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Higher rate of fat oxidation during rowing compared with cycling ergometer exercise across a range of exercise intensities: Fat oxidation during rowing vs cycling

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The relative contribution of carbohydrate and fat oxidation to energy expenditure during exercise is dependent on variables including exercise intensity, mode, and recruited muscle mass. This study investigated patterns of substrate utilization during two non-weightbearing exercise modalities, namely cycling and rowing. Thirteen young, moderately trained males performed a continuous incremental (3-min stages) exercise test to exhaustion on separate occasions on an electronically braked cycle (CYC) ergometer and an air-braked rowing (ROW) ergometer, respectively. On two further occasions, participants performed a 20-min steady-state exercise bout at ∼50%VO2peak on the respective modalities. Despite similar oxygen consumption, rates of fat oxidation (FATox ) were ∼45% higher during ROW compared with CYC (P < 0.05) across a range of power output increments. The crossover point for substrate utilization occurred at a higher relative exercise intensity for ROW than CYC (57.8 ± 2.1 vs 42.1 ± 3.6%VO2peak , P < 0.05). During steady-state submaximal exercise, the higher FATox during ROW compared with CYC was maintained (P < 0.05), but absolute FATox were 42% (CYC) and 28% (ROW) lower than during incremental exercise. FATox is higher during ROW compared with CYC exercise across a range of exercise intensities matched for energy expenditure, and is likely as a consequence of larger muscle mass recruited during ROW. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
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Higher rate of fat oxidation during rowing compared with
cycling ergometer exercise across a range of exercise intensities
B. Egan1,2, D. T. Ashley3, E. Kennedy3, P. L. O’Connor3,4, D. J. O’Gorman3,5
1Institute for Sport & Health, University College Dublin, Dublin, Ireland, 2Institute of Food & Health, School of Public Health,
Physiotherapy & Population Science, University College Dublin, Dublin, Ireland, 3School of Health & Human Performance, Dublin
City University, Dublin, Ireland, 4Exercise and Health Sciences Division, Central Michigan University, Mount Pleasant, Michigan,
USA, 5Centre for Preventive Medicine, Dublin City University, Dublin 9, Ireland
Corresponding author: Donal J. O’Gorman, PhD, School of Health and Human Performance, Dublin City University, Glasnevin,
Dublin 9, Ireland. Tel: +353 (0)1 7008060, Fax: +353 (0)1 7008888, E-mail: donal.ogorman@dcu.ie
Accepted for publication 28 April 2015
The relative contribution of carbohydrate and fat oxida-
tion to energy expenditure during exercise is dependent
on variables including exercise intensity, mode, and
recruited muscle mass. This study investigated patterns
of substrate utilization during two non-weightbearing
exercise modalities, namely cycling and rowing. Thirteen
young, moderately trained males performed a continuous
incremental (3-min stages) exercise test to exhaustion on
separate occasions on an electronically braked cycle
(CYC) ergometer and an air-braked rowing (ROW)
ergometer, respectively. On two further occasions, par-
ticipants performed a 20-min steady-state exercise bout
at 50%VO2peak on the respective modalities. Despite
similar oxygen consumption, rates of fat oxidation
(FAT ox) were 45% higher during ROW compared with
CYC (P<0.05) across a range of power output incre-
ments. The crossover point for substrate utilization
occurred at a higher relative exercise intensity for ROW
than CYC (57.8 ±2.1 vs 42.1 ±3.6%VO2peak,P<0.05).
During steady-state submaximal exercise, the higher
FATox during ROW compared with CYC was maintained
(P<0.05), but absolute FATox were 42% (CYC) and 28%
(ROW) lower than during incremental exercise. FATox is
higher during ROW compared with CYC exercise across
a range of exercise intensities matched for energy expen-
diture, and is likely as a consequence of larger muscle
mass recruited during ROW.
Rowing combines intense dynamic movement of most of
the major muscle groups of the body with a requirement
for large force production during each stroke at high
intensities of exercise. While rowing as a sport requires
skill and considerable time invested to master the tech-
nique (Hagerman, 1984; Soper & Hume, 2004), indoor
rowing ergometer exercise is safe, relatively easy to
learn, and effective for rehabilitation and improving
aerobic fitness (Hagerman, 1984). The recruitment of a
relatively large proportion of muscle mass compared
with activities like cycling can result in higher energy
expenditure during exercise (Hagerman et al., 1988;
Zeni et al., 1996; Moyna et al., 2001). Several studies
have investigated a range of physiological parameters in
response to rowing compared with cycling in partici-
pants ranging from novice to elite to elderly (Hagerman
et al., 1988; Szal & Schoene, 1989; Zeni et al., 1996;
Beneke et al., 2001; Moyna et al., 2001), but none have
compared the metabolic responses and rates of substrate
utilization to these exercise modes.
A myriad of intrinsic biochemical factors influence
the relative contributions of fat and carbohydrate to
energy expenditure during exercise (Spriet & Watt,
2003; Brooks, 2012), but extrinsic factors such as the
intensity and mode of exercise are important regulators
of substrate utilization (Romijn et al., 1993; van Loon
et al., 2001; Achten et al., 2003; Knechtle et al., 2004).
