RESEARCH ARTICLE
Examination of gas exchange and blood
lactate thresholds in Paralympic athletes
during upper-body poling
Julia Kathrin BaumgartID1*, Maaike Moes2, Knut Skovereng1, Gertjan EttemaID1,
Øyvind Sandbakk1
1 Centre for Elite Sports Research, Department of Neuroscience and Movement Science, Faculty of
Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway,
2 Department of Human Movement Sciences, Faculty of Health, Medicine and Life Sciences, Maastricht
University, Maastricht, The Netherlands
* jk.baumgart@gmail.com
Abstract
Objectives
The primary aim was to compare physiological and perceptual outcome parameters identi-
fied at common gas exchange and blood lactate (BLa) thresholds in Paralympic athletes
while upper-body poling. The secondary aim was to compare the fit of the breakpoint models
used to identify thresholds in the gas exchange thresholds data versus continuous linear
and curvilinear (no-breakpoint) models.
Methods
Fifteen elite Para ice hockey players performed seven to eight 5-min stages at increasing
workload until exhaustion during upper-body poling. Two regression lines were fitted to the
oxygen uptake (VO2)-carbon dioxide (VCO2) and minute ventilation (VE)/VO2 data to deter-
mine the ventilatory threshold (VT), and to the VCO2-VE and VE/VCO2 data to determine
the respiratory compensation threshold (RCT). The first lactate threshold (LT1) was deter-
mined by the first rise in BLa (+0.4mmolL-1 and +1.0mmolL-1) and a breakpoint in the log-
log transformed VO2-BLa data, and the second lactate threshold (LT2) by a fixed rise in BLa
above 4mmolL-1 and by employing the modified Dmax method. Paired-samples t-tests were
used to compare the outcome parameters within and between the different threshold meth-
ods. The fit of the two regression lines (breakpoint model) used to identify thresholds in the
gas exchange data was compared to that of a single regression line, an exponential and a
3rd order polynomial curve (no-breakpoint models) by Akaike weights.
Results
All outcome parameters identified with the VT (i.e., breakpoints in the VO2-VCO2 or VE/VO2
data) were significantly higher than the ones identified with a fixed rise in BLa (+0.4 or
+1.0mmolL-1) at the LT1 (e.g. BLa: 5.1±2.2 or 4.9±1.8 vs 1.9±0.6 or 2.3±0.5mmolL-1,
p<0.001), but were not significantly different from the log-log transformed VO2-BLa data
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OPEN ACCESS
Citation: Baumgart JK, Moes M, Skovereng K,
Ettema G, Sandbakk Ø (2018) Examination of gas
exchange and blood lactate thresholds in
Paralympic athletes during upper-body poling.
PLoS ONE 13(10): e0205588. https://doi.org/
10.1371/journal.pone.0205588
Editor: Tiago M Barbosa, Nanyang Technological
University, SINGAPORE
Received: February 19, 2018
Accepted: September 17, 2018
Published: October 31, 2018
Copyright: © 2018 Baumgart et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
files.
Funding: The laboratory equipment was provided
by NeXt Move, Norwegian University of Science
and Technology (NTNU). NeXt Move is funded by
the Faculty of Medicine at NTNU and Central
Norway Regional Health Authority. The funder had
no role in study design, how the data collection and
analysis was performed, decision to publish, or
preparation of the manuscript.
(4.3±1.6mmolL-1,p>0.06). The outcome parameters identified with breakpoints in the
VCO2-VE data to determine the RCT (e.g. BLa: 5.5±1.4mmolL-1) were not different from the
ones identified with the modified Dmax method at the LT2 (5.5±1.1mmolL-1) (all p>0.53), but
were higher compared to parameters identified with VE/VCO2 method (4.9±1.5mmolL-1)
and a fixed BLa value of 4mmolL-1 (all p<0.03). Although we were able to determine the VT
and RCT via different gas exchange threshold methods with good fit in all 15 participants
(mean R2>0.931), the continuous no-breakpoint models had the highest probability (>68%)
of being the best models for the VO2-VCO2 and the VCO2-VE data.
Conclusions
In Paralympic athletes who exercise in the upper-body poling mode, the outcome parame-
ters identified at the VT and the ones identified with fixed methods at the LT1 showed large
differences, demonstrating that these cannot be used interchangeably to estimate the aero-
bic threshold. In addition, the close location of the VT, RCT and LT2 does not allow us to dis-
tinguish the aerobic and anaerobic threshold, indicating the presence of only one threshold
in athletes with a disability exercising in an upper-body mode. Furthermore, the better fit of
continuous no-breakpoint models indicates no presence of clear breakpoints in the gas
exchange data for most participants. This makes us question if breakpoints in the gas
exchange data really exist in an upper-body exercise mode in athletes with disabilities.
