasal face mask (7450 series V2 (HansRudolph, 
Shawnee, KS, USA)) was adjusted on each participant to install a bi-directional digital 
turbine. This turbine measured the respiration flow and obtained the 𝑉ሶ 𝐸 in L.min−1 and 
the breathing frequency (BF) in cycles.min−1. A short sample line tube (0.6 m) collected the 
inspired and expired air between the mask and turbine to measure the O2 and CO2 con-
centrations and calculate the O2 consumption (𝑉ሶ 𝑂ଶ, L·min−1) and CO2 output (𝑉ሶ 𝐶𝑂ଶ 
L·min−1). For each subject, the 𝑉ሶ 𝑂ଶ was normalized and expressed in mL·min−1·kg−1. The 
heart rate (HR) was collected by a thoracic belt strap, the Polar H7 (Polar Electro, 
Kemplele, Finland), and transmitted via Bluetooth Low Energy technology to the gas ex-
change measurement system. For each data collection, the tests were initialized and 
Figure 1. Graphical representation of each protocol performed by participants. The grey area
represents the speed in km·h, while the black solid line represents the slope gradient in degrees.
Protocol designs are displayed from 0◦ to 40◦ from left to right. ((A): 0◦, (B): 15◦, (C): 25◦ and
(D): 40◦).
2.3. Physiological Measurements
During the incremental testing, the physiological parameters were measured using a
portable gas exchange system, the Metamax 3B-R2 (Cortex Biophysics, Leipzig, Germany),
previously validated by Marcfarlane et al. [35]. This system was installed on participants
with a vest in a thoracic position and carefully placed on the clavicula to permit free arm
movement while running. An oronasal face mask (7450 series V2 (HansRudolph, Shawnee,
KS, USA)) was adjusted on each participant to install a bi-directional digital turbine. This
turbine measured the respiration ﬂow and obtained the
.
VE in L.min−1 and the breathing
frequency (BF) in cycles.min−1. A short sample line tube (0.6 m) collected the inspired
and expired air between the mask and turbine to measure the O2 and CO2 concentrations
and calculate the O2 consumption (
.
VO2, L·min−1) and CO2 output (
.
VCO2 L·min−1). For
each subject, the
.
VO2 was normalized and expressed in mL·min−1·kg−1. The heart rate
(HR) was collected by a thoracic belt strap, the Polar H7 (Polar Electro, Kemplele, Finland),
and transmitted via Bluetooth Low Energy technology to the gas exchange measurement
system. For each data collection, the tests were initialized and started from a computer
Int. J. Environ. Res. Public Health 2022, 19, 12210
4 of 12
using MetaSoft Studio© software 5.5.1, and the data were collected into the internal memory
of the portable device. Then, all the data were downloaded with the software to be stored
and analyzed. Before each test, the ﬂow sensor was calibrated with a 3L syringe and the
gas sensors were calibrated with ambient air and the reference gas (15% O2, 5% CO2), as
recommended by the manufacturer.
For each individual test, the MetaSoft Studio© software determined automatically the
maximal physiological values in the highest average of 30 s. During this period (MAX), the
.
VO2max in mL·min−1·kg−1, ventilation (
.
VEmax) in L·min−1, breathing frequency (BFmax),
heart rate (HRmax) were calculated. An experienced examinator determined the positions of
the ventilatory thresholds 1 (VT1) and 2 (VT2) using Wasserman and Beaver’s method [36]
to allow the system to extract following parameters:
.
VO2vt1,
.
VEvt1, BFvt1, HRvt1 and
.
VO2vt2,
.
VEvt2, BFvt2 and HRvt2. The VT1 and VT2 positions were set using the graphical
interface of the MetaSoft Studio© software 5.5.1 displaying the
.
VE/
.
VO2 and
.
VE/
.
VCO2
curves over the time, with averaging every 10 s. The VT1 was set at the ﬁrst increase of
.
VE/
.
VO2 without an increase of
.
VE/
.
VCO2, and the VT2 was set at a concomitant increase
of
.
VE/
.
VO2 and
.
VE/
.
VCO2.
For each tests series with a gradient (15, 25 and 40%), the ascending speed in meters
per hour was calculated and identiﬁed at the VT1, VT2 and the maximum moments.
