1268
Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by FLORIDA STATE UNIVERSITY on 11/13/14 For personal use only.
BRIEF COMMUNICATION The reliability of running economy expressed as oxygen cost and energy cost in trained distance runners Andrew J. Shaw, Stephen A. Ingham, Barry W. Fudge, and Jonathan P. Folland
Abstract: This study assessed the between-test reliability of oxygen cost (OC) and energy cost (EC) in distance runners, and contrasted it with the smallest worthwhile change (SWC) of these measures. OC and EC displayed similar levels of within-subject variation (typical error < 3.85%). However, the typical error (2.75% vs 2.74%) was greater than the SWC (1.38% vs 1.71%) for both OC and EC, respectively, indicating insufficient sensitivity to confidently detect small, but meaningful, changes in OC and EC. Key words: athletes, physiology, physiological assessment of performance, running. Résumé : Cette étude évalue la fiabilité entre tests du coût d'oxygène (OC) et du coût énergétique (EC) chez des coureurs de distance et la compare au plus petit changement digne d'intérêt (SWC) concernant ces mesures. OC et EC présentent une variation intrasujet similaire (erreur typique < 3,85 %). Toutefois, l'erreur typique (2,75 vs 2,74 %) est plus grande que le SWC d'Oc et d'Oe (1,38 vs 1,71 %), respectivement, ce qui révèle un manque de sensibilité pour détecter avec confiance des variations d'Oc et d'Oe minimes mais significatives. [Traduit par la Rédaction] Mots-clés : athlètes, physiologie, évaluation physiologique de la performance, course.
Introduction For distance running, maximal oxygen uptake (V˙O2max), the proportion of V˙O2max that can be sustained prior to the onset blood lactate accumulation, and the metabolic cost of locomotion are the primary physiological factors that underpin performance (Pollock 1977; Farrell et al. 1979; Ingham et al. 2008). The latter, quantified as the oxygen cost or energy cost for a given submaximal velocity, defines an individual's running economy. Within an athletically homogenous population, running economy is cited as a stronger indicator of endurance performance than V˙O2max alone (Conley and Krahenbuhl 1980; Daniels 1985), and it has been suggested that modest enhancements in running economy could result in substantial performance gains for elite distance runners (Cavanagh 1989). Accordingly, improvements in running economy are highly desirable to maximise athletic performance. However, without prior knowledge of the between test reliability of running economy, interpretation of any changes is limited. Measurements of running economy are made during submaximal steady-state exercise to provide an index of adenosine triphosphate (ATP) turnover when aerobic metabolism supplies virtually all of the energy requirements. The most commonly employed measure of running economy is oxygen cost (OC), defined as the oxygen required to cover a given distance (Foster and Lucia 2007; Ingham et al. 2008), and has been reported to have a typical error of 4.7% and 2.4% in elite distance runners (Brisswalter and Legros 1994; Saunders et al. 2004). However, as there are differences in the OC of metabolising carbohydrates and lipids (Jeukendrup and Wallis 2005), alterations in substrate utilisation could influence, and potentially confound, the reliability of running economy. The use of energy cost (EC) has been used as an alternative measure of running economy (Margaria et al. 1963; Folland et al. 2006; Allison et al. 2008) that has been postulated to be a more comprehensive, sensitive, and valid measure (Fletcher et al. 2009),
as it calculates actual energy expenditure, from OC and the respiratory exchange ratio (RER), and thus accounts for variations in substrate metabolism. To minimise between-test reliability of OC, previous studies have typically employed a range of experimental controls, including restrictions on prior training and nutrition (Morgan et al. 1991, Brisswalter and Legros 1994; Pereira and Freedson 1997), to control for variations in substrate metabolism. However, for the monitoring of athletes in full-time training, these experimental controls are frequently impractical and may not be necessary if EC is the primary measurement of running economy. Accordingly, quantification of running economy as EC might mitigate the confounding influence of substrate utilisation on OC, providing greater reliability without imposing practical constraints on the participant. We therefore hypothesised that EC would provide a more reliable measure of running economy than OC. To aid the practical interpretation of between-test reliability, it is useful to compare the typical error to the smallest worthwhile change (SWC). The SWC reflects the smallest individual change that can be interpreted as real within acceptable limits of probability (Impellizzeri and Marcora 2009), representing the threshold for when a change becomes “meaningful”. Comparisons of the typical error to SWC enable investigators to assess if a test is sufficiently reliable to detect the SWC. Consequently, if the typical error > SWC, it is not possible to confidently detect the SWC because of the insufficient reliability of the test. A previous investigation suggested that absolute measurements of OC (L·min−1) were sufficiently reliable to detect the SWC (Saunders et al. 2004). However, the metabolic cost of running is known to be proportional to body mass (BM), specifically BM0.75 (Bergh et al. 1991), and relative values enable accurate comparisons between individuals of differing BM (Bergh et al. 1991; Svedenhag 1995), which is not the case for absolute values. As the calculation of the SWC relies
Received 7 February 2013. Accepted 18 June 2013. A.J. Shaw. English Institute of Sport, Loughborough University, Loughborough, UK; School of Sport, Exercise and Health Sciences, Loughborough University, Ashby Road, Loughborough, Leicestershire LE11 3TU, UK. S.A. Ingham and B.W. Fudge. English Institute of Sport, Loughborough University, Loughborough, UK. J.P. Folland. School of Sport, Exercise and Health Sciences, Loughborough University, Ashby Road, Loughborough, Leicestershire LE11 3TU, UK. Corresponding author: Andrew J. Shaw (e-mail: [email protected]).
Appl. Physiol. Nutr. Metab. 38: 1268–1272 (2013) dx.doi.org/10.1139/apnm-2013-0055
Published at www.nrcresearchpress.com/apnm on 26 September 2013.
Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by FLORIDA STATE UNIVERSITY on 11/13/14 For personal use only.
Shaw et al.
on the assessment of inter-individual differences, the expression of running economy relative to BM0.75 would appear the most appropriate measurement. However, whether quantification of running economy relative to BM0.75 provides sufficient reliability to detect the SWC remains unknown. Therefore, the primary aim of the present study was to examine the between-test reliability of oxygen and energy cost measurements of running economy. Highly trained competitive runners were assessed using a widely used short-duration incremental submaximal running protocol, but without specific training or dietary restrictions, to examine if these controls might be circumvented by the potentially more reliable EC assessment of running economy. The secondary aim was to contrast the reliability of OC and EC measurements with the SWC for these measures.
Materials and methods Participants Twelve healthy endurance trained males (mean ± SD: age, 28 ± 6 years; stature, 180 ± 5 cm; BM, 70.6 ± 3.4 kg, V˙O2max, 75.5 ± 5.2 mL·kg−1·min−1) participated in this study. Participants' best performance times over the past 2 seasons were 86% ± 5% of the current British record as of December 2012 in events from 1500 m to the marathon. All participants were treadmill habituated and provided written informed consent prior to participating in this study, which was approved by the Loughborough University Ethical Advisory Committee. Observations on a larger cohort of 29 endurance trained males (age, 24 ± 7 years; BM, 67.9 ± 7.5 kg; V˙O2max, 73.4 ± 6.1 mL·kg−1·min−1) were used to determine the SWC. Overview Participants attended the laboratory on 4 separate occasions. The first 3 visits were for identical submaximal running trials conducted 7 days apart at a consistent time of day for each participant. A final visit involved a maximal treadmill running assessment. Participants wore appropriate clothing and racing shoes and laboratory conditions were similar throughout all running assessments (temperature, 19–21 °C; relative humidity, 40%–50%). The SWC was assessed by using single observations of 29 runners that utilised the same protocol employed for the reliability measurements. Protocol Submaximal running assessments Following a warm-up (10 min at 10–11.5 km·h−1), participants completed a discontinuous submaximal incremental test of seven 3 min stages with increments of 1 km·h−1 on a calibrated motorised treadmill (HP cosmos Saturn, Traunstein, Germany) at 1% gradient, interspersed by 30-s rest periods for blood sampling. The heart rate (HR) response during the warm-up was used to determine a starting speed and provide a minimum of 4 speeds prior to lactate turnpoint (LTP). HR (s610i, Polar, Finland) and pulmonary gas exchange (detailed below) were monitored throughout the test. Maximal running assessments V˙O2max was determined by a continuous incremental treadmill running ramp test to volitional exhaustion. After a warm-up, participants initially ran at a speed 2 km·h−1 below the final speed of the submaximal test and at a 1% gradient. Each minute, the incline was increased by 1% until volitional exhaustion. The test duration was typically 6–8 min. Measurements Anthropometry Prior to exercise on all laboratory visits, BM was measured using beam balance scales to the nearest 0.1 kg. Stature was recorded to the nearest 1 cm using a stadiometer.