Introduction
In able-bodied endurance athletes performing lower-body or whole-body exercise, gas
exchange and blood lactate (BLa) threshold concepts are well-established in the diagnosis of
endurance performance as well as in the prescription of systematic training with different exer-
cise intensity zones [1]. Two thresholds are commonly described in the literature: 1) The aero-
bic threshold (AT)–determined by the ventilatory threshold (VT) or the first lactate threshold
(LT1)–separates low- from moderate-intensity exercise [2, 3]. 2) The anaerobic threshold
(ANT)–determined by the respiratory compensation threshold (RCT) or the second lactate
threshold (LT2)–separates moderate- from high-intensity exercise [2, 3]. However, to what
extent the outcome parameters identified at the VT and LT1 as well as the RCT and LT2 coin-
cide in Paralympic sitting sport athletes who exercise in an upper-body mode remains to be
investigated.
Various methods have been employed to determine the VT and the RCT, as well as the LT1
and the LT2 [3–6]. The VT is based on a disproportionate increase (i.e. a breakpoint) in carbon
dioxide production (VCO2) and minute ventilation (VE) in relation to oxygen uptake (VO2)
[3, 7], and the LT1 on an onset in BLa concentration above resting levels that marks the begin-
ning of exercise [5] or on a breakpoint in the log-log transformed VO2-BLa data [4]. Even
though these physiological changes occur above the VT and LT1, the body is still able to main-
tain equilibrium at intensities up to the ANT, and aerobic metabolism (indicated by measure-
ments of oxygen uptake and the corresponding energy equivalent) reflects overall energy
expenditure [2]. The ANT marks the point beyond which any attempt of the body to maintain
metabolic equilibrium at a constant rate of work fails [6]. The RCT is based on a dispropor-
tionate increase (i.e. a breakpoint) of VE in relation to VCO2 [3], a mechanism that has been
suggested to correspond with the point where BLa starts to accumulate with constant workload
Gas exchange and blood lactate thresholds in upper-body poling
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Competing interests: The authors have declared
that no competing interests exist.
[6]. In contrast, it has been argued that the changes in gas exchange with increasing work rate
are continuous transitions where fatigue gradually accumulates rather than clear breakpoints
[8].
The assumption that the VT corresponds with the LT1, and the RCT with the LT2, are
based on the initial studies by Beaver et al. [3] and Wassermann et al. [6, 9, 10] from the
1980’s. However, there has been a continuous debate around the existence of and the physio-
logical link between these different thresholds [2, 11–14]. Although physiological parameters
identified at the VT and LT1, and at the RCT and LT2 have shown high correlations in able-
bodied participants during cycling and running in some studies [15, 16], others find low corre-
lations [17]. In wheelchair basketball and wheelchair rugby athletes with a spinal cord injury,
the % of VO2peak was lower at the LT1 compared to the VT, whereas it did not significantly dif-
fer at the LT2 and RCT [18]. In contrast, in able-bodied swimmers, there were no significant
differences in physiological outcome parameters at the LT1 and the VT [19].
Whereas a range of studies have investigated the VT during upper-body exercise in able-
bodied participants and participants with a disability [20–29], knowledge is limited on whether
gas exchange and BLa threshold concepts can be used interchangeably in athletes with disabili-
ties who exercise in an upper-body mode, or whether breakpoints exist in the gas exchange
data of these athletes. Therefore, the primary aim of this study was to compare physiological
and perceptual outcome parameters at the gas exchange and BLa thresholds in the data
obtained from Paralympic athletes while upper-body poling. The secondary aim was to com-
pare the fit of breakpoint models used to identify gas exchange thresholds with continuous lin-
ear or curvilinear (no-breakpoint) models.
Methods
Participants
Fourteen male and one female endurance-trained Norwegian Para ice hockey players partici-
pated in this study. Anthropometrics and training hours per month of the participants are
depicted in Table 1. All participants were healthy and free of injuries at the time of testing. The
study was approved by the Norwegian Data Protection Authority and conducted in accor-
dance with the Declaration of Helsinki. All participants signed an informed consent form
prior to voluntarily take part in the study, and were made aware that they could withdraw
from the study at any point without providing an explanation.
Experimental design
The testing consisted of two consecutive test days at similar test times, during which partici-
pants performed an incremental test to exhaustion on day one, followed by seven to eight
5-min stages at gradually increasing effort for each stage until exhaustion on day two. All tests
were performed in upper-body poling on a Concept2 ski ergometer 1 (Concept2, Inc., Morris-
ville, USA, http://www.concept2.com/service/skierg/skierg-1), while sitting in an ice sledge
hockey seat.