2.4. Statistic
All the data exported from the MetaSoft Studio© software were merged into a Mi-
crosoft Ofﬁce 365 Excel spreadsheet (Microsoft, Redmond, WA, USA) and computed to
be analyzed with a custom R-Studio algorithm on the desktop software version 1.4.1106
(RStudio PBC, Boston, MA, USA). The descriptive statistics are presented as the mean and
SD for the physiological variables and AS. The normal distribution of all the physiological
variables was conﬁrmed through the Shapiro–Wilk test (p > 0.05) except for the
.
VO2, HR
and
.
VE measurements at the maximum moment on a 0% of slope. A one-way repeated
measures ANOVA with a Bonferroni post-hoc analysis was used to determine the effects of
the slope gradient (0, 15, 25 and 40%) on the physiological variables (HR, BF,
.
VE and
.
VO2)
at speciﬁc time points: the VT1, VT2 and the maximum (MAX). In a second time, similar
procedures were performed for the AS values for the gradient slopes of 15, 25 and 40% for
each moment. The physiological variables not having a normal distribution were analyzed
using the Friedman test to determine the impact of the slope gradient [37]. A post-hoc test
was a paired Wilcoxon signed-rank test with the Bonferroni correction [38].
These analyses were complemented by an effect size estimation using Hedges’ g
(population <16, repeated measures design) [39]. Hedges’ g was also used for the variables
not following a normal distribution. The magnitude thresholds for the effect size were
deﬁned as 0.20, 0.60, 1.20, 2.0 and 4.0 for small, moderate, large, very large and extremely
large correlation coefﬁcients, in accordance with previous recommendations [40].
For this study a p level inferior at 0.05 was considered as signiﬁcant.
3. Results
The durations of the tests were 944.0 ± 115.8 s, 907.6 ± 99.6 s, 900.2 ± 100.2 s and
904.3 ± 101.2 s for the 0, 15, 25 and 40% gradient slopes, respectively, without signiﬁcant
differences between the conditions. The data for each slope and time points (VT1, VT2 and
MAX) are displayed in Table 1. All the individual values, as well as the mean and standard
deviations are displayed as violin plot graphics in Figure 2 to observe the distribution and
changes with the slope conditions. A second violin plots series was designed to show the
AS values for the gradient conditions (Figure 3).
Int. J. Environ. Res. Public Health 2022, 19, 12210
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Int. J. Environ. Res. Public Health 2022, 19, x  
8 of 13 
 
 
 
Figure 2. Violin plot of dependent variables, heart rate (HR), breathing frequency (BF), ventilation 
(𝑉ሶ 𝐸), oxygen consumption (𝑉ሶ 𝑂ଶ) for all time points (VT1, VT2 and MAX) for slope conditions (0, 
Figure 2. Violin plot of dependent variables, heart rate (HR), breathing frequency (BF), ventilation
(
.
VE), oxygen consumption (
.
VO2) for all time points (VT1, VT2 and MAX) for slope conditions (0,
15, 25 and 40%). Statistical differences observed were noted as follow; * p < 0.05, ** p < 0.01 and
*** p < 0.001.
Int. J. Environ. Res. Public Health 2022, 19, 12210
6 of 12
Int. J. Environ. Res. Public Health 2022, 19, x  
9 of 13 
 
 
15, 25 and 40%). Statistical differences observed were noted as follow; * p < 0.05, ** p < 0.01 and *** p 
< 0.001. 
 
Figure 3. Violin plot of ascending speed (AS) at all positions (VT1, VT2 and MAX) for all slope 
conditions (15, 25 and 40%). Statistical differences observed were noted as follow; * p < 0.05, ** p < 
0.01 and *** p < 0.001. 
4. Discussion 
The aim of this study was to investigate the effect of a positive gradient slope on 
cardiopulmonary variables during maximal incremental testing. As hypothesized, we ob-
served that the steeper the slope, the higher the 𝑉ሶ 𝑂ଶ𝑚𝑎𝑥 up to +25%, without a further 
significant increase thereafter. However, we also noticed that not all cardiorespiratory 
variables are equally influenced by the slope gradient increase. 
As expected, our results confirmed an increase in the cardiorespiratory requirements 
while increasing the slope angles. However, not all cardiorespiratory variables were im-
pacted equally. Indeed, we observed that the HR at VT1, VT2 and MAX remained unaf-
fected by the slope gradients from 15% to 40%. This finding at MAX is in line with the 
previous studies [24,26,28,29]. This observation provides an interesting confirmation for 
training purposes and allows the transposition of the HR intensities in the various positive 
slopes when targeting the ventilatory threshold intensity based on the HR values. 