1269
Pulmonary gas exchange Breath-by-breath gas exchange data was quantified via an automated open circuit metabolic cart (Oxycon Pro, Carefusion, San Diego, Calif., USA). Participants breathed through a low-dead space mask, with air sampled at 60 mL·min−1. Prior to each test, 2-point calibrations of both gas sensors were completed, using a known gas mixture (16% O2, 5% CO2) and ambient air. Ventilatory volume was calibrated using a 3-L (±0.4%) syringe. Oxygen consumption (V˙O2), carbon dioxide production (V˙CO2), and RER values were quantified over the final 60 s of each stage of the submaximal protocol. To assess if a steady-state for V˙O2 and V˙CO2 had been attained (defined as a difference of 1.0 mmol·L−1 from the previous stage (Thoden 1991). The 4 stages prior to LTP were identified for each participant (LTP-4, –3, –2 and –1 km·h−1) and were used to assess the OC and EC of running. Calculation of running economy V˙O2 during the final minute of each submaximal stage was used to determine OC in mL·kg–0.75·km−1. V˙O2 and V˙CO2 during the same time period were used to calculate EC. Updated nonprotein respiratory quotient equations (Péronnet and Massicotte 1991) were used to estimate substrate utilisation (g·min−1) during the monitored period. The energy derived from each substrate was then calculated by multiplying fat and carbohydrate usage by 9.75 kcal and 4.07 kcal, respectively, reflecting the mean energy content of the metabolised substrates during moderate to high intensity exercise (Jeukendrup and Wallis 2005). EC was quantified as the sum of these values, expressed in kcal·kg−0.75·km−1. Both OC and EC were also quantified in absolute terms (L·km−1 and kcal·km−1, respectively), enabling comparisons of the SWC to previously published data. Statistical analyses Normal distributions of the dependent variables were confirmed via Shapiro-Wilk tests, and the variance was found to be homogenous for the assessed speeds. Two-way ANOVA with repeated measures were used to assess differences within all monitored variables across trials and speeds. To assess intra-individual variation between tests, the typical error (TE), a value that encompasses both technical and biological variation, was calculated using the root mean squares error method (Batterham and George 2003). The reliability of EC and OC was also assessed via intraclass correlation coefficients (ICC; 2-way random, single measure). To enable the statistical comparison (2-way ANOVA) of withinsubject variation to be made between measures, the withinsubject coefficients of variations (CVW) were calculated for each individual ((Standard deviation/mean) × 100). The SWC in measures of EC and OC was calculated as 0.2 times the betweenparticipant standard deviation within the larger cohort (n = 29; Hopkins 2000). The between-participant coefficient of variation (CVB) for V˙O2 and V˙CO2 were calculated from this cohort. Data are presented as means ± standard deviation, with significance accepted at p ≤ 0.05. Published by NRC Research Press