The contribution of fat to energy expenditure is greatest
during low- and moderate-intensity exercise but
declines thereafter (Romijn et al., 1993; van Loon et al.,
2001). The maximal rate of fat oxidation typically
occurs between 45% and 65% of peak oxygen con-
sumption (VO2peak), and this intensity has been termed
“FATmax” (Achten et al., 2002). FATmax on an individual
basis is influenced by training and nutrition status,
gender, and the mode of exercise (Achten &
Jeukendrup, 2003a, 2004; Achten et al., 2003; Venables
et al., 2005). Because of the deleterious effects of
ectopic fat deposition on the function of liver and skel-
etal muscle (Savage et al., 2007), and the causal role of
skeletal muscle insulin resistance in numerous lifestyle-
related chronic diseases (Wolfe, 2006), there is increas-
ing interest in the prescription of exercise specifically
around an intensity that maximizes fat oxidation
(Achten & Jeukendrup, 2004; Brun et al., 2012;
O’Hagan et al., 2013).
630
Scand J Med Sci Sports 2016: 26: 630–637
doi: 10.1111/sms.12498
ª2015 John Wiley & Sons A/S.
Published by John Wiley & Sons Ltd
When comparing exercise modes, running elicits a
greater rate of fat oxidation (FATox) compared with
cycling across a wide range of exercise intensities, a
finding that has been attributed to the weight-bearing
nature and greater quantity of muscle mass recruited
while running (Achten et al., 2003; Knechtle et al.,
2004; Capostagno & Bosch, 2010). For individuals with
obesity and type 2 diabetes, it is important to identify a
mode of exercise that can safely and effectively maxi-
mize energy expenditure, but because of complications
such as peripheral neuropathy or degenerative arthritis,
these individuals require alternative modes of exercise
that are non-weightbearing (Colberg et al., 2010). Like
cycling, rowing is a non-weightbearing mode of exer-
cise, but the recruitment of a markedly greater propor-
tion of the body’s muscle mass may positively affect
FATox during exercise. Therefore, the primary aim of this
study was to compare the pattern of substrate utilization
and FATox over a range of intensities during cycling and
rowing ergometer exercise using the FATmax protocol
(Achten et al., 2002). We hypothesized that FATox would
be greater during rowing compared with cycling at the
same relative intensities of exercise. Additionally,
because the validity of this protocol has been questioned
based on the use of incremental 3-min stages (Bordenave
et al., 2007), a secondary aim of this study was to
compare FATox observed during incremental exercise to
steady-state submaximal exercise.
Methods
Experimental design
Thirteen healthy male, moderately trained club-standard rowers
participated in this study: age, 23.2 ±1.6 years; height,
1.82 ±0.02 m; body mass, 77.0 ±1.6 kg; body mass index,
23.2 ±0.3 kg/m2; body fat, 9.1 ±1.2%; lean body mass,
69.9 ±1.3 kg. All participants had a rowing training history of at
least 2 years, and were completing at least 1.5 h per week of
cycling as part of their overall training plan. The participants
performed an incremental exercise test to exhaustion on two sepa-
rate occasions in random order; once on a cycle ergometer (CYC;
VO2peak, 55.7 ±1.6 mL/kg/min) and once on a rowing ergometer
(ROW; VO2peak, 57.5 ±1.5 mL/kg/min), in order to measure rates
of substrate oxidation over a wide range of exercise intensities
(Achten et al., 2002, 2003). Two further exercise tests were sub-
sequently performed in random order, once on each ergometer, at
an intensity corresponding to 50%VO2peak of the respective mode.
Because of time commitments external to the study, only 9 of the
13 participants completed this second phase of the study. This
study was approved by the Dublin City University Research Ethics
Committee, and was performed in accordance with the Declara-
tion of Helsinki. Each participant provided written informed
consent after explanation of the experimental procedures.
Pre-test preparation
Participants were familiarized with all equipment and procedures
prior to the commencement of testing. All tests were performed
between 07:30 and 10:00 h (ambient temperature 19 °C), and par-
ticipants performed subsequent tests at the same time as their first
test. Pre-test preparation was the same for each visit. Participants
were asked to abstain from caffeine and alcohol and refrain from
strenuous exercise for 24 h prior to testing, and all testing took
place after an overnight (8 to 10 h) fast. Participants were asked
to keep a one day portion estimate food diary on the day prior to
the first day of testing, which was scanned and emailed to partici-
pants 48 h prior to each subsequent visit after which they were
asked to repeat this pattern of intake on the day preceding each
test. During the first visit, body composition was estimated from
skinfold thickness measurements using a Harpenden skinfold
caliper at seven sites (Jackson & Pollock, 1978), and body mass
(to nearest 0.1 kg) and height (to nearest 0.01 m) were measured
using a digital scales and wall-mounted stadiometer, respectively.
Incremental exercise tests
The incremental exercise tests were based on the method of
Achten et al. (2002) for determining the intensity (FATmax) elicit-
ing maximal rate of fat oxidation. Briefly, on an electronically
braked cycle ergometer (Ergoline 900, SensorMedics, Yorba
Linda, California, USA) or air-braked rowing ergometer (Model C
Indoor Rower, Concept II, Nottingham, UK), participants began
exercise at 95 W and the power output was increased by 35 W
every 3 min thereafter until volitional fatigue. A minor modifica-
tion was required during ROW such that participants maintained
the required exercise intensity by keeping the average power
output at the target value. At the end of each 3-min stage, the
ergometer monitor was reset to clear the average power output of
the previous stage. The wind vanes were adjusted to set the coef-
ficient of drag at 130 (as per Irish Amateur Rowing Association
protocol). The order of these tests was randomized, and each was
separated by 7 or 14 days.
