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Avish P. Sharma, Adrian D. Elliott and David J. Bentley


Road cycle racing is characterized by significant variability in exercise intensity. Existing protocols attempting to model this aspect display inadequate variation in power output. Furthermore, the reliability of protocols representative of road cycle racing is not well known. There are also minimal data regarding the physiological parameters that best predict performance during variable-power cycling.


To determine the reliability of mean power output during a new test of variable-power cycling and establish the relationship between physiological attributes typically measured during an incremental exercise test and performance during the variable-power cycling test (VCT).


Fifteen trained male cyclists (mean ± SD age 33 ± 6.5 y, VO2max 57.9 ± 4.8 mL · kg−1 · min−1) performed an incremental exercise test to exhaustion for determination of physiological attributes, 2 VCTs (plus familiarization), and a 30-km time trial. The VCT was modeled on data from elite men’s road racing and included significant variation in power output.


Mean power output during the VCT showed good reliability (r = .92, CV% = 1.98). Relative power during the self-paced sections of the VCT was most correlated with maximal aerobic power (r = .79) and power at the second ventilatory threshold (r = .69). Blood lactate concentration showed poor reliability between trials (CV% = 13.93%).


This study has demonstrated a new reliable protocol simulating the stochastic nature of road cycling races. Further research is needed to determine which factors predict performance during variable-power cycling and the validity of the test in monitoring longitudinal changes in cycling performance.

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Erin L. McCleave, Katie M. Slattery, Rob Duffield, Philo U. Saunders, Avish P. Sharma, Stephen Crowcroft and Aaron J. Coutts

Purpose: To determine whether combining training in heat with “Live High, Train Low” hypoxia (LHTL) further improves thermoregulatory and cardiovascular responses to a heat-tolerance test compared with independent heat training. Methods: A total of 25 trained runners (peak oxygen uptake = 64.1 [8.0] mL·min−1·kg−1) completed 3-wk training in 1 of 3 conditions: (1) heat training combined with “LHTL” hypoxia (H+H; FiO2 = 14.4% [3000 m], 13 h·d−1; train at <600 m, 33°C, 55% relative humidity [RH]), (2) heat training (HOT; live and train <600 m, 33°C, 55% RH), and (3) temperate training (CONT; live and train <600 m, 13°C, 55% RH). Heat adaptations were determined from a 45-min heat-response test (33°C, 55% RH, 65% velocity corresponding to the peak oxygen uptake) at baseline and immediately and 1 and 3 wk postexposure (baseline, post, 1 wkP, and 3 wkP, respectively). Core temperature, heart rate, sweat rate, sodium concentration, plasma volume, and perceptual responses were analyzed using magnitude-based inferences. Results: Submaximal heart rate (effect size [ES] = −0.60 [−0.89; −0.32]) and core temperature (ES = −0.55 [−0.99; −0.10]) were reduced in HOT until 1 wkP. Sweat rate (ES = 0.36 [0.12; 0.59]) and sweat sodium concentration (ES = −0.82 [−1.48; −0.16]) were, respectively, increased and decreased until 3 wkP in HOT. Submaximal heart rate (ES = −0.38 [−0.85; 0.08]) was likely reduced in H+H at 3 wkP, whereas CONT had unclear physiological changes. Perceived exertion and thermal sensation were reduced across all groups. Conclusions: Despite greater physiological stress from combined heat training and “LHTL” hypoxia, thermoregulatory adaptations are limited in comparison with independent heat training. The combined stimuli provide no additional physiological benefit during exercise in hot environments.

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Amy L. Woods, Avish P. Sharma, Laura A. Garvican-Lewis, Philo U. Saunders, Anthony J. Rice and Kevin G. Thompson

High altitude exposure can increase resting metabolic rate (RMR) and induce weight loss in obese populations, but there is a lack of research regarding RMR in athletes at moderate elevations common to endurance training camps. The present study aimed to determine whether 4 weeks of classical altitude training affects RMR in middle-distance runners. Ten highly trained athletes were recruited for 4 weeks of endurance training undertaking identical programs at either 2200m in Flagstaff, Arizona (ALT, n = 5) or 600m in Canberra, Australia (CON, n = 5). RMR, anthropometry, energy intake, and hemoglobin mass (Hbmass) were assessed pre- and posttraining. Weekly run distance during the training block was: ALT 96.8 ± 18.3km; CON 103.1 ± 5.6km. A significant interaction for Time*Group was observed for absolute ( (F-statistic, p-value: F(1,8)=13.890, p = .01) and relative RMR (F(1,8)=653.453, p = .003) POST-training. No significant changes in anthropometry were observed in either group. Energy intake was unchanged (mean ± SD of difference, ALT: 195 ± 3921kJ, p = .25; CON: 836 ± 7535kJ, p = .75). A significant main effect for time was demonstrated for total Hbmass (g) (F(1,8)=13.380, p = .01), but no significant interactions were observed for either variable [Total Hbmass (g): F(1,8)=1.706, p = .23; Relative Hbmass ( F(1,8)=0.609, p = .46]. These novel findings have important practical application to endurance athletes routinely training at moderate altitude, and those seeking to optimize energy management without compromising training adaptation. Altitude exposure may increase RMR and enhance training adaptation,. During training camps at moderate altitude, an increased energy intake is likely required to support an increased RMR and provide sufficient energy for training and performance.