Beyond the HR, the breathing pattern was impacted by the slope gradients. For the 
BF, we noted that no difference was found at the VT1 and VT2 landmarks. However, a 
weak trend was observed at the MAX, highlighting that the greater the slope, the higher 
the BF (p = 0.011) associated with a small effect size between the level condition and the 
+25% and +40% gradient or +15% and the steeper slopes. Moreover, we can observe in 
Figure 2 that the individual BF values are more dispersed for the 25 and 40% slopes. This 
observation is also corroborated with an increased standard deviation, especially at the 
MAX and for 40%. This bigger dispersion of the BF at the 25 and 40% gradients could be 
explained by different running pattern strategies when the slope increases. Indeed, run-
ners can choose to increase cadence and decrease step-length, or vice-versa, [24] and it is 
known that a tight locomotor–respiratory coupling exists, especially while running [41]. 
Moreover this coupling could be exacerbated when the upper limbs are more involved 
[42,43] potentially, or in a more pronounced way, at higher gradients. 
On the other hand, the 𝑉ሶ 𝐸 was largely positively influenced by the increase in the 
slope for the VT1, VT2 and MAX time points. We observed small to moderate effect sizes 
between the conditions, excepting between +25% and 40% at the VT2 and MAX land-
marks, which remained trivial. These results differ from the literature, since Balducci et 
al. did not observe any differences during the incremental running test for the level con-
dition vs. the 15% and the level vs. the 25% slope gradients [24], and Scheer et al. did not 
report any differences between the level test and the test with the constant slope increase 
(1% per minute) [28]. Given that the BF remained largely unchanged, this phenomenon 
Figure 3. Violin plot of ascending speed (AS) at all positions (VT1, VT2 and MAX) for all slope
conditions (15, 25 and 40%). Statistical differences observed were noted as follow; * p < 0.05, ** p < 0.01
and *** p < 0.001.
Table 1. Mean and standard deviation of heart rate (HR), breathing frequency (BF), ventilation (
.
VE),
oxygen consumption (
.
VO2) and ascending speed (AS) for each position; ventilatory thresholds (VT1
and VT2) and at maximum (MAX) for 0, 15, 25, 40% gradient slope conditions. §, Ø and β indicate
that value is signiﬁcantly different than 0%, 15% and 25% gradient slope condition, respectively.
0%
15%
25%
40%
VT1
HR (bpm)
148.3 ± 11.9
150.4 ± 11.4
150.1 ± 11.6
150.4 ± 11.4
BF (cycles·min−1)
44.1 ± 4.8
44.9 ± 4.5
45 ± 5.1
45.3 ± 5.4
VE (L·min−1)
90 ± 5.8 Ø β
98.9 ± 10.8 §
101.6 ± 11.9 §
105.9 ± 12.4 § Ø β
VO2 (mL·min−1·kg)
42 ± 4.2 Ø β
46 ± 6 §
46.9 ± 6.2 §
46.9 ± 6.7 §
AS (m·h−1)
-
807.1 ± 85.1 β
1057.1 ± 126.8
1096.4 ± 135.1 Ø
VT2
HR (bpm)
171.9 ± 8.2
172.4 ± 9.7
171.9 ± 9.1
172.3 ± 8.5
BF (cycles·min−1)
50.9 ± 5
52 ± 5
51.4 ± 5.4
52.6 ± 4.5
VE (L·min−1)
131.9 ± 18.2 β
137 ± 18.8
141.5 ± 17.9 §
144.1 ± 18.1 §
VO2 (mL·min−1·kg)
55.1 ± 6 Ø β
58.6 ± 5 § β
59.9 ± 4.4 §
61 ± 5.6 § Ø
AS (m·h−1)
-
1039.2 ± 163.1 β
1478.5 ± 106.9
1503.5 ± 120 Ø
Max
HR (bpm)
189 ± 7.6
188.7 ± 8.2
188.2 ± 8.1
188.4 ± 7.8
BF (cycles·min−1)
57.1 ± 3.9
57.5 ± 3.6
58.4 ± 4.4
59.1 ± 4.7
VE (L·min−1)
164.5 ± 25.3 Ø β
172.6 ± 24.8 §
177.4 ± 23.6 § Ø
181.5 ± 24.5 § Ø β
VO2 (mL·min−1·Kg)
63.3 ± 7.3 Ø β
66.5 ± 5.9 § β
67.9 ± 5.8 § Ø
68.1 ± 5.9 § Ø
AS (m·h−1)
-
1175 ± 141.1 β
1750 ± 137.2
1771.4 ± 132.6 Ø
The results of the statistical analysis from the repeated one-way ANOVA and Bonfer-
roni post-hoc analysis are displayed in Table 2 for all the physiological variables, whereas
the ascending speed can be read in Table 3. At the VT1, VT2 and MAX time points, the
.