Immediately prior to each test, an indwelling catheter
(Insyte-W 20/22G, Becton Dickinson, Franklin Lakes, New
Jersey, USA) for serial blood sampling was introduced into an
antecubital vein for CYC, or a superficial forearm vein for ROW.
During the last 20 s of each stage, a blood sample (3 mL) was
collected in a pre-chilled vacutainer (FX Plus, Becton Dickinson)
for measurement of plasma lactate (YSI 2300 Stat Plus, Yellow
Springs Instruments, Ohio, USA), and heart rate (Vantage, Polar
Electro, Kempele, Finland) and rating of perceived exertion (RPE)
were recorded at the same time.
Submaximal exercise tests
On two separate days in random order, participants completed a
submaximal exercise test at 50%VO2peak on each ergometer. In
each submaximal test, participants exercised for 20 min. During
the last 30 s of each 5-min period, HR and RPE were recorded
(data not shown). During the last 15 s of the 20-min bout, a blood
sample was taken from the indwelling catheter for measurement of
plasma lactate. Each of these tests was undertaken at least 7 days
after the last incremental exercise test. The power output required
to elicit this target oxygen uptake was interpolated based on the
linear relationship between oxygen uptake (y-axis) and power
output (x-axis). On the day prior to each submaximal test, partici-
pants performed a brief exercise bout to verify the power output
corresponding to the intensity to be used in the subsequent test.
This verification session involved 15 min of exercise at exercise
intensities approximating to 50% VO2peak.
Calculations of substrate utilization
Expired air was collected continuously throughout each exercise
test, and breath-by-breath measurements were performed using a
Vmax 29C gas analysis system (SensorMedics, Yorba Linda, Cali-
fornia, USA). Average values for VO2and VCO2were calculated
during the last 2 min of each 3-min stage in the incremental tests
631
Fat oxidation during rowing vs cycling
as described by the established determination of FATmax protocol
(Achten et al., 2002), and during the last 10 min of the 20 min
submaximal tests. The rate (g/min) of carbohydrate and fat oxida-
tion (CHOox and FATox, respectively) and energy expenditure
during each stage were calculated (Jeukendrup & Wallis, 2005).
The percentage contribution of carbohydrate and fat to total energy
expenditure during exercise was also calculated (Kuo et al., 2005).
A comparison of oxidation rates measured during steady-state
submaximal exercise to oxidation rates predicted based on gas
exchange data collected during the incremental tests was based on
linear regression of the relationship between oxidation rate
(y-axis) and oxygen uptake (x-axis) recorded during the incremen-
tal exercise tests.
Statistical analysis
Data were evaluated using GraphPad Prism 6 (GraphPad Soft-
ware, Inc., San Diego, California, USA), and are presented as
mean ±SEM. Two-way (mode ×time) repeated measures analysis
of variance were used to determine differences between the two
modes of exercise for variables with serial measurements, for
example, VO2, VCO2,%W
max, HR, RER, and lactate. On the
incremental exercise tests, there were two sub-analyses performed
on the data using this approach; the first as a comparison of
responses at the same power output (W), and the second as a
comparison of responses at the same relative intensity (%VO2peak).
The latter was possible by comparing each stage in ROW with the
next power output increment in CYC, that is, ROW stage 1 (95 W)
vs CYC stage 2 (130 W), ROW stage 2 (130 W) vs CYC stage 3
(165 W), because at these power outputs, VO2and %VO2peak were
similar between modes (Table 1). When a main effect of exercise
mode, or an interaction effect between exercise mode and time,
was indicated, post-hoc tests of pair-wise comparisons were per-
formed using the Student–Newman–Keuls test. Apaired t-test was
used to compare differences between modes for variables with
single measurements. The significance level was set at α=0.05 for
all statistical tests.
Results
Physiological responses to incremental exercise
VO2, VCO2, and HR were all higher (P<0.05) during
ROW compared with CYC at all power outputs
(Table 1), but VO2peak and HRmax were similar for ROW
and CYC (4.49 ±0.20 vs 4.36 ±0.18 L/min; 188 ±3vs
189 ±3 bpm, respectively). Wmax, calculated from the
power output of last completed stage plus the fraction of
time spent in the final non-completed stage multiplied by
the power output increment (Jeukendrup et al., 1996),
tended to be higher in CYC (331 ±9vs352±15 W,
P=0.098) and peak lactate levels tended to be higher in
ROW (12.3 ±0.8 vs 10.6 ±0.5 mM, P=0.057). VO2
was 0.35 to 0.65 L/min higher at each stage during
ROW, and therefore, expressed as a percentage of
VO2peak, the relative exercise intensity was higher at all
power outputs during ROW (P<0.05; Table 1).