Test set-up
After being equipped with an oro-nasal mask (Hans Rudolph Inc, Kansas City, MO, USA) and
a heart rate monitor (Polar Electro Inc., Port Washington, NY, USA), the participants were
tightly strapped around the thighs and hips into an ice sledge hockey seat that was mounted on
a wooden platform (Fig 1). The distance of the seat to the Concept2 ski ergometer and the
position of the feet depended on personal preference but was the same for test day one and
Gas exchange and blood lactate thresholds in upper-body poling
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two. The ski ergometer uses wind resistance, which is generated by the spinning flywheel. The
ski ergometer has a spiral damper with settings from one to ten, which works like a gearing
system. We had this damper set at “eight” for all participants. Power output was measured
with the ergometer’s software, which was previously validated with force and velocity measure-
ments using a force cell (Noraxon USA inc., Scottsdal, AZ, USA) and the Oqus cameras of the
Qualisys motion capture system (Qualisys AB, Gothenburg, Sweden) as described by Hegge
et al. [30]. The Metamax II ergospirometer CORTEX Biophysik GmbH, Leipzig, Germany)
was calibrated against a known mixture of gases (16% O2 and 4% CO2) and ambient air prior
to the testing procedure of every second participant. Before each athlete was tested, the flow
transducer was calibrated with a 3 L syringe and then connected to the oro-nasal mask, which
allowed for the measurement of breath-by-breath respiratory parameters.
Test protocol
The participants were instructed to refrain from heavy training and alcohol consumption 24
hours before, caffeine intake the day of, and food intake two hours before testing. Additionally,
the participants were instructed to void their bladder directly before arriving at the laboratory.
A questionnaire was filled out on each of the two test days to monitor if the participants fol-
lowed these instructions, as well as to exclude any prior illness or injury that might have inter-
fered with the testing.
Test day one. A standardized warm-up of five 5-min submaximal stages with a 2- to
3-min break between stages was performed in the upper-body poling mode at an overall rating
of perceived exertion (RPE) of 7 (very light), 9 (very light), 11 (light), 13 (somewhat hard) and
15 (hard). Next to serving as a warm-up, the submaximal stages were used to familiarize the
participants with the use of the Borg scale [31] to indicate RPE after the incremental test and
Table 1. Sex, age, anthropometric and disability characteristics as well as monthly training hours of the 15 Norwegian national team Para ice hockey players partici-
pating in this study.
Sex
Age
(years)
Body mass
(kg)
Height
(cm)
Disability
(level of injury)
Training hrs/month
1
Male
53
83.3
186
Paraplegia (Th12-L1)
25
2
Male
18
75.7
160
Spina bifida (L5)
49
3
Male
27
61.0
160
Athrogryposis multiplex congenita
63
4
Male
31
69.4
184
Hereditary spastic paraplegia
45
5
Male
28
90.0
173
Paraplegia (Th10)
26
6
Male
21
70.4
164
Spina bifida (ns)
59
7
Male
33
70.5
160
Spina bifida (Th12)
67
8
Male
34
75.3
173
Paraplegia (Th11-12)
48
9
Female
22
70.0
167
Spina bifida (L3-S1)
33
10
Male
22
63.4
164
Paraplegia (Th11-12)
28
11
Male
18
64.2
154
Spina bifida (ns)
54
12
Male
20
68.0
186
Paraplegia (Th12)
40
13
Male
20
77.0
163
Cerebral Palsy (motor only)
23
14
Male
28
66.5
173
Amputation (single leg above the knee)
80
15
Male
32
63.2
165
Paraplegia (ns)
56
Mean ± SD
27.1±8.9
71.2±8.0
170±10
-
47±18
 Players are from the Norwegian national B-team
All other players are from the Norwegian national A-team.
Thoracic (Th), lumbar (L), sacral (S), not specified (ns)
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Fig 1. Test set-up. The participants were strapped in around the hips and thighs in an ice sledge hockey seat mounted
on a platform in front of the Concept2 ski-ergometer.
https://doi.org/10.1371/journal.pone.0205588.g001
Gas exchange and blood lactate thresholds in upper-body poling
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each of the 5-min stages on day two. After a 5-min break, the incremental test started at the
individual power output of the third submaximal stage (rounded to the nearest 10-point
value), and participants were instructed to continuously increase power output by 10 W every
30 s. The test was terminated when the participant, despite strong verbal encouragement,
could no longer maintain the required power output of the 30-s stage and the VO2 values
either plateaued or decreased (a drop of more than 2 mLkg-1min-1). After the incremental
test, participants recovered passively for five min and actively for three min (at the power out-
put of the first submaximal stage). They then performed a verification stage at a 10% higher
power output than the peak power output of the incremental test (rounded to the nearest
10-point value) to verify the attainment of a true VO2peak [32]. The verification stage was ter-
minated when the participant dropped more than 10% of target power output for more than
five s.