VE,
.
VO2 and AS signiﬁcantly increased with an increase in the slope gradients (p < 0.001),
whereas the HR and BF were not signiﬁcantly affected in any condition. Speciﬁcally, only
the HR (at VT1; signiﬁcantly increased with slopes; p = 0.006) and BF (at MAX; signiﬁcantly
increased with slopes; p = 0.011) were affected. Moreover, the AS showed signiﬁcantly
slower values (p < 0.001) between 15% and the other gradients (25 and 40%) but no differ-
ence was observed at any time points between the 25 and 40% slope gradients (p = 0.999).
Int. J. Environ. Res. Public Health 2022, 19, 12210
7 of 12
Table 2. Results of statistical analysis including Shapiro–Wilk test for normality and p value for
one-way ANOVA and Bonferroni post-hoc analysis comparing heart rate (HR), breathing frequency
(BF), ventilation (
.
VE) and oxygen consumption (
.
VO2) at all positions (VT1, VT2 and MAX) and
between slope conditions. Effect sizes are presented in right part of the table using Hedges’ g method.
Anova One-Way Repeated Measures
Bonferroni Post-Hoc
Effect Size
HR
VT1
Slope
p value
Normality
p value
p value
g Hedges
0%
0.074
Valid
0.006
0%
15%
25%
0%
15%
25%
15%
0.449
Valid
15%
0.22
15%
0.172
25%
0.202
Valid
25%
0.13
0.999
25%
0.142
0.024
40%
0.352
Valid
40%
0.16
0.999
0.999
40%
0.173
0
0.241
VT2
Slope
p value
Normality
p value
p value
g Hedges
0%
0.182
Valid
0.920
0%
15%
25%
0%
15%
25%
15%
0.753
Valid
15%
0.999
15%
0.061
25%
0.806
Valid
25%
0.999
0.999
25%
0.001
0.059
40%
0.771
Valid
40%
0.999
0.999
0.999
40%
0.049
0.015
0.047
MAX
Slope
p value
Normality
p value
p value
g Hedges
0%
0.453
Failed
0.899
0%
15%
25%
0%
15%
25%
15%
0.068
Valid
15%
0.999
15%
0.035
25%
0.72
Valid
25%
0.999
0.999
25%
0.096
0.059
40%
0.287
Valid
40%
0.999
0.999
0.999
40%
0.074
0.034
0.026
BF
VT1
Slope
p value
Normality
p value
p value
g Hedges
0%
0.377
Valid
0.421
0%
15%
25%
0%
15%
25%
15%
0.434
Valid
15%
0.999
15%
0.163
25%
0.444
Valid
25%
0.999
0.999
25%
0.181
0.028
40%
0.3
Valid
40%
0.5
0.5
0.999
40%
0.23
0.083
0.053
VT2
Slope
p value
Normality
p value
p value
g Hedges
0%
0.453
Valid
0.182
0%
15%
25%
0%
15%
25%
15%
0.49
Valid
15%
0.999
15%
0.209
25%
0.107
Valid
25%
0.999
0.999
25%
0.08
0.121
40%
0.054
Valid
40%
0.19
0.999
0.78
40%
0.336
0.117
0.329
MAX
Slope
p value
Normality
p value
p value
g Hedges
0%
0.08
Valid
0.011
0%
15%
25%
0%
15%
25%
15%
0.187
Valid
15%
0.999
15%
0.11
25%
0.586
Valid
25%
0.058
0.666
25%
0.301
0.207
40%
0.913
Valid
40%
0.051
0.064
0.307
40%
0.468
0.382
0.169
VE
VT1
Slope
p value
Normality
p value
p value
g Hedges
0%
0.643
Valid
<0.001
0%
15%
25%
0%
15%
25%
15%
0.49
Valid
15%
0.01
15%
0.994
25%
0.163
Valid
25%
0.008
0.439
25%
1.2
0.232
40%
0.056
Valid
40%
<0.001
<0.001
0.002
40%
1.6
0.591
0.348
VT2
Slope
p value
Normality
p value
p value
g Hedges
0%
0.095
Valid
< 0.001
0%
15%
25%
0%
15%
25%
15%
0.118
Valid
15%
0.569
15%
0.266
25%
0.208
Valid
25%
<0.001
0.205
25%
0.515
0.238
40%
0.119
Valid
40%
<0.001
0.086
0.097
40%
0.651
0.372
0.139
MAX
Slope
p value
Normality
p value
p value
g Hedges
0%
0.186
Failed
<0.001
0%
15%
25%
0%
15%
25%
15%
0.097
Valid
15%
<0.001
15%
0.316
25%
0.193
Valid
25%
<0.001
0.01
25%
0.511
0.189
40%
0.689
Valid
40%
<0.001
0.003
0.036
40%
0.663
0.348
0.167
Int. J. Environ. Res. Public Health 2022, 19, 12210
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Table 2. Cont.