However, when comparing each stage in ROW with the
next power output increment in CYC, that is, ROW stage
1 (95 W) vs CYC stage 2 (130 W), ROW stage 2
(130 W) vs CYC stage 3 (165 W), and so on, VO2and
%VO2peak were similar between modes (Table 1). Hence,
it was possible to compare each dependent variable
between CYC and ROW in terms of power output (W)
and relative exercise intensity (%VO2peak) and compari-
sons are referred to such. For instance, RER was similar
at the same power output in CYC and ROW but was
significantly lower during ROW for all time points when
matched for relative exercise intensity (P<0.05;
Table 1). The relative power output (%Wmax) was higher
during ROW (P<0.05) each power output increment
>165 W, but when compared as a function of relative
exercise intensity, %Wmax was higher during CYC
(P<0.05; Table 1).
Substrate utilization during incremental CYC and
ROW exercise
CHOox increased and FATox decreased progressively with
each increment in power output (Fig. 1). The highest
FATox during exercise was 45% higher in ROW
Table 1. Physiological responses, as a function of power output, during incremental exercise on cycling (CYC) and rowing (ROW) ergometers
Power output (W)
95 130 165 200 235 270 305
%VO2peak CYC 35 ±144±253±263±273±282±290±4
ROW 42 ±1* 53 ±1* 63 ±2* 75 ±2* 84 ±2* 92 ±2* 98 ±1*
%Wmax CYC 28 ±139±248 ±258 ±268 ±378 ±386 ±3
ROW 29 ±141±151±2* 61 ±2* 72 ±2* 83 ±3* 90 ±2*
VO2(L/min) CYC 1.49 ±0.05 1.89 ±0.06 2.27 ±0.06 2.70 ±0.07 3.14 ±0.09 3.54 ±0.13 3.98 ±0.22
ROW 1.85 ±0.08* 2.35 ±0.09* 2.82 ±0.09* 3.35 ±0.11* 3.73 ±0.13* 4.08 ±0.15* 4.39 ±0.16*
VCO2(L/min) CYC 1.22 ±0.05 1.65 ±0.06 2.06 ±0.06 2.51 ±0.08 3.04 ±0.10 3.59 ±0.12 4.01 ±0.25
ROW 1.48 ±0.08* 2.03 ±0.08* 2.50 ±0.10* 3.08 ±0.10* 3.61 ±0.12* 4.21 ±0.13* 4.69 ±0.13*
RER CYC 0.82 ±0.01 0.88 ±0.010.90 ±0.010.93 ±0.010.97 ±0.011.01 ±0.021.04 ±0.02
ROW 0.80 ±0.02 0.86 ±0.01 0.89 ±0.01 0.92 ±0.01 0.97 ±0.02 1.04 ±0.02 1.07 ±0.01
HR (bpm) CYC 102 ±3 115 ±4 130 ±4 144 ±4 158 ±4 170 ±4 179 ±4
ROW 109 ±3* 124 ±3* 137 ±3* 153 ±4* 165 ±4* 175 ±3* 184 ±3*
Data presented as mean ±SEM, n= 13.
*P<0.05, CYC vs ROW at same power output (W).
P<0.05, CYC vs ROW at same relative intensity (%VO2peak).
%VO2peak, percentage peak oxygen uptake; %Wmax, percentage of maximal power output; HR, heart rate; RER, respiratory exchange ratio; VCO2, carbon
dioxide production; VO2, oxygen uptake.
632
Egan et al.
compared with CYC (0.71 ±0.05 vs 0.49 ±0.04 g/min,
P<0.05) and occurred in the first stage of both the CYC
and ROW tests (95 W). With respect to the comparison
of oxidation rates at the same relative intensity, that is, as
a function of %VO2peak, despite a similar rate of oxygen
consumption and whole-body energy expenditure, FATox
was higher during ROW at the same relative intensity
throughout a range of submaximal exercise intensities
between 43% and 84%VO2peak (Fig. 1), commensurate
with higher CHOox during CYC. The relative contribu-
tion of fat to energy expenditure was greater across the
range of exercise intensities (Fig. 2). Additionally, the
crossover point, that is, the exercise intensity after which
carbohydrate oxidation predominates for energy provi-
sion (Brooks & Mercier, 1994), occurred at lower rela-
tive exercise intensity during CYC (42.1 ±3.6% VO2peak)
compared with ROW (57.8 ±2.1% VO2peak,P<0.05).
Compared as a function of relative exercise intensity,
there was no effect of exercise mode on plasma lactate
concentrations (Fig. 3), but concentrations were higher
during ROW compared with CYC (P<0.05) at 270 W
(7.45 ±1.30 vs 5.38 ±0.86 mM, P<0.05) and 305 W
(8.94 ±1.22 vs 6.96 ±0.89 mM, P<0.05).
Substrate utilization during submaximal
steady-state exercise
During the steady-state submaximal exercise tests,
no difference occurred between the exercise modes in
terms of relative exercise intensity (46.1 ±1.5% vs
Fig. 1. Rates of carbohydrate (a) and fat (b) oxidation as a
function of exercise intensity during incremental cycling (CYC)
or rowing (ROW) ergometer exercise. Values are presented as
mean ±SEM. *P<0.05, CYC vs ROW. %VO2peak, peak oxygen
uptake.