Test day 2. Seven to eight 5-min stages were performed with a 2- to 3-min break between
stages and in the same upper-body poling mode. The first stage started at 20% of the individual
peak power output obtained during the incremental test on day one, with increases of 10% (of
the individual peak power output) for each consecutive stage. The last stage was terminated
when the participant, despite strong verbal encouragement, could no longer maintain the
power output of that stage and dropped more than 10% in the target power output for longer
than five s. The intermittent exercise protocol was chosen to take a BLa sample from the fin-
gertip in between stages. The duration of five min per stage was chosen, since in an upper-
body mode two to three min are needed to achieve steady-state of physiological outcome
parameters [33].
Outcome measurements
Heart rate was measured every second with a Polar heart rate monitor, and respiratory param-
eters (i.e., VO2, VCO2, VE, and respiratory exchange ratio (RER)) were measured breath-by-
breath and averaged over 10 s by the in-built software of a Metamax II. A blood sample was
taken from the fingertip and BLa analysed with a Lactate Pro device (Arkray Inc., Japan) at
rest and directly after each of the submaximal stages on day one and day two, and one and
three min after the incremental test and the verification stage on day one as well as the last
stage of day two. Overall RPE was recorded after each of the submaximal stages on day one
and two, as well as after the incremental test on day one and the last stage on day two. Power
output was displayed per stroke and saved as 20-s averages during the submaximal stages on
day one and day two by the in-built Concept2 software (Concept2, Morrisville, VT, USA).
Peak power output during the incremental test and during the verification stage was registered
as the highest 30-s average.
Data analysis
Data processing.
Peak power output and gas exchange outcome parameters were calcu-
lated as the highest 30-s moving average and peak heart rate (HRpeak) as the highest 3-s moving
average of the incremental test performed on test day one. The gas exchange, heart rate and
power output data of the last two min (12 x 10-s averages) of each complete 5-min stage
conducted on test day two was included for data analysis in MATLAB (R2016a; Mathworks
Inc., Natick, MA). The analyses in the following were based on the concatenated 2-min gas
exchange data for the VT and RCT and on the BLa values after each 5-min stages for the LT1
and LT2.
Different methods were used to determine both the VT and the RCT, as well as the LT1 and
the LT2. For the determination of the VT, VO2 was plotted against VCO2 (V-slope method)
Gas exchange and blood lactate thresholds in upper-body poling
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[3] as well as time against VE/VO2 and VE/VCO2 (ventilatory equivalent method) [7] and two
regression lines fit to the data. For a valid detection of the VT with the ventilatory equivalent
method, the VE/VO2 had to increase before an increase in VE/VCO2 [15, 34]. For the detec-
tion of the RCT, VCO2 was plotted against VE [3] and two regression lines fit to the data. The
LT1 was determined in two different ways: the first fixed rise in BLa concentration by 0.4 and
1 mmolL-1 above the lowest individual BLa value [5, 35]. Additionally, the LT1 was deter-
mined by breakpoints in the log-log transformed VO2-BLa relationship [4]. The LT2 was
determined by a fixed BLa concentration of 4 mmolL-1 [36]. Additionally, the LT2 was deter-
mined by the modified Dmax method, which identifies the point on the 3rd order polynomial
curve fitted to the BLa values that yields the maximal perpendicular distance to the straight
line formed by the first stage with an increase of 0.4 mmolL-1 and the BLa measured after the
last stage [5]. Outcome parameters (% of peak power output, % of VO2peak, % of HRpeak, as
well as BLa and RPE) were interpolated at the thresholds identified with each of the above
described methods used to determine the VT, LT1, RCT and LT2.
Statistical analyses.
Paired-samples t-tests were used to compare the physiological and
perceptual outcome parameters within the VT, LT1, RCT and LT2, and between all four differ-
ent thresholds. Pearson’s r was used to investigate relationships between the outcome parame-
ters identified with the different methods used to determine VT, LT1, RCT and LT2. Ranges of
0.26–0.49, 0.50–0.69, 0.70–0.89 and 0.90–1.0 were used to indicate low, moderate, high and
very high correlations according to Munro’s criteria [37]. An α level of 0.05 was used to indi-
cate statistical significance.
To compare the fit of breakpoint models versus continuous linear or curvilinear (no-break-
point) models to the gas exchange data, two regression lines (Eq 1) versus a single linear
regression line (Eq 2), an exponential curve (Eq 3), and a 3rd order polynomial curve (Eq 4)
were fitted to the VO2-VCO2, VE/VO2, VE/VCO2, and VCO2-VE data by linear least squares
fitting.
y ¼
a1 þ b1 x; t < k
a2 þ b2 x; t  k
(
ð1Þ
y ¼ a þ bx
ð2Þ
y ¼ a þ c  exp
x þ g
d


ð3Þ
y ¼ a þ b1 x þ b2 x2 þ b3 x3
ð4Þ
y is the variable of interest, a the y-axis offset, b the slope coefficients, c and d spreading coeffi-
cients, g the x-axis offset and k the point where the first and the second regression line of the
piecewise function cross. To compare the fit of the four models, the Akaike information crite-
rion (AIC) (Eq 5) [38] and the Akaike weights (wi) (Eq 7) for each model i relative to the set of
R candidate models were calculated based on the delta AIC (Δi) (Eq 6) [39, 40].