1270
Appl. Physiol. Nutr. Metab. Vol. 38, 2013
Table 1. Reliability of running economy measures collected during the submaximal running assessments. Trial Measurement speed
1
2
3
TE
TE (%)
ICC
16.22±1.46 16.11±1.33 16.02±1.18 16.11±1.25 16.12±1.28
15.94±1.05 15.99±1.02 15.97±0.98 15.96±0.96 15.96±0.98
15.87±0.94 16.06±0.98 16.16±0.98 16.20±0.89 16.06±0.93
0.53 0.50 0.45 0.43 0.45
3.34 3.24 2.86 2.73 2.89
0.79 0.81 0.82 0.84
Oxygen cost relative to BM (mL O·kg−0.75·km−1) LTP-4 km·h−1 666.5±58.7 654.7±43.9 LTP-3 km·h−1 662.2±53.1 656.6±41.7 LTP-2 km·h−1 658.3±45.1 655.5±37.0 LTP-1 km·h−1 662.1±48.8 655.4±36.5 Mean of the 4 speeds 662.3±50.3 655.6±38.9
651.0±39.8 658.4±36.6 662.5±37.1 662.3±34.4 658.5±36.2
21.3 20.2 18.5 17.6 18.4
3.31 3.18 2.86 2.72 2.88
0.82 0.82 0.81 0.83
Energy cost (kcal·km−1) LTP-4 km·h−1 LTP-3 km·h−1* LTP-2 km·h−1 LTP-1 km.h−1* Mean of the 4 speeds
82.43±5.98 83.43±5.77 83.95±5.72 84.40±5.56 83.56±5.63
82.31±4.57 84.20±5.08 85.14±5.33 85.51±4.58 84.30±4.76
3.17 2.91 2.71 2.75 2.70
3.83 3.53 3.27 3.28 3.27
0.73 0.78 0.78 0.76
3.385±0.240 3.426±0.229 3.447±0.214 3.465±0.210 3.431±0.218
3.375±0.180 3.452±0.182 3.494±0.192 3.514±0.175 3.459±0.176
0.126 0.115 0.108 0.106 0.106
3.72 3.39 3.16 3.05 3.13
0.75 0.79 0.78 0.79
Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by FLORIDA STATE UNIVERSITY on 11/13/14 For personal use only.
−1
Oxygen cost (L O2·km ) LTP-4 km·h−1 LTP-3 km·h−1 LTP-2 km·h−1 LTP-1 km·h−1 Mean of the 4 speeds
84.27±7.29 84.70±7.13 84.70±6.05 86.35±6.81 85.01±6.72
Energy cost relative to BM (kcal·kg−0.75·km−1) LTP-4 km·h−1 3.463±0.297 LTP-3 km·h−1* 3.481±0.287 3.480±0.233 LTP-2 km·h−1 LTP-1 km·h−1* 3.549±0.281 Mean of the 4 speeds 3.493±0.240
Note: Data are displayed as means ± SD (n = 12). BM, body mass; ICC, intraclass correlation coefficient; LTP, lactate turnpoint; TE, typical error. *Significant difference to LTP-4 km·h−1 when collapsed across trials.
Results BM remained consistent across the submaximal assessments (70.6 ± 3.4, 70.6 ± 3.3, 70.8 ± 3.4 kg; p = 0.46), with a mean CVW of 0.55% ± 0.31% across the 3 trials. Mean LTP was 17 ± 1 km·h−1 for the cohort. V˙O2, RER, and blood lactate concentration were similar across all trials at each given speed. Low levels of within-subject variation were seen for HR (TE < 3.25%), V˙CO2 (TE < 5.94%), RER (TE < 4.35%), and V˙O2 (TE < 3.33%) across the submaximal assessments. Within-subject variability for blood lactate concentration was high for all monitored speeds (TE 18.3%–24.4%), but absolute group mean values were stable (
Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by FLORIDA STATE UNIVERSITY on 11/13/14 For personal use only.