Fig. 2. Relative contribution of carbohydrate and fat to energy
expenditure during incremental cycling (CYC) and rowing
(ROW). Values are presented as mean ±SEM. *P<0.05, CYC
vs ROW. %VO2peak, peak oxygen uptake.
Fig. 3. Plasma lactate concentrations as a function of exercise
intensity during incremental cycling (CYC) or rowing (ROW)
ergometer exercise. Values are presented as mean ±SEM.
%VO2peak, peak oxygen uptake.
633
Fat oxidation during rowing vs cycling
48.4 ±1.5%VO2peak), VO2(1.98 ±0.08 vs 2.08 ±0.13 L/
min) or plasma lactate concentration (1.20 ±0.17 vs
1.03 ±0.13 mM; all CYC vs ROW, respectively). The
pattern for higher FATox observed for ROW compared
with CYC during incremental exercise was maintained
during the submaximal exercise test (Table 2). This
was equivalent to 43% higher FATox during ROW
(0.43 ±0.05 vs 0.30 ±0.02 g/min, P<0.05). This
reflected a lower RER value recorded during ROW
(0.88 ±0.01 vs 0.91 ±0.01, P<0.05). Therefore, the
contribution of fat to energy expenditure (Fig. 4) was
greater in ROW (42.3 ±2.8%) compared with CYC
(31.6 ±2.2%, P<0.05). Despite a similar pattern of sub-
strate utilization during the submaximal exercise test, the
absolute values for FATox were markedly lower com-
pared with incremental exercise (Table 2). Based on
values predicted by linear regression of gas analysis data
recorded during incremental exercise, FATox during
steady-state exercise was 42% lower for CYC and 28%
lower for ROW (both P<0.05 for steady-state vs pre-
dicted). These data reflect higher VCO2, and hence
higher RER, values during the submaximal exercise bout
than predicted based on the incremental data (Table 2).
Discussion
The present study compared patterns of substrate utili-
zation during two non-weightbearing modes of exercise,
namely cycling and rowing, over a range of exercise
intensities. The principal finding is that FATox is higher
during rowing compared with cycling exercise eliciting
similar rates of oxygen consumption during incremental
exercise based on the FATmax protocol (Achten et al.,
2002). The higher FATox observed during rowing was
maintained during submaximal exercise, but in agree-
ment with others (Bordenave et al., 2007), this protocol
resulted in an overestimation of the absolute FATox value
observed during steady-state exercise.
Exercise intensity and duration are the major determi-
nants of substrate utilization during exercise (Romijn
et al., 1993; Brooks & Mercier, 1994; van Loon et al.,
2001), but the influence of exercise mode is less well-
described. Comparisons of different exercise modes can
be problematic when there are large inter-mode differ-
ences between VO2resulting in greater energy expendi-
ture at the same relative exercise intensity. Alternatively,
normalizing exercise intensity to an individual’s lactate
threshold for each exercise mode has been proposed
(Baldwin et al., 2000; Arkinstall et al., 2001). Despite no
differences in VO2peak between rowing and cycling, VO2
for each power output increment during rowing was
higher than cycling, as reported by others (Hagerman
et al., 1988; Zeni et al., 1996; Moyna et al., 2001).
However, in the present study, energy expenditure and
plasma lactate concentration did not differ as a function
of the relative exercise intensity in either the incremental
or submaximal exercise tests.
Several studies have compared physiological
responses to rowing and cycling (Hagerman et al., 1988;
Szal & Schoene, 1989; Zeni et al., 1996; Beneke et al.,
2001; Moyna et al., 2001), but none have investigated
differences, if any, in substrate utilization. We report that
FATox is higher during rowing compared with cycling
exercise at the same rate of energy expenditure across a
range of exercise intensities up to 85%VO2peak. Similar
patterns and higher FATox occur during running when
compared with cycling (Achten et al., 2003; Knechtle
et al., 2004; Capostagno & Bosch, 2010). The highest
Table 2. Measured steady-state oxidation rates during submaximal (50%VO2peak) cycling (CYC) and rowing (ROW) exercise compared with rates
predicted by an incremental exercise test
VO2(L/min) VCO2(L/min) RER CHOox (g/min) FATox (g/min)
CYC Steady-state 1.98 ±0.08 1.80 ±0.08 0.91 ±0.01 1.75 ±0.10 0.30 ±0.02
Predicted 1.98 ±0.08 1.68 ±0.06* 0.85 ±0.02* 1.29 ±0.14* 0.51 ±0.06*
ROW Steady-state 2.08 ±0.13 1.82 ±0.11 0.88 ±0.011.53 ±0.100.43 ±0.05
Predicted 2.08 ±0.13 1.67 ±0.16* 0.79 ±0.03* 1.09 ±0.15* 0.59 ±0.05*
Data presented as mean ±SEM.
*P<0.05 predicted vs steady-state exercise.
P<0.05 CYC vs ROW.
CHOox, calculated rates of carbohydrate oxidation; FATox, calculated rates of fat oxidation; RER, respiratory exchange ratio; VCO2, carbon dioxide
production; VO2, oxygen uptake.
Fig. 4. Contribution of carbohydrate (CHO) and fat to energy
expenditure (kcal/min) during steady-state submaximal (SUB)
cycling (CYC) and rowing (ROW) exercise compared with
incremental (INC) exercise. Values are presented as
mean ±SEM. *P<0.05, SUB vs INC, †P<0.05 CYC SUB vs
ROW SUB.