AIC ¼ n  log
SSer
n


þ 2  K
ð5Þ
Delta AIC ¼ Di ¼ AICi AIC weight ¼ wi ¼
exp or LT1 (+1.0) (exception: power output and BLa at LT1 (+0.4): r>0.55, p<0.04; all other out-
come parameters: r<0.38, p>0.16) (S1 File, sheet “correlations”). All outcome parameters at
LT1 (+0.4) and LT1 (+1.0) were highly or very highly correlated (all r>0.83, p<0.001). In addi-
tion, some of the outcome parameters identified with breakpoints in the log-log transformed
VO2-BLa moderately correlated with the outcome parameters identified by the V-slope
method (HR: r = 0.64, p = 0.01; BLa: r = 0.54, p = 0.04) and the breakpoints in the VE/VO2
data of the ventilatory equivalent method (HR: r = 0.54, p = 0.04).
The outcome parameters identified with breakpoints in the VCO2-VE data at the RCT (e.g.
BLa: 5.5±1.4 mmolL-1) were not significantly different from the ones identified with the modi-
fied Dmax method at the LT2 (5.5±1.1 mmolL-1) (all p>0.53), but were higher compared to
parameters identified with VE/VCO2 method (4.9±1.5 mmolL-1) and a fixed BLa value of 4
mmolL-1 (all p<0.03). Furthermore, there was no significant difference between the outcome
parameters identified with V-slope method used to determine the VT and the ones identified
with breakpoints in the VE/VCO2 and VCO2-VE data used to determine the RCT (p>0.22).
However, most outcome parameters identified at the breakpoints in the VE/VO2 and VE/
VCO2 data (ventilatory equivalent method) were highly or very highly correlated with those
identified at the breakpoints in the VCO2-VE data (RCT) (exception: % of VO2peak r = 0.67,
p = 0.006; all other outcome parameters: r>0.73, p<0.01) (Fig 2). In addition, most outcome
parameters identified at the thresholds in the VE/VCO2 data were moderately to highly corre-
lated with the same outcome parameters at the thresholds identified with the modified Dmax
method (exception: % of peak power output: r = 0.43, p = 0.11; all other outcome parameters:
r>0.57, p<0.03). Furthermore, there was no significant difference between the outcome
parameters identified with the log-log transformed VO2-BLa method used to determine
the LT1 and at a fixed BLa concentration of 4 mmolL-1 used to determine the LT2 and (all
p>0.43).
For the gas exchange data, all fitting procedures for the VO2-VCO2 and the VCO2-VE
plots, including the single linear regression line, showed very good fit on the data for all 15
participants (mean r2>0.97) (Table 3). However, the fit of the breakpoint model compared to
the continuous no-breakpoint models on the VO2-VCO2 and the VCO2-VE data was only bet-
ter among five participants. Accordingly, the continuous no-breakpoint models had 71% and
68% probability of being the best models for the VO2-VCO2 and the VCO2-VE data, respec-
tively (Table 4). Exemplary VO2-VCO2 and VCO2-VE plots are illustrated in Figs 3 and 4,
respectively.
In the gas exchange data displayed in the VE/VO2 plots and the VE/VCO2 plots, the break-
point model fitted better than the continuous no-breakpoint models in six and seven of the
athletes, respectively (Fig 5). Accordingly, it is unclear if in general the breakpoint (41 and
Table 2. Mean ± SD (95% CI) peak power output and peak physiological and perceptual outcome parameters.
Peak values
Peak power output (W)
144 ± 37 (125–163)
VO2peak (mLkg-1min-1)
36 ± 7 (32–39)
HRpeak (beatsmin-1)
188 ± 12 (182–194)
Blood lactate (mmolL-1)
14.4 ± 1.5 (13.7–15.2)
RPE (6–20)
19.7 ± 0.5 (19.4–19.9)
The data was collected during an incremental test to exhaustion while upper-body poling of 15 Norwegian Para ice
hockey players.
Peak oxygen uptake (VO2peak), peak heart rate (HRpeak), rating of perceived exertion (RPE)
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47%, respectively) or continuous no-breakpoint (59 and 53%, respectively) models fit the VE/
VO2 and the VE/VCO2 data best (Table 4). The rise in VE/VO2 occurred earlier than the VE/
VCO2 only in four athletes (S1 Fig). The VT detection by the VE/VO2 relationship was, there-
fore, only valid in these four athletes. In none of these four athletes, did the breakpoint model
fit the VE/VO2 data better than the continuous no-breakpoint models.