BRIEF COMMUNICATION The reliability of running economy expressed as oxygen cost and energy cost in trained distance runners Andrew J. Shaw, Stephen A. Ingham, Barry W. Fudge, and Jonathan P. Folland
Abstract: This study assessed the between-test reliability of oxygen cost (OC) and energy cost (EC) in distance runners, and contrasted it with the smallest worthwhile change (SWC) of these measures. OC and EC displayed similar levels of within-subject variation (typical error < 3.85%). However, the typical error (2.75% vs 2.74%) was greater than the SWC (1.38% vs 1.71%) for both OC and EC, respectively, indicating insufficient sensitivity to confidently detect small, but meaningful, changes in OC and EC. Key words: athletes, physiology, physiological assessment of performance, running. Résumé : Cette étude évalue la fiabilité entre tests du coût d'oxygène (OC) et du coût énergétique (EC) chez des coureurs de distance et la compare au plus petit changement digne d'intérêt (SWC) concernant ces mesures. OC et EC présentent une variation intrasujet similaire (erreur typique < 3,85 %). Toutefois, l'erreur typique (2,75 vs 2,74 %) est plus grande que le SWC d'Oc et d'Oe (1,38 vs 1,71 %), respectivement, ce qui révèle un manque de sensibilité pour détecter avec confiance des variations d'Oc et d'Oe minimes mais significatives. [Traduit par la Rédaction] Mots-clés : athlètes, physiologie, évaluation physiologique de la performance, course.
Introduction For distance running, maximal oxygen uptake (V˙O2max), the proportion of V˙O2max that can be sustained prior to the onset blood lactate accumulation, and the metabolic cost of locomotion are the primary physiological factors that underpin performance (Pollock 1977; Farrell et al. 1979; Ingham et al. 2008). The latter, quantified as the oxygen cost or energy cost for a given submaximal velocity, defines an individual's running economy. Within an athletically homogenous population, running economy is cited as a stronger indicator of endurance performance than V˙O2max alone (Conley and Krahenbuhl 1980; Daniels 1985), and it has been suggested that modest enhancements in running economy could result in substantial performance gains for elite distance runners (Cavanagh 1989). Accordingly, improvements in running economy are highly desirable to maximise athletic performance. However, without prior knowledge of the between test reliability of running economy, interpretation of any changes is limited. Measurements of running economy are made during submaximal steady-state exercise to provide an index of adenosine triphosphate (ATP) turnover when aerobic metabolism supplies virtually all of the energy requirements. The most commonly employed measure of running economy is oxygen cost (OC), defined as the oxygen required to cover a given distance (Foster and Lucia 2007; Ingham et al. 2008), and has been reported to have a typical error of 4.7% and 2.4% in elite distance runners (Brisswalter and Legros 1994; Saunders et al. 2004). However, as there are differences in the OC of metabolising carbohydrates and lipids (Jeukendrup and Wallis 2005), alterations in substrate utilisation could influence, and potentially confound, the reliability of running economy. The use of energy cost (EC) has been used as an alternative measure of running economy (Margaria et al. 1963; Folland et al. 2006; Allison et al. 2008) that has been postulated to be a more comprehensive, sensitive, and valid measure (Fletcher et al. 2009),
as it calculates actual energy expenditure, from OC and the respiratory exchange ratio (RER), and thus accounts for variations in substrate metabolism. To minimise between-test reliability of OC, previous studies have typically employed a range of experimental controls, including restrictions on prior training and nutrition (Morgan et al. 1991, Brisswalter and Legros 1994; Pereira and Freedson 1997), to control for variations in substrate metabolism. However, for the monitoring of athletes in full-time training, these experimental controls are frequently impractical and may not be necessary if EC is the primary measurement of running economy. Accordingly, quantification of running economy as EC might mitigate the confounding influence of substrate utilisation on OC, providing greater reliability without imposing practical constraints on the participant. We therefore hypothesised that EC would provide a more reliable measure of running economy than OC. To aid the practical interpretation of between-test reliability, it is useful to compare the typical error to the smallest worthwhile change (SWC). The SWC reflects the smallest individual change that can be interpreted as real within acceptable limits of probability (Impellizzeri and Marcora 2009), representing the threshold for when a change becomes “meaningful”. Comparisons of the typical error to SWC enable investigators to assess if a test is sufficiently reliable to detect the SWC. Consequently, if the typical error > SWC, it is not possible to confidently detect the SWC because of the insufficient reliability of the test. A previous investigation suggested that absolute measurements of OC (L·min−1) were sufficiently reliable to detect the SWC (Saunders et al. 2004). However, the metabolic cost of running is known to be proportional to body mass (BM), specifically BM0.75 (Bergh et al. 1991), and relative values enable accurate comparisons between individuals of differing BM (Bergh et al. 1991; Svedenhag 1995), which is not the case for absolute values. As the calculation of the SWC relies