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Egan et al.
FATox in the present study is similar to values in moder-
ately trained males during cycling (0.60 ±0.07 g/min;
Achten et al., 2002), and values ranging from 0.45 to
0.65 g/min reported in subsequent studies (Achten et al.,
2002; Achten & Jeukendrup, 2003a; Venables et al.,
2005). Moreover, higher FATox and lower CHOox during
rowing are reflected by the crossover point (Brooks &
Mercier, 1994) occurring at a higher relative exercise
intensity in rowing. That the highest FATox occurred in
the first stage of the incremental protocol has been pre-
viously observed (Achten & Jeukendrup, 2003b),
whereas the intensity at which the highest FATox occurs
is variable, ranging from 54% to 65% (Achten et al.,
2002, 2003) and from 25% to 77% (Venables et al.,
2005). Employing a incremental protocol that differs
from the original FATmax protocol, peak FATox occurred
43% and 50% in untrained and trained subjects,
respectively (Nordby et al., 2006). Clearly, the protocol
used, the participants recruited, and the habitual diet are
the three most important factors determining the rela-
tionship between FATox,FAT
max and exercise intensity
(Achten & Jeukendrup, 2004).
Differences in substrate utilization between exercise
modes have been attributed to divergence in the quantity
of recruited muscle mass. One proposed mechanism
involves a reduced activation of lipolysis because of a
lower catecholamine response during cycling as a con-
sequence of the recruitment of a smaller proportion of
muscle mass (Achten et al., 2003). This is speculative as
catecholamines are also potent stimulators of glycoge-
nolysis during exercise (Hargreaves, 2006), and increase
only modestly during low intensities of exercise (Galbo,
1983). An alternative explanation is that when a larger
proportion of muscle mass is recruited for the same rate
of energy expenditure, the metabolic demand per skel-
etal muscle fiber is lower (Hoffman et al., 1996; Beneke
et al., 2001), and the reliance on carbohydrate metabo-
lism is reduced (Costill et al., 1971; Coyle et al., 1988;
Richter et al., 1988).
Next, we compared FATox measured during the incre-
mental exercise tests to rates elicited during submaximal
steady-state exercise at 50%VO2peak. The current proto-
col, which uses 3-min stages at each power output incre-
ment, may overestimate FATox in sedentary individuals
(Bordenave et al., 2007). We extend these findings to
moderately trained individuals as FATox observed during
submaximal exercise was 42% and 28% lower in CYC
and ROW, respectively, compared with incremental
exercise at the same energy expenditure. The explanation
for this observation is likely to reside at the level of
VCO2kinetics. When comparing predicted to measured
gas exchange data during steady-state exercise, VCO2
values were markedly higher during steady-state exer-
cise. These data suggest that the rate of carbon dioxide
production at the onset of exercise, or when the exercise
intensity increases, lags behind VO2and thereby results
in an artificially lower RER value during 3-min incre-
ments at a given power output. This is unsurprising given
the half-time of VCO2on-kinetics is approximately 30%
to 60% longer than VO2on-kinetics due to higher solu-
bility and tissue storage of CO2(Diamond et al., 1977;
Zhang et al., 1991; Poole & Jones, 2012). The lower than
predicted FATox during submaximal exercise reflects this
artifact in RER caused by the disparity in VO2and VCO2
kinetics. However, FATox remained 43% higher in
rowing compared with cycling during steady-state
submaximal exercise matched for energy expenditure.
Therefore, predicting substrate utilization rates from
3-min stages during incremental exercise may overesti-
mate the magnitude (g/min) of FATox during submaximal
exercise, but the pattern of higher FATox during rowing
persists.
The training status of the participants may have
influenced the patterns of substrate utilization, as those
with previous rowing experience were recruited in
order to minimize the influence of inefficiencies in
rowing technique of novices. Therefore, the higher
FATox observed may reflect the training history of the
participants in the present study, so these findings
should be explored in other populations. A final expla-
nation for observed differences in FATox may be that,
secondary to mechanical alterations arising from gen-
erating high levels of ventilation in a variable seated
position, rowing exercise results in a relative hypocap-
nia at the same power output compared with cycling
(Szal & Schoene, 1989). Thus, the lower VCO2could
contribute to the aforementioned lower RER value, but
this remains to be assessed at low-to-moderate exercise
intensity.
Perspectives
Indoor rowing ergometry is an attractive exercise mode
because of its non-weightbearing nature. As a form of
physical activity, rowing for as little as 1 h per week is
associated with 18% risk reduction of developing coro-
nary heart disease (Tanasescu et al., 2002). Moreover,
during inter-mode comparisons, energy expenditure is
greater for rowing when the intensity of exercise is
matched by self-selected RPE (Zeni et al., 1996; Moyna
et al., 2001). Therefore, exercises such as rowing that
recruit larger muscle mass for the same perceived effort
may be most beneficial by optimizing the contribution of
FATox to energy expenditure (Achten & Jeukendrup,
2004; Brun et al., 2012), while simultaneously present-
ing a training stimulus that is perceptually preferable
(Moyna et al., 2001). Moreover, even when energy
expenditure is similar, rowing exercise elicits a greater
rate of fat oxidation than cycling across a broad range of
intensities.