Discussion
The main aim of this study was to compare physiological and perceptual outcome parameters
identified with common gas exchange and BLa thresholds methods used to determine the VT,
LT1, RCT and LT2 in Paralympic athletes while upper-body poling. Furthermore, we com-
pared the fit of breakpoint models used to determine gas exchange thresholds to the fit of con-
tinuous linear or curvilinear (i.e., no-breakpoint) models. The LT1 occurred at much lower
exercise intensity than the VT although both are used as indicators of AT, whereas there were
no or minor differences between the methods used to identify the RCT and LT2 that deter-
mine the ANT. Furthermore, the RCT and LT2 did not differ from the VT. In addition, the
outcome parameters corresponding to the LT1 and LT2 using the log-log transformed VO2-
BLa data and the modified Dmax method, respectively, were significantly higher than ones
identified with fixed BLa values at the LT1 and LT2 (i.e., rise in BLa of +0.4/1.0 at LT1 or BLa
concentration of 4 mmolL-1 at LT2). We were able to determine breakpoints at the VT and
RCT with different gas exchange methods with good fit in all 15 participants, although contin-
uous no-breakpoint models showed even better fit for the majority of participants.
The physiological and perceptual outcome parameters identified with a fixed rise in BLa at
the LT1 were significantly lower than the ones at the VT, and the outcome parameters using
these methods only low or moderately correlated with each other. Overall, this indicates that
these two thresholds cannot be used interchangeably to determine the AT. In addition,
Table 4. Akaike weights (wi) representing a measure of strength of evidence for probability of best fit of the two regression lines (breakpoint model) and the single
regression line, exponential and 3rd order polynomial curve (continuous no-breakpoint models) (mean wi ± SD (95% CI) [# of participants with better fit of the
respective model compared to the two regression lines]) fitted to the gas exchange data of 15 elite Para ice hockey players following a protocol with stepwise
increases in workload every 5 min while upper-body poling.
Two regression lines
Single regression line
Exponential curve
3rd order polynomial curve
VO2-VCO2 plots
0.29 ± 0.35 (0.11–0.46)
0.07 ± 0.18 (-0.03–0.16) [#0]
0.03 ± 0.10 (-0.01–0.08) [#0]
0.61 ± 0.37 (0.42–0.79) [#10]
VE/VO2 plots
0.41 ± 0.45 (0.18–0.64)
0.00 ± 0.00 (0.00–0.00) [#0]
0.13 ± 0.24 (0.01–0.26) [#2]
0.46 ± 0.40 (0.25–0.66) [#7]
VE/VCO2 plots
0.47 ± 0.49 (0.22–0.72)
0.00 ± 0.00 (0.00–0.00) [#0]
0.09 ± 0.19 (-0.01–0.19) [#2]
0.44 ± 0.43 (0.22–0.66) [#6]
VCO2-VE plots
0.31 ± 0.44 (0.09–0.54)
0.00 ± 0.00 (0.00–0.00) [#0]
0.00 ± 0.01 (0.00–0.01) [#0]
0.68 ± 0.44 (0.46–0.91) [#10]
Oxygen uptake (VO2), carbon dioxide production (VCO2), minute ventilation (VE)
https://doi.org/10.1371/journal.pone.0205588.t004
Table 3. The coefficient of determination (mean r2 ± SD (range) for the two regression lines (breakpoint model) and the single regression line, exponential and 3rd
order polynomial curve (continuous no-breakpoint models) fitted to the gas exchange data of 15 elite Para ice hockey players following a protocol with stepwise
increases in workload every 5 min while upper-body poling.
Two regression lines
Single regression line
Exponential curve
3rd order polynomial curve
VO2-VCO2 plots
0.995 ± 0.005 (0.993–0.998)
0.994 ± 0.005 (0.991–0.996)
0.993 ± 0.005 (0.991–0.996)
0.996 ± 0.005 (0.993–0.998)
VE/VO2 plots
0.931 ± 0.069 (0.896–0.966)
0.764 ± 0.094 (0.716–0.811)
0.919 ± 0.064 (0.886–0.951)
0.932 ± 0.064 (0.900–0.964)
VE/VCO2 plots
0.940 ± 0.044 (0.918–0.962)
0.700 ± 0.142 (0.628–0.772)
0.920 ± 0.044 (0.898–0.942)
0.940 ± 0.041 (0.919–0.961)
VCO2-VE plots
0.995 ± 0.003 (0.994–0.997)
0.968 ± 0.015 (0.960–0.976)
0.992 ± 0.006 (0.989–0.994)
0.996 ± 0.003 (0.994–0.998)
Oxygen uptake (VO2), carbon dioxide production (VCO2), minute ventilation (VE)
https://doi.org/10.1371/journal.pone.0205588.t003
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Fig 3. Exemplary VO2-VCO2 plots. The VO2-VCO2 data was fitted with a single regression line, a bilinear regression
line, an exponential curve, and a 3rd order polynomial curve for an athlete without breakpoint (the four plots to the
left) and with suggested breakpoint presence (the four plots to the right). (Note that the plots of the five athletes with a
suggested breakpoint also show a rather linear increase in the VO2-VCO2 relationship). Oxygen uptake (VO2), carbon
dioxide production (VCO2).