Received 7 February 2013. Accepted 18 June 2013. A.J. Shaw. English Institute of Sport, Loughborough University, Loughborough, UK; School of Sport, Exercise and Health Sciences, Loughborough University, Ashby Road, Loughborough, Leicestershire LE11 3TU, UK. S.A. Ingham and B.W. Fudge. English Institute of Sport, Loughborough University, Loughborough, UK. J.P. Folland. School of Sport, Exercise and Health Sciences, Loughborough University, Ashby Road, Loughborough, Leicestershire LE11 3TU, UK. Corresponding author: Andrew J. Shaw (e-mail: [email protected]).
Appl. Physiol. Nutr. Metab. 38: 1268–1272 (2013) dx.doi.org/10.1139/apnm-2013-0055
Published at www.nrcresearchpress.com/apnm on 26 September 2013.
Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by FLORIDA STATE UNIVERSITY on 11/13/14 For personal use only.
Shaw et al.
on the assessment of inter-individual differences, the expression of running economy relative to BM0.75 would appear the most appropriate measurement. However, whether quantification of running economy relative to BM0.75 provides sufficient reliability to detect the SWC remains unknown. Therefore, the primary aim of the present study was to examine the between-test reliability of oxygen and energy cost measurements of running economy. Highly trained competitive runners were assessed using a widely used short-duration incremental submaximal running protocol, but without specific training or dietary restrictions, to examine if these controls might be circumvented by the potentially more reliable EC assessment of running economy. The secondary aim was to contrast the reliability of OC and EC measurements with the SWC for these measures.
Materials and methods Participants Twelve healthy endurance trained males (mean ± SD: age, 28 ± 6 years; stature, 180 ± 5 cm; BM, 70.6 ± 3.4 kg, V˙O2max, 75.5 ± 5.2 mL·kg−1·min−1) participated in this study. Participants' best performance times over the past 2 seasons were 86% ± 5% of the current British record as of December 2012 in events from 1500 m to the marathon. All participants were treadmill habituated and provided written informed consent prior to participating in this study, which was approved by the Loughborough University Ethical Advisory Committee. Observations on a larger cohort of 29 endurance trained males (age, 24 ± 7 years; BM, 67.9 ± 7.5 kg; V˙O2max, 73.4 ± 6.1 mL·kg−1·min−1) were used to determine the SWC. Overview Participants attended the laboratory on 4 separate occasions. The first 3 visits were for identical submaximal running trials conducted 7 days apart at a consistent time of day for each participant. A final visit involved a maximal treadmill running assessment. Participants wore appropriate clothing and racing shoes and laboratory conditions were similar throughout all running assessments (temperature, 19–21 °C; relative humidity, 40%–50%). The SWC was assessed by using single observations of 29 runners that utilised the same protocol employed for the reliability measurements. Protocol Submaximal running assessments Following a warm-up (10 min at 10–11.5 km·h−1), participants completed a discontinuous submaximal incremental test of seven 3 min stages with increments of 1 km·h−1 on a calibrated motorised treadmill (HP cosmos Saturn, Traunstein, Germany) at 1% gradient, interspersed by 30-s rest periods for blood sampling. The heart rate (HR) response during the warm-up was used to determine a starting speed and provide a minimum of 4 speeds prior to lactate turnpoint (LTP). HR (s610i, Polar, Finland) and pulmonary gas exchange (detailed below) were monitored throughout the test. Maximal running assessments V˙O2max was determined by a continuous incremental treadmill running ramp test to volitional exhaustion. After a warm-up, participants initially ran at a speed 2 km·h−1 below the final speed of the submaximal test and at a 1% gradient. Each minute, the incline was increased by 1% until volitional exhaustion. The test duration was typically 6–8 min. Measurements Anthropometry Prior to exercise on all laboratory visits, BM was measured using beam balance scales to the nearest 0.1 kg. Stature was recorded to the nearest 1 cm using a stadiometer.