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Avish P. Sharma, Philo U. Saunders, Laura A. Garvican-Lewis, Brad Clark, Jamie Stanley, Eileen Y. Robertson and Kevin G. Thompson


To determine the effect of training at 2100-m natural altitude on running speed (RS) during training sessions over a range of intensities relevant to middle-distance running performance.


In an observational study, 19 elite middle-distance runners (mean ± SD age 25 ± 5 y, VO2max, 71 ± 5 mL · kg–1 · min–1) completed either 4–6 wk of sea-level training (CON, n = 7) or a 4- to 5-wk natural altitude-training camp living at 2100 m and training at 1400–2700 m (ALT, n = 12) after a period of sea-level training. Each training session was recorded on a GPS watch, and athletes also provided a score for session rating of perceived exertion (sRPE). Training sessions were grouped according to duration and intensity. RS (km/h) and sRPE from matched training sessions completed at sea level and 2100 m were compared within ALT, with sessions completed at sea level in CON describing normal variation.


In ALT, RS was reduced at altitude compared with sea level, with the greatest decrements observed during threshold- and VO2max-intensity sessions (5.8% and 3.6%, respectively). Velocity of low-intensity and race-pace sessions completed at a lower altitude (1400 m) and/or with additional recovery was maintained in ALT, though at a significantly greater sRPE (P = .04 and .05, respectively). There was no change in velocity or sRPE at any intensity in CON.


RS in elite middle-distance athletes is adversely affected at 2100-m natural altitude, with levels of impairment dependent on the intensity of training. Maintenance of RS at certain intensities while training at altitude can result in a higher perceived exertion.

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Avish P. Sharma, Philo U. Saunders, Laura A. Garvican-Lewis, Brad Clark, Marijke Welvaert, Christopher J. Gore and Kevin G. Thompson

Purpose: To determine the effect of altitude training at 1600 and 1800 m on sea-level (SL) performance in national-level runners. Methods: After 3 wk of SL training, 24 runners completed a 3-wk sojourn at 1600 m (ALT1600, n = 8), 1800 m (ALT1800, n = 9), or SL (CON, n = 7), followed by up to 11 wk of SL racing. Race performance was measured at SL during the lead-in period and repeatedly postintervention. Training volume (in kilometers) and load (session rating of perceived exertion) were calculated for all sessions. Hemoglobin mass was measured via CO rebreathing. Between-groups differences were evaluated using effect sizes (Hedges g). Results: Performance improved in both ALT1600 (mean [SD] 1.5% [0.9%]) and ALT1800 (1.6% [1.3%]) compared with CON (0.4% [1.7%]); g = 0.83 (90% confidence limits −0.10, 1.66) and 0.81 (−0.09, 1.62), respectively. Season-best performances occurred 5 to 71 d postaltitude in ALT1600/1800. There were large increases in training load from lead-in to intervention in ALT1600 (48% [32%]) and ALT1800 (60% [31%]) compared with CON (18% [20%]); g = 1.24 (0.24, 2.08) and 1.69 (0.65, 2.55), respectively. Hemoglobin mass increased in ALT1600 and ALT1800 (∼4%) but not CON. Conclusions: Larger improvements in performance after altitude training may be due to the greater overall load of training in hypoxia compared with normoxia, combined with a hypoxia-mediated increase in hemoglobin mass. A wide time frame for peak performances suggests that the optimal window to race postaltitude is individual, and factors other than altitude exposure per se may be important.

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Gareth N. Sandford, Simon A. Rogers, Avish P. Sharma, Andrew E. Kilding, Angus Ross and Paul B. Laursen

Purpose: Anaerobic speed reserve (ASR), defined as the speed range from velocity associated with maximal oxygen uptake (vVO2max) to maximal sprint speed, has recently been shown to be an important tool for middle-distance coaches to meet event surge demands and inform on the complexity of athlete profiles. To enable field application of ASR, the relationship between gun-to-tape 1500-m average speed (1500v) and the vVO2max for the determination of lower landmark of the ASR was assessed in elite middle-distance runners. Methods: A total of 8 national and 4 international middle-distance runners completed a laboratory-measured vVO2max assessment within 6 wk of a nonchampionship 1500-m gun-to-tape race. ASR was calculated using both laboratory-derived vVO2max (ASR-LAB) and 1500v (ASR-1500v), with maximal sprint speed measured using radar technology. Results: 1500v was on average +2.06 ± 1.03 km/h faster than vVO2max (moderate effect, very likely). ASR-LAB and ASR-1500v mean differences were −2.1 ± 1.5 km/h (large effect, very likely). 1500v showed an extremely large relationship with vVO2max, r = .90 ± .12 (most likely). Using this relationship, a linear-regression vVO2max-estimation equation was derived as vVO2max (km/h) = (1500v [km/h] − 14.921)/0.4266. Conclusions: A moderate difference was evident between 1500v and vVO2max in elite middle-distance runners. The present regression equation should be applied for an accurate field prediction of vVO2max from 1500-m gun-to-tape races. These findings have strong practical implications for coaches lacking access to a sports physiology laboratory who seek to monitor and profile middle-distance runners.