https://doi.org/10.1371/journal.pone.0205588.g003
Gas exchange and blood lactate thresholds in upper-body poling
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Fig 4. Exemplary VCO2-VE plots. The VCO2-VE data was fitted with a single regression line, a bilinear regression
line, an exponential curve, and a third order polynomial curve for an athlete without breakpoint (the four plots to the
left) and with suggested breakpoint presence (the four plots to the right). (Note that the plots of the five athletes with a
suggested breakpoint show a rather curvilinear increase in the VCO2-VE relationship). Carbon dioxide production
(VCO2), minute ventilation (VE).
https://doi.org/10.1371/journal.pone.0205588.g004
Gas exchange and blood lactate thresholds in upper-body poling
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Fig 5. Exemplary VE/VO2 and VE/VCO2 plots. Exemplary VE/VO2 data fitted with a bilinear regression line and a
3rd order polynomial curve for an athlete without breakpoint (upper two plots to the left) and with suggested
breakpoint presence (upper two plots to the right). Exemplary VE/VCO2 data fitted with a bilinear regression line and
a 3rd order polynomial curve for an athlete without breakpoint (lower two plots to the left) and with suggested
breakpoint presence (upper two plots to the right). Oxygen uptake (VO2), carbon dioxide production (VCO2), minute
ventilation (VE).
https://doi.org/10.1371/journal.pone.0205588.g005
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thresholds identified by a fixed BLa increase at the LT1 were significantly lower compared
with the breakpoints identified in the log-log transformed VO2-BLa data, showing that indi-
vidually adjustable BLa methods did not correspond with fixed methods in determining the
LT1. The early occurrence of a rise in BLa in upper-body exercise is in accordance with Beneke
et al. [41], who found BLa to be higher at a given workload in activities involving smaller mus-
cle mass, where power output per kg of active muscle mass and, thus, local metabolic stress is
increased compared to lower body exercise. In addition, BLa accumulation after cessation of
exercise was shown to be faster in individuals with a spinal cord injury as compared to able-
bodied individuals [42]. However, although outcome parameters identified with breakpoints
in the log-log transformed VO2-BLa data are not significantly lower than the ones identified
at the VT, outcome parameters identified with methods using fixed BLa values to identify the
LT1 are much lower than the VT.
As estimates of the ANT, the outcome parameters identified with the Dmax method to deter-
mine LT2 did not significantly differ from the ones identified with breakpoints in the VCO2-
VE data at the RCT, whereas most of the outcome parameters identified with breakpoints in
the VE/VCO2 data were significantly lower than these. However, the outcome parameters
identified by the latter method differ only marginally from the two other ANT methods
(VCO2-VE, Dmax), indicating that the exercise intensity where a disproportionate increase in
BLa and in VE occurs is relatively similar. Note that we decided to not correct for multiple
comparisons and rather present the uncorrected p-values from paired samples t-tests instead.
Although we are aware of the subsequent increased chances of making a type 1 errors, the
decreased chances of making a type a type 2 errors were regarded more important, which is in
accordance with Rothman [43]. However, if Bonferroni corrections would have been used in
this specific case, there would have been no significant differences between the outcome mea-
sures identified at with these three methods.
Furthermore, most of the outcome parameters identified with the different methods at the
LT2 and RCT are low to moderately correlated, coinciding with high individual variation in
the outcome parameters within each of the methods used to identify the LT2 and RCT. This
indicates that an individual with a high LT2 does not necessarily display a high RCT. The high
individual variation may be explained by disability-related differences in the cardio-respiratory
system that might affect physiological responses to upper-body exercise. For example, athletes
with a spinal cord injury exercising in an upper-body mode were shown to vary considerably
in their VO2peak depending on their level of injury [44], which might also reflect differences
in the % of VO2peak that can be sustained during exercise. In addition, the inclusion of one par-
ticipant that was much older than the rest and one female participant may have contributed
to the high variation. Furthermore, individual variation in physiological responses may be
higher in upper-body exercise compared to lower-body exercise. Altogether, it is questionable
whether the similar outcome parameters identified at the LT2 and the RCT on a group basis,
result in similar outcome parameters at the LT2 and RCT for the individual sitting athlete
when training in an upper-body mode.