Despite absolute FATox values being overestimated
during incremental exercise testing, the greater relative
contribution of fat to energy expenditure during rowing
persists during submaximal exercise. This phenomenon
635
Fat oxidation during rowing vs cycling
may be related to the quantity of muscle mass recruited,
the rate of carbon dioxide production and/or the training
status of the participants. However, because the present
study was performed with physically active young
males, and that the protocol was performed in the fasted
state, two factors known to result in elevated FATox
(Achten & Jeukendrup, 2004), the observed results are
likely to reflect a “best-case scenario” in relation to
FATox during rowing exercise. Future work should
explore whether these patterns are maintained in seden-
tary and at-risk populations, potentially in the post-
prandial state, in order to better inform exercise
prescription of non-weightbearing exercise and intensi-
ties individualized for maximal fat oxidation.
Key words: Exercise modality, energy expenditure, fuel
utilization, aerobic, non-weightbearing.
Acknowledgements
The authors would like to thank the participants for their dedica-
tion to this demanding study, and the excellent technical support
provided by Javier Monedero. Support for this research came from
the Irish Research Council for Science, Engineering and Technol-
ogy (IRCSET) and the Targeted Research Fund from Dublin City
University.
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Fat oxidation during rowing vs cycling
... pH, temperature, substrate availability, etc.) (Gevers, 1979;Robergs et al., 2004;Tarnopolsky et al., 1995). The oxidation of substrates is also known to be further altered extrinsically, via exercise duration (Phillips et al., 1996), and exercise modality (Achten et al., 2003;Capostagno and Bosch, 2010;Egan et al., 2016). Substrate metabolism shifts towards greater fat oxidation and reaches higher rates of maximal fat oxidation (MFO) during walking and running compared to cycling (Achten et al., 2003;Capostagno and Bosch, 2010;Chenevière et al., 2010;Knechtle et al., 2004). ...
... Carey et al. (1974) also demonstrated that maximal oxygen uptake values were not significantly different between treadmill and rowing exercise. Despite some aerobic similarities, MFO and Fat max was reported higher during rowing compared to cycling (Egan et al., 2016). The crossover point, where energy contribution from CHO and fat to total energy expenditure is equal (Brooks and Mercier, 1994), was also reported to occur at a higher relative exercise intensity during rowing than cycling (Egan et al., 2016). ...
... Despite some aerobic similarities, MFO and Fat max was reported higher during rowing compared to cycling (Egan et al., 2016). The crossover point, where energy contribution from CHO and fat to total energy expenditure is equal (Brooks and Mercier, 1994), was also reported to occur at a higher relative exercise intensity during rowing than cycling (Egan et al., 2016). Although the elliptical and rower involve a large level of muscle mass (Egan et al., 2016), they involve more regular activation of muscles in the upper limbs compared to treadmill exercise (Bazzucchi et al., 2013;Hagerman, 1984;Sozen, 2010). ...
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... For example, the -12% gradient used in the present study could increase cardiovascular and metabolic demands and muscle damage to a greater extent than gentler inclinations, such as between -5% and -10% [28]. Moreover, several factors such as insulin level [19], mode of exercise [29], and the recruitment of muscle mass during the test [30] influence the rate of exercise-induced fat oxidation. For example, when individuals performed cycling and rowing exercises at the same intensity, fat oxidation was greater during the rowing session, and this was likely due to the larger muscle mass recruited during rowing [30]. ...
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At international standard, sculling (two oars) and rowing (one oar) are competed on-water over 2000m. Race time is the critical measure of performance and is determined from mean skiff velocity during a race. Although a high proportion of race training is completed on-water, rowing ergometers are commonly used for performance testing, technique coaching, crew selection or for training during poor weather. Rowing biomechanics research has aimed to identify characteristics of successful sculling and sweep rowing strokes; however, biomechanical predictors of 2000m rowing performance are indistinct in the literature. If specific biomechanical parameters distinguish between ability levels and successful or unsuccessful techniques, these attributes can be considered when modifying technique or predicting future rowing performance. The kinematics and kinetics of the sculling and rowing movements have been described on ergometers, on-water and for novice and elite male and female rowers, but there is limited research on the ideal technique or how a rower’s anthropometry or boat set-up could help improve/optimise their rowing performance. Currently viewing the technique and providing verbal feedback is the primary tool used by a coach to help improve a rower’s technique and performance. The greater use of customised telemetered sensors on the rowing skiff can assist the coach and biomechanist with judging when performance (skiff velocity) improves with some form of intervention.