Anova One-Way Repeated Measures
Bonferroni Post-Hoc
Effect Size
VO2
VT1
Slope
p value
Normality
p value
p value
g Hedges
0%
0.398
Valid
<0.001
0%
15%
25%
0%
15%
25%
15%
0.614
Valid
15%
<0.001
15%
0.754
25%
0.409
Valid
25%
<0.001
0.201
25%
0.886
0.136
40%
0.848
Valid
40%
<0.001
0.505
0.999
40%
0.86
0.143
0.010
VT2
Slope
p value
Normality
p value
p value
g Hedges
0%
0.22
Valid
<0.001
0%
15%
25%
0%
15%
25%
15%
0.81
Valid
15%
<0.001
15%
0.588
25%
0.184
Valid
25%
<0.001
0.048
25%
0.898
0.264
40%
0.204
Valid
40%
<0.001
0.001
0.739
40%
0.994
0.43
0.205
MAX
Slope
p value
Normality
p value
p value
g Hedges
0%
0.034
Failed
<0.001
0%
15%
25%
0%
15%
25%
15%
0.749
Valid
15%
<0.001
15%
0.427
25%
0.889
Valid
25%
<0.001
0.042
25%
0.680
0.237
40%
0.482
Valid
40%
<0.001
0.039
0.999
40%
0.712
0.271
0.035
Table 3. Results of statistical analysis including Shapiro–Wilk test for normality and p value for
one-way ANOVA and Bonferroni post-hoc analysis comparing ascending speed (AS) at all positions
(VT1, VT2 and MAX) and between slope conditions 15, 25 and 40%. Effect sizes are presented in right
part of the table using Hedges’ g method.
Anova One-Way Repeated Measures
Bonferroni Post-Hoc
Effect Size
AS
VT1
Slope
p value
Normality
p value
p value
g Hedges
15%
0.655
Valid
<0.001
15%
25%
15%
25%
25%
0.046
Valid
25%
<0.001
25%
2.25
40%
0.036
Valid
40%
<0.001
0.999
40%
2.49
0.291
VT2
Slope
p value
Normality
p value
p value
g Hedges
15%
0.013
Valid
<0.001
15%
25%
15%
25%
25%
0.65
Valid
25%
<0.001
25%
3.09
40%
0.275
Valid
40%
<0.001
0.999
40%
3.15
0.214
Max
Slope
p value
Normality
p value
p value
g Hedges
15%
0.094
Valid
<0.001
15%
25%
15%
25%
25%
0.518
Valid
25%
<0.001
25%
4.01
40%
0.056
Valid
40%
<0.001
0.999
40%
4.23
0.154
4. Discussion
The aim of this study was to investigate the effect of a positive gradient slope on
cardiopulmonary variables during maximal incremental testing. As hypothesized, we
observed that the steeper the slope, the higher the
.
VO2max up to +25%, without a further
signiﬁcant increase thereafter. However, we also noticed that not all cardiorespiratory
variables are equally inﬂuenced by the slope gradient increase.
