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The aim of the current study was to determine if a single ParvoMedics TrueOne 2400 metabolic cart provides valid and reliable measurement of RMR in comparison with the criterion Douglas Bag method (DB). Ten endurance-trained participants completed duplicate RMR measurements on 2 consecutive days using the ParvoMedics system in exercise mode, with the same expirate analyzed using DB. Typical error (TE) in mean RMR between the systems was 578.9 kJ or 7.5% (p = .01). In comparison with DB, the ParvoMedics system over-estimated RMR by 946.7 ± 818.6 kJ. The bias between systems resulted from ParvoMedics V_E(STPD) values. A regression equation was developed to correct the bias, which reduced the difference to -83.3 ± 631.9 kJ. TE for the corrected ParvoMedics data were 446.8 kJ or 7.2% (p = .70). On Day 1, intraday reliability in mean RMR for DB was 286.8 kJ or 4.3%, (p = .54) and for ParvoMedics_uncorrected, 359.3 kJ or 4.4%, (p = .35), with closer agreement observed on Day 2. Interday reliability for DB was 455.3 kJ or 6.6% (p = .61) and for ParvoMedics_uncorrected, 390.2 kJ or 6.3% (p = .54). Similar intraday and interday TE was observed between ParvoMedics_uncorrected and ParvoMedics_corrected data. The ParvoMedics TrueOne 2400 provided valid and reliable RMR values compared with DB when the V_E(STPD) error was corrected. This will enable widespread monitoring of RMR using the ParvoMedics system in a range of field-based settings when DB is not available.

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 (Hb_mass) 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 (kJ.day^-1) (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 Hb_mass (g) (F_(1,8)=13.380, p = .01), but no significant interactions were observed for either variable [Total Hb_mass (g): F_(1,8)=1.706, p = .23; Relative Hb_mass (g.kg^-1): 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.

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.

Studies examining pacing strategies during 4000-m cycling time trials (TTs) typically ensure that participants are not prefatigued; however, competitive cyclists often undertake TTs when already fatigued. This study aimed to determine how TT pacing strategies and sprint characteristics of cyclists change during an intensified training period (mesocycle). Thirteen cyclists regularly competing in A- and B-grade cycling races and consistently training (>10 h/wk for 4 [1] y) completed a 6-wk training mesocycle. Participants undertook individually prescribed training, using training stress scores (TrainingPeaks, Boulder, CO), partitioned into a baseline week, a build week, 2 loading weeks (designed to elicit an overreached state), and 2 recovery weeks. Laboratory-based tests (15-s sprint and TT) and Recovery-Stress Questionnaire (RESTQ-52) responses were repeatedly undertaken over the mesocycle. TT power output increased during recovery compared with baseline and loading weeks (P = .001) with >6-W increases in mean power output (MPO) detected for 400-m sections (10% bins) from 1200 to 4000 m in recovery weeks. Decreases in peak heart rate (P < .001) during loading weeks and postexercise blood lactate (P = .005) during loading week 2 and recovery week 1 were detected. Compared with baseline, 15-s sprint MPO declined during loading and recovery weeks (P < .001). An interaction was observed between RESTQ-52 total stress score with a 15-s sprint (P = .003) and with a TT MPO (P = .04), indicating that participants who experienced greater stress during loading weeks exhibited reduced performance. To conclude, intensified endurance training diminished sprint performance but improved 4000-m TT performance, with a subtle change in MPO evident over the last 70% of TTs.

Purpose: To determine if a series of trials with fraction of inspired oxygen (FiO₂) content deception could improve 4000-m cycling time-trial (TT) performance. Methods: A total of 15 trained male cyclists (mean [SD] body mass 74.2 [8.0] kg, peak oxygen uptake 62 [6] mL·kg⁻¹·min⁻¹) completed six 4000-m cycling TTs in a semirandomized order. After a familiarization TT, cyclists were informed in 2 initial trials they were inspiring normoxic air (NORM, FiO₂ 0.21); however, in 1 trial (deception condition), they inspired hyperoxic air (NORM-DEC, FiO₂ 0.36). During 2 subsequent TTs, cyclists were informed they were inspiring hyperoxic air (HYPER, FiO₂ 0.36), but in 1 trial, normoxic air was inspired (HYPER-DEC). In the final TT (NORM-INFORM), the deception was revealed and cyclists were asked to reproduce their best TT performance while inspiring normoxic air. Results: Greater power output and faster performances occurred when cyclists inspired hyperoxic air in both truthful (HYPER) and deceptive (NORM-DEC) trials than NORM (P < .001). However, performance only improved in NORM-INFORM (377 W; 95% confidence interval [CI] 325–429) vs NORM (352 W; 95% CI 299–404; P < .001) when participants (n = 4) completed the trials in the following order: NORM-DEC, NORM, HYPER-DEC, HYPER. Conclusions: Cycling performance improved with acute exposure to hyperoxia. Mechanisms for the improvement were likely physiological; however, improvement in a deception trial suggests an additional placebo effect. Finally, a particular sequence of oxygen deception trials may have built psychophysiological belief in cyclists such that performance improved in a subsequent normoxic trial.

Purpose: To compare the effects of natural altitude training (NAT) and simulated (SIM) live high:train low altitude training on road-race walking performance (min), as well as treadmill threshold walking speed (km·h⁻¹) at 4 mmol·L⁻¹ and maximal oxygen consumption, at 1380 m. Methods: Twenty-two elite-level male (n = 15) and female (n = 7) race walkers completed 14 d of NAT at 1380 m (n = 7), SIM live high:train low at 3000:600 m (n = 7), or control conditions (600-m altitude; CON, n = 8). All preintervention and postintervention testing procedures were conducted at 1380 m and consisted of an incremental treadmill test, completed prior to a 5 × 2-km road-race walking performance test. Differences between groups were analyzed via mixed-model analysis of variance and magnitude-based inferences, with a substantial change detected with >75% likelihood of exceeding the smallest worthwhile change. Results: The improvement in total performance time for the 5 × 2-km test in NAT was not substantially different from SIM but was substantially greater (85% likely) than CON. The improvement in percentage decrement in the 5 × 2-km performance test in NAT was greater than in both SIM (93% likely) and CON (93% likely). The increase in maximal oxygen consumption was substantially greater (91% likely) in NAT than in SIM. Improvement in threshold walking speed was substantially greater than CON for both SIM (91% likely) and NAT (90% likely). Conclusions: Both NAT and SIM may allow athletes to achieve reasonable acclimation prior to competition at low altitude.