1269
Pulmonary gas exchange Breath-by-breath gas exchange data was quantified via an automated open circuit metabolic cart (Oxycon Pro, Carefusion, San Diego, Calif., USA). Participants breathed through a low-dead space mask, with air sampled at 60 mL·min−1. Prior to each test, 2-point calibrations of both gas sensors were completed, using a known gas mixture (16% O2, 5% CO2) and ambient air. Ventilatory volume was calibrated using a 3-L (±0.4%) syringe. Oxygen consumption (V˙O2), carbon dioxide production (V˙CO2), and RER values were quantified over the final 60 s of each stage of the submaximal protocol. To assess if a steady-state for V˙O2 and V˙CO2 had been attained (defined as a difference of 1.0 mmol·L−1 from the previous stage (Thoden 1991). The 4 stages prior to LTP were identified for each participant (LTP-4, –3, –2 and –1 km·h−1) and were used to assess the OC and EC of running. Calculation of running economy V˙O2 during the final minute of each submaximal stage was used to determine OC in mL·kg–0.75·km−1. V˙O2 and V˙CO2 during the same time period were used to calculate EC. Updated nonprotein respiratory quotient equations (Péronnet and Massicotte 1991) were used to estimate substrate utilisation (g·min−1) during the monitored period. The energy derived from each substrate was then calculated by multiplying fat and carbohydrate usage by 9.75 kcal and 4.07 kcal, respectively, reflecting the mean energy content of the metabolised substrates during moderate to high intensity exercise (Jeukendrup and Wallis 2005). EC was quantified as the sum of these values, expressed in kcal·kg−0.75·km−1. Both OC and EC were also quantified in absolute terms (L·km−1 and kcal·km−1, respectively), enabling comparisons of the SWC to previously published data. Statistical analyses Normal distributions of the dependent variables were confirmed via Shapiro-Wilk tests, and the variance was found to be homogenous for the assessed speeds. Two-way ANOVA with repeated measures were used to assess differences within all monitored variables across trials and speeds. To assess intra-individual variation between tests, the typical error (TE), a value that encompasses both technical and biological variation, was calculated using the root mean squares error method (Batterham and George 2003). The reliability of EC and OC was also assessed via intraclass correlation coefficients (ICC; 2-way random, single measure). To enable the statistical comparison (2-way ANOVA) of withinsubject variation to be made between measures, the withinsubject coefficients of variations (CVW) were calculated for each individual ((Standard deviation/mean) × 100). The SWC in measures of EC and OC was calculated as 0.2 times the betweenparticipant standard deviation within the larger cohort (n = 29; Hopkins 2000). The between-participant coefficient of variation (CVB) for V˙O2 and V˙CO2 were calculated from this cohort. Data are presented as means ± standard deviation, with significance accepted at p ≤ 0.05. Published by NRC Research Press