As expected, our results conﬁrmed an increase in the cardiorespiratory requirements
while increasing the slope angles. However, not all cardiorespiratory variables were
impacted equally. Indeed, we observed that the HR at VT1, VT2 and MAX remained
unaffected by the slope gradients from 15% to 40%. This ﬁnding at MAX is in line with the
previous studies [24,26,28,29]. This observation provides an interesting conﬁrmation for
training purposes and allows the transposition of the HR intensities in the various positive
slopes when targeting the ventilatory threshold intensity based on the HR values.
Beyond the HR, the breathing pattern was impacted by the slope gradients. For the BF,
we noted that no difference was found at the VT1 and VT2 landmarks. However, a weak
trend was observed at the MAX, highlighting that the greater the slope, the higher the BF
Int. J. Environ. Res. Public Health 2022, 19, 12210
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(p = 0.011) associated with a small effect size between the level condition and the +25% and
+40% gradient or +15% and the steeper slopes. Moreover, we can observe in Figure 2 that
the individual BF values are more dispersed for the 25 and 40% slopes. This observation
is also corroborated with an increased standard deviation, especially at the MAX and for
40%. This bigger dispersion of the BF at the 25 and 40% gradients could be explained by
different running pattern strategies when the slope increases. Indeed, runners can choose
to increase cadence and decrease step-length, or vice-versa, [24] and it is known that a
tight locomotor–respiratory coupling exists, especially while running [41]. Moreover this
coupling could be exacerbated when the upper limbs are more involved [42,43] potentially,
or in a more pronounced way, at higher gradients.
On the other hand, the
.
VE was largely positively inﬂuenced by the increase in the
slope for the VT1, VT2 and MAX time points. We observed small to moderate effect sizes
between the conditions, excepting between +25% and 40% at the VT2 and MAX landmarks,
which remained trivial. These results differ from the literature, since Balducci et al. did
not observe any differences during the incremental running test for the level condition vs.
the 15% and the level vs. the 25% slope gradients [24], and Scheer et al. did not report
any differences between the level test and the test with the constant slope increase (1% per
minute) [28]. Given that the BF remained largely unchanged, this phenomenon can only be
explained by an increase in the tidal volume with an increasing slope to increase the air
volume exchange at each breathing cycle. Similar ﬁnding have been reported by Lemire
et al., comparing uphill and downhill to an incremental level running test [18]. In the same
way, these authors also observed a higher metabolic coupling of ventilation when running
uphill at 15% [18]. Moreover, the
.
VE and tidal volume have already been demonstrated to
be higher at the maximal intensity (>80% maximum) during an incremental test with a slope
gradient compared to the level condition [27], or in a ﬁeld test performed at 16% compared
with the treadmill test at 1% [26]. Here again, the hypothesis of locomotor–respiratory
coupling could potentially explain the mechanisms. Potentially, the slope gradient led to a
reduction of the step frequency [24,44] at a similar intensity and could allow the use of a
deeper breathing pattern with increased tidal volume.
Finally, we observed that the
.
VO2 was higher during uphill running compared to the
slope gradients for the VT1, VT2 and MAX time points. Amongst the different positive
slopes, we noticed that, at VT1, no signiﬁcant differences were found between the 15% and
25% (p = 0.201) and between the 25% and 40% gradients (p = 0.999). Both the VT2 and MAX
time points provided the same pattern, with a signiﬁcant increase in the
.
VO2 between 15%
and 25% (p < 0.001 with a small effect size), while no differences were found between 25%
and 40% (p = 0.739 and 0.999) These results corroborated the previous ﬁndings comparing
the
.
VO2max between the level condition and the various slopes conditions [27–29,31,45,46].
Nevertheless, it is important to notice that these previous studies focused on a smaller
slope gradient (7%). Moreover, differences in the studied populations could be reported
as the previous studies were conducted without specialist trail runners [25] or with older
and heavier athletes [24,26]. In these studies, the athletes’ ages were 38.5 ± 6.4 years and
42.8 ± 14.6 years, respectively, whereas the were 20.4 ± 2.3 years in our study, and the
body weights were 69.8 ± 8.6 kg and 75.8 ± 10.2 kg vs. 63.9 ± 5.8 kg in our study.
The main mechanism that could explain an increase in the
.