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Muscular exercise requires transitions to and from metabolic rates often exceeding an order of magnitude above resting and places prodigious demands on the oxidative machinery and O2-transport pathway. The science of kinetics seeks to characterize the dynamic profiles of the respiratory, cardiovascular, and muscular systems and their integration to resolve the essential control mechanisms of muscle energetics and oxidative function: a goal not feasible using the steady-state response. Essential features of the O2 uptake (VO2) kinetics response are highly conserved across the animal kingdom. For a given metabolic demand, fast VO2 kinetics mandates a smaller O2 deficit, less substrate-level phosphorylation and high exercise tolerance. By the same token, slow VO2 kinetics incurs a high O2 deficit, presents a greater challenge to homeostasis and presages poor exercise tolerance. Compelling evidence supports that, in healthy individuals walking, running, or cycling upright, VO2 kinetics control resides within the exercising muscle(s) and is therefore not dependent upon, or limited by, upstream O2-transport systems. However, disease, aging, and other imposed constraints may redistribute VO2 kinetics control more proximally within the O2-transport system. Greater understanding of VO2 kinetics control and, in particular, its relation to the plasticity of the O2-transport/utilization system is considered important for improving the human condition, not just in athletic populations, but crucially for patients suffering from pathologically slowed VO2 kinetics as well as the burgeoning elderly population. © 2012 American Physiological Society. Compr Physiol 2:933-996, 2012.
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Human muscles, limbs and supporting ventilatory, cardiovascular, and metabolic systems are well adapted for walking, and there is reasonable transfer of efficiency of movement to bicycling. Our efficiency and economy of movement of bipedal walking (≈30%) are far superior to those of apes. This overall body efficiency during walking and bicycling represents the multiplicative interaction of a phosphorylative coupling efficiency of ≈60%, and a mechanical coupling efficiency of ≈50%. These coupling efficiencies compare well with those of other species adapted for locomotion. We are capable runners, but our speed and power are inferior to carnivorous and omnivorous terrestrial mammalian quadrupeds because of biomechanical and physiological constraints. But, because of our metabolic plasticity (i.e., the ability to switch among carbohydrate (CHO)- and lipid-derived energy sources) our endurance capacity is very good by comparison to most mammals, but inferior to highly adapted species such as wolves and migratory birds. Our ancestral ability for hunting and gathering depends on strategy and capabilities in the areas of thermoregulation, and metabolic plasticity. Clearly, our competitive advantage of survival in the biosphere depends in intelligence and behavior. Today, those abilities that served early hunter-gatherers make for interesting athletic competitions due to wide variations in human phenotypes. In contemporary society, the stresses of regular physical exercise serve to minimize morbidities and mortality associated with physical inactivity, overnutrition, and aging. © 2012 American Physiological Society. Compr Physiol 2:537-562, 2012.
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Muscle glycogen and blood-borne glucose are important substrates for skeletal muscle during exercise and fatigue during endurance exercise often coincides with depletion of these carbohydrate reserves. This review summarises the effects of exercise on skeletal muscle carbohydrate metabolism and some of the important regulatory mechanisms. Factors that influence the utilisation of muscle glycogen and blood glucose during exercise include exercise intensity and duration, training status and diet. The important regulatory mechanisms include local factors within contracting muscle that influence enzyme activity and membrane transport systems, alterations in intramuscular metabolite levels, substrate availability and hormonal regulation, primarily by insulin and adrenaline. The interplay of these factors ensures the appropriate mobilisation and utilisation of glycogen and glucose during exercise.
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Context Studies have shown an inverse relationship between exercise and risk of coronary heart disease (CHD), but data on type and intensity are sparse. Objective To assess the amount, type, and intensity of physical activity in relation to risk of CHD among men. Design, Setting, and Participants A cohort of 44452 US men enrolled in the Health Professionals' Follow-up Study, followed up at 2-year intervals from 1986 through January 31, 1998, to assess potential CHD risk factors, identify newly diagnosed cases of CHD, and assess levels of leisure-time physical activity. Main Outcome Measure Incident nonfatal myocardial infarction or fatal CHD occurring during the follow-up period. Results During 475755 person-years, we documented 1700 new cases of CHD. Total physical activity, running, weight training, and rowing were each inversely associated with risk of CHID. The RRs (95% confidence intervals [CIs]) corresponding to quintiles of metabolic equivalent tasks (METs) for total physical activity adjusted for age, smoking, and other cardiovascular risk factors were 1.0, 0.90 (0.78-1.04), 0.87 (0.75-1.00), 0.83 (0.71-0.96), and 0.70 (0.59-0.82) (P<.001 for trend). Men who ran for an hour or more per week had a 42% risk reduction (RR, 0.58; 95% CI, 0.44-0.77) compared with men who did not run (P<.001 for trend). Men who trained with weights for 30 minutes or more per week had a 23% risk reduction (RR, 0.77; 95% CI, 0.61-0.98) compared with men who did not train with weights (P=.03 for trend). Rowing for 1 hour or more per week was associated with an 18% risk reduction (RR, 0.82; 05% CI, 0.68-0.99). Average exercise intensity was associated with reduced CHD risk independent of the total volume of physical activity. The RRs (95% CIs) corresponding to moderate (4-6 MET's) and high (6-12 METs) activity intensities were 0.94 (0.83-1.04) and 0.83 (0.72-0.97) compared with low activity intensity (<4 ME Ts) (P=.02 for trend). A half-hour per day or more of brisk walking was associated with an 18% risk reduction (RR, 0.82; 95% CI, 0.67-1.00). Walking pace was associated with reduced CHD risk independent of the number of walking hours. Conclusions Total physical activity, running, weight training, and walking were each associated with reduced CHID risk. Average exercise intensity was associated with reduced risk independent of the number of MET-hours spent in physical activity.