1270
Appl. Physiol. Nutr. Metab. Vol. 38, 2013
Table 1. Reliability of running economy measures collected during the submaximal running assessments. Trial Measurement speed
1
2
3
TE
TE (%)
ICC
16.22±1.46 16.11±1.33 16.02±1.18 16.11±1.25 16.12±1.28
15.94±1.05 15.99±1.02 15.97±0.98 15.96±0.96 15.96±0.98
15.87±0.94 16.06±0.98 16.16±0.98 16.20±0.89 16.06±0.93
0.53 0.50 0.45 0.43 0.45
3.34 3.24 2.86 2.73 2.89
0.79 0.81 0.82 0.84
Oxygen cost relative to BM (mL O·kg−0.75·km−1) LTP-4 km·h−1 666.5±58.7 654.7±43.9 LTP-3 km·h−1 662.2±53.1 656.6±41.7 LTP-2 km·h−1 658.3±45.1 655.5±37.0 LTP-1 km·h−1 662.1±48.8 655.4±36.5 Mean of the 4 speeds 662.3±50.3 655.6±38.9
651.0±39.8 658.4±36.6 662.5±37.1 662.3±34.4 658.5±36.2
21.3 20.2 18.5 17.6 18.4
3.31 3.18 2.86 2.72 2.88
0.82 0.82 0.81 0.83
Energy cost (kcal·km−1) LTP-4 km·h−1 LTP-3 km·h−1* LTP-2 km·h−1 LTP-1 km.h−1* Mean of the 4 speeds
82.43±5.98 83.43±5.77 83.95±5.72 84.40±5.56 83.56±5.63
82.31±4.57 84.20±5.08 85.14±5.33 85.51±4.58 84.30±4.76
3.17 2.91 2.71 2.75 2.70
3.83 3.53 3.27 3.28 3.27
0.73 0.78 0.78 0.76
3.385±0.240 3.426±0.229 3.447±0.214 3.465±0.210 3.431±0.218
3.375±0.180 3.452±0.182 3.494±0.192 3.514±0.175 3.459±0.176
0.126 0.115 0.108 0.106 0.106
3.72 3.39 3.16 3.05 3.13
0.75 0.79 0.78 0.79
Appl. Physiol. Nutr. Metab. Downloaded from www.nrcresearchpress.com by FLORIDA STATE UNIVERSITY on 11/13/14 For personal use only.
−1
Oxygen cost (L O2·km ) LTP-4 km·h−1 LTP-3 km·h−1 LTP-2 km·h−1 LTP-1 km·h−1 Mean of the 4 speeds
84.27±7.29 84.70±7.13 84.70±6.05 86.35±6.81 85.01±6.72
Energy cost relative to BM (kcal·kg−0.75·km−1) LTP-4 km·h−1 3.463±0.297 LTP-3 km·h−1* 3.481±0.287 3.480±0.233 LTP-2 km·h−1 LTP-1 km·h−1* 3.549±0.281 Mean of the 4 speeds 3.493±0.240
Note: Data are displayed as means ± SD (n = 12). BM, body mass; ICC, intraclass correlation coefficient; LTP, lactate turnpoint; TE, typical error. *Significant difference to LTP-4 km·h−1 when collapsed across trials.
Results BM remained consistent across the submaximal assessments (70.6 ± 3.4, 70.6 ± 3.3, 70.8 ± 3.4 kg; p = 0.46), with a mean CVW of 0.55% ± 0.31% across the 3 trials. Mean LTP was 17 ± 1 km·h−1 for the cohort. V˙O2, RER, and blood lactate concentration were similar across all trials at each given speed. Low levels of within-subject variation were seen for HR (TE < 3.25%), V˙CO2 (TE < 5.94%), RER (TE < 4.35%), and V˙O2 (TE < 3.33%) across the submaximal assessments. Within-subject variability for blood lactate concentration was high for all monitored speeds (TE 18.3%–24.4%), but absolute group mean values were stable (