VO2 while running uphill
is likely the higher muscular mass involved in this condition, especially for the vastus,
soleus, gluteus, biceps femoris and gastrocnemius muscles [31,32,47–49]. In addition, uphill
running over a 15% gradient eliminates the bouncing mechanism and the use of elastic
energy, which is helpful for displacement [22,50,51]. The locomotion related to uphill
running induces stronger muscular contractions and mechanical works [52]. To produce
this additional mechanical energy, Robert and Belliveau concluded the involvement of a
greater contribution of ankle, knee and hip extensor muscles in line with Sloniger et al. or
Swanson and Caldwell’s work [31,32]. In addition, a greater hip extensors’ contribution has
an additional effect on the metabolic expenditure, because theses muscles are not able to
Int. J. Environ. Res. Public Health 2022, 19, 12210
10 of 12
produce force economically with a low contribution of elastic storage and recovery [53,54].
Gottschall and Kram reported an increase of 75% in the propulsive force during treadmill
running at a 9% slope compared to a level condition [55]. Basically, more important
propulsive work induces additional concentric muscle contraction levels, which are most
costly physiologically [21].
Furthermore, even if our result indicates a positive inﬂuence of the slope on the
.
VO2
at the VT1, VT2 and MAX time points, we can also underline that the 40% gradient does
not produce signiﬁcantly greater
.
VO2 max values compared to the 25%, while the
.
VEmax is
superior on this gradient. Based on this ﬁnding, we can exclude ventilatory limitation in
this condition to produce a higher oxygen consumption. We can hypothesis a higher O2
extraction, transportation or utilization in muscles as limiting factors at steep grades [30].
In addition, this result provides an interesting insight to evaluate trail runner specialists.
Indeed, based on this result, we can recommend the evaluation of the
.
VO2max capacity of
trail runners on slope conditions at or over 25% to obtain their real maximal capacities,
which has been highly correlated with performance levels for short and middle-distance
trail-running competitions [56].
Finally, our study investigated the maximal AS for the VT1, VT2 and MAX time points
and for different slope conditions (15, 25 and 40%). Our results provided similar ﬁndings
for all the time points; the 15% gradient provided a systematically lower AS than 25%
(p < 0.001) and 40% (p < 0.001), with a very large effect size. We also noted that the AS
did not differ between 25 and 40%, whatever the time points considered (p = 0.999). This
observation is very interesting for training purposes and may allow using ascending speeds
as intensity indexes during sessions. Moreover, this information provides new evidence for
athletes intending to compete in maximal elevation challenges, where the goal is to reach
the highest elevation in an allocated duration (from 4 to 24 h). In our study, the slopes
between 25 and 40% allowed the achievement of a greater ascending speed (approx. 1750 m
per hour) than the 15% gradient (approx. 1175 m per hour) and could be selected for such
contests based on the individual’s capabilities.
5. Conclusions
The aim of this study was to investigate the effect of different gradient slopes (from
level to +40%) on the cardiorespiratory variables reached at exhaustion and ventilatory
thresholds during maximum incremental tests in specialist trail runners. First, our study
clearly indicates that slope conditions over a 15% gradient allow reaching higher
.
VO2 and
.
VE levels at the VT1, VT2 and MAX time points, whereas the BF and HR remain unchanged
for the specialist trail runners. Our study also pointed out a limitation of the slope inﬂuence
on the physiological variables over the 25% gradient, whereas the
.
VO2 does not further
increase at the VT1, VT2 and MAX time points. Finally, an analysis of the speed provides
similar ﬁndings. Our study pointed out that the maximal AS can be reached for slopes of
25% and 40% equally. Based on these results, we recommend trail runner testing on slope
conditions between 25 and 40% to stress and reach their real maximal cardiorespiratory
capacities and obtain their maximal AS for training purposes.
Author Contributions: Conceptualization, G.D. and J.C.; methodology, G.D., L.M. and J.C.; software,
A.G.; investigation, G.D. and M.C.; writing—original draft preparation, J.C.; writing—review and
editing, J.C., M.C., A.G., G.D. and L.M. supervision, G.D., J.C. and L.M.; project administration, L.M.
All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: The experiment was conducted in accordance with the
Declaration of Helsinki and received the approval ID-RCB: 2019-A03012-55 from “COMITE DE
PROTECTION DES PERSONNES SUD MEDITERRANEE IV”.
Conﬂicts of Interest: The authors declare no conﬂict of interest.
Int. J. Environ. Res. Public Health 2022, 19, 12210
11 of 12
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