The thresholds identified by the breakpoints in the VE/VO2 at the VT and in VE/VCO2 at
the RCT did not significantly differ and were highly correlated. This, together with the rather
linear increase in the VO2-VCO2 relationship suggests that it is solely the disproportionate rise
in VE that leads to a rather rapid increase in the data of the VE/VO2 and the VE/VCO2 plots,
and to discernible breakpoints in approximately half of the participants. Together with the
close location of the breakpoints identified in the VCO2-VO2 data at the VT and the VCO2-
VE data at the RCT, this indicates that a two-phase (low-high) rather than a three-phase (low-
moderate-high) intensity zone model could be applicable in athletes with a disability who exer-
cise in an upper-body mode. This is in contrast to significant differences between the VT and
Gas exchange and blood lactate thresholds in upper-body poling
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the RCT in Dekerle et al. [45], who test able-bodied participants in the arm crank ergometry
mode, and Leicht et al. [18], who tested wheelchair athletes in the wheelchair treadmill mode.
However, our findings are in line with a study of Pires et al. [46], who also found one rather
than two thresholds in the gas exchange data in upper-body trained able-bodied participants
during exercise in the arm crank ergometry mode. Whether the discrepancies between studies
are related to employment of e.g. different populations, protocols or exercise modes needs to
be examined further in other experimental designs.
All gas exchange threshold methods have in common that there is an a priori assumption of
the presence of a breakpoint, defined as “a place where an interruption or change occurs” [47].
However, the presence or absence of breakpoints in the gas exchange data is a debated topic
[8, 12]. Thus, in addition to the breakpoint models used to identify the VT and the RCT in the
present study, we fitted continuous no-breakpoint models to the data to investigate if there are
clear breakpoints in our data. Here, we found good fit for the breakpoint model used to iden-
tify the gas exchange thresholds, but better fit for the curvilinear no-breakpoint models in
most cases. We, hence, question if clear breakpoints really exist in the gas exchange data of ath-
letes with disabilities in an upper-body exercise mode.
Conclusion
In Paralympic athletes who exercise in upper-body poling, the physiological and perceptual
outcome parameters identified at the VT and the LT1 showed large differences, which demon-
strates that these cannot be used interchangeably to identify the AT. In addition, the close loca-
tion of the VT, RCT and LT2 does not allow us to distinguish the AT and ANT, indicating that
there might only be one threshold in athletes with a disability exercising in an upper-body
mode. Furthermore, continuous no-breakpoint models fit the gas exchange data better than
breakpoint models in most participants. We, hence, question if clear breakpoints in the gas
exchange data really exist in an upper-body exercise mode in athletes with disabilities.
Supporting information
S1 File. Data. Data and analyses conducted in this study of gas exchange and blood lactate
threshold in Paralympic sitting athletes.
(XLSX)
S1 Fig. VE/VO2 and VE/VCO2 plots fitted with two regression lines. The data is of the six or
seven completed stages of each of the 15 athletes. Breakpoint presence is indicated above each
individual plot. Furthermore, it is indicated in the second row above the figures whether the
two thresholds occur at the same time, or the VE/VO2 occurs before or after the VE/VCO2
threshold. Oxygen uptake (VO2), carbon dioxide production (VCO2), minute ventilation (VE).
(TIF)
Acknowledgments
The laboratory equipment was provided by NeXt Move, Norwegian University of Science and
Technology (NTNU). NeXt Move is funded by the Faculty of Medicine at NTNU and Central
Norway Regional Health Authority. The funder had no role in study design, how the data
collection and analysis was performed, decision to publish, or preparation of the manuscript.
The authors acknowledge the support of the Olympic and Paralympic Centre in Oslo and the
Centre for Elite Sports Research in Trondheim in conducting this research. The eager partici-
pation of the athletes is deeply appreciated. None of the authors have any conflicts of interest
to declare.
Gas exchange and blood lactate thresholds in upper-body poling
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Author Contributions
Conceptualization: Julia Kathrin Baumgart, Maaike Moes, Knut Skovereng, Gertjan Ettema,
Øyvind Sandbakk.
Data curation: Julia Kathrin Baumgart, Maaike Moes.
Formal analysis: Julia Kathrin Baumgart, Knut Skovereng, Gertjan Ettema, Øyvind Sandbakk.
Funding acquisition: Øyvind Sandbakk.
Investigation: Julia Kathrin Baumgart, Øyvind Sandbakk.
Methodology: Julia Kathrin Baumgart, Maaike Moes, Knut Skovereng, Gertjan Ettema,
Øyvind Sandbakk.
Project administration: Julia Kathrin Baumgart, Øyvind Sandbakk.
Supervision: Gertjan Ettema, Øyvind Sandbakk.
Validation: Julia Kathrin Baumgart, Gertjan Ettema, Øyvind Sandbakk.
Visualization: Julia Kathrin Baumgart, Gertjan Ettema.
Writing – original draft: Julia Kathrin Baumgart.
Writing – review & editing: Maaike Moes, Knut Skovereng, Gertjan Ettema, Øyvind
Sandbakk.
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Examination of gas exchange and blood lactate thresholds in Paralympic athletes during upper-body poling.
Baumgart, Julia Kathrin,Moes, Maaike,Skovereng, Knut,Ettema, Gertjan,Sandbakk, Øyvind