Recently, a new automated carbon monoxide (CO) rebreathing method (aCO) to estimate haemoglobin mass (Hb; mass; ) was introduced. The aCO method uses the same CO dilution principle as the widely used optimised CO rebreathing method (oCO). The two methods differ in terms of CO administration, body position, and rebreathing time. Whereas with aCO, CO is administered automatically by the system in a supine position of the subject, with oCO, CO is administered manually by an experienced operator with the subject sitting. Therefore, the aim of this study was to quantify possible differences in Hb; mass; estimated with the two methods. Hb; mass; was estimated in 18 subjects (9 females, 9 males) with oCO using capillary blood samples (oCOc) and aCO taking simultaneously venous blood samples (aCOv) and capillary blood samples (aCOc). Overall, Hb; mass; was different between the three measurement procedures (; F; = 57.55,; p;
It is unknown, whether endurance training stimulates hemoglobin mass (Hbmass) and maximal oxygen uptake (V˙O2max) increases during late adolescence. Therefore, this study assessed the influence of endurance training on Hbmass, blood volume parameters, and V˙O2max in endurance athletes and control subjects from age 16 to 19 yr.; Hemoglobin mass, blood volume parameters, V˙O2max and anthropometric parameters were measured in male elite endurance athletes from age 16 to 19 yr in 6-month intervals (n = 10), as well as in age-matched male controls (n = 12).; Neither the level of Hbmass per lean body mass (LBM) (P = 0.80) nor the development of Hbmass during the 3 yr (P = 0.97) differed between athletes and controls. Hbmass at age 16 yr was 13.24 ± 0.89 g·kg LBM and increased by 0.74 ± 0.58 g·kg LBM (P < 0.01) from age 16 to 19 yr. There was a high correlation between Hbmass at age 16 and 19 yr (r = 0.77; P < 0.001). Plasma volume, blood volume, and V˙O2max were higher in athletes compared to controls (P < 0.05). Blood volume and V˙O2max increased with age (P < 0.01, similarly in both groups).; Endurance training volumes do not explain individual differences in Hbmass levels nor Hbmass and V˙O2max development in the age period from 16 to 19 yr. The higher V˙O2max levels of athletes may be partially explained by training-induced higher plasma and blood volumes, as well as other training adaptations. Since Hbmass at age 16 yr varies substantially and the development of Hbmass in late adolescence is comparably small and not influenced by endurance training, Hbmass at age 16 yr is an important predictor for Hbmass at adult age and possibly for the aptitude for high-level endurance performance.
The rim width of cross-country mountain bike wheel sets has increased in recent years, but the effect of this increase on performance remains unknown. The aim of this study was to analyse the influence of rim width on rolling resistance and off-road speed. We compared 3 tubeless wheel sets: 25 mm inner width as baseline, 30 mm width with the same tyre stiffness, and 30 mm width with the same tyre pressure. Three riders conducted 75 rolling resistance tests for each wheel set on a cross-country course. We determined rolling resistance using the virtual elevation method and calculated off-road speeds for flat and uphill conditions using a mathematical model. Baseline rolling resistance (C; r; ) was 0.0298, 90% CI [0.0286, 0.0310], which decreased by 1.4%, [0.7, 2.2] with the wider rim and the same tyre stiffness and increased by 0.9%, [0.1, 1.6] with the wider rim and the same tyre pressure. The corresponding effects on off-road speed were most likely trivial (0.0% to 0.7% faster and 0.1% to 0.6% slower, respectively). Because the effect of rim width on off-road speed seems negligible, athletes should choose the rim width that offers the best bike handling and should experiment with low tyre pressures.
Hemoglobin mass does not change over years in Swiss male elite endurance athletes Theoretical background In aerobic sport disciplines – such as cross-country skiing or mountainbiking - a main important factor determining aerobic performance is the total amount of hemoglobin, hemoglobin mass (Hbmass). Since endurance athletes are characterized by an about 35% higher Hbmass than untrained subjects, the question arise if this is due to endurance training over years or other factors like genetic predisposition. Very little is known about the Hbmass changes with training over years. From cross sectional data from athletes at age 23 and age 28 (2) as well as Hbmass data measured over one training year (1), it can be hypothesized there is no relevant Hbmass increase over years (3). Research question Does Hbmass in Swiss national team endurance athletes change with several years of endurance training? Methods We retrospectively filtered body weight related Hbmass values (CO-rebreathing), measured during standard performance testing of the Swiss national cross-country and mountain bike teams twice a year, with the athlete inclusion criteria: male, age > 23 yrs, minimum measurement duration three years and/or at least six measurements. 22 Athletes fulfilled the criteria and were included in the analyses. The average number of measurements was 10.8 ± 4.5 over a period of 5.1 ± 2.1 years. For every athlete mean of the two first and mean of two last measurements were compared and an individual linear model for the development of Hbmass with age was fitted. Individual models were combined to one linear model by averaging all individual slopes and axis sections. All values are mean ± SD. Results There was no difference in mean absolute Hbmass (1058 ± 93 vs 1069 ± 93g; p=0.48) and mean relative Hbmass (14.49 ± 0.88 vs 14.64 ± 0.97g/kg bodyweight; p=0.32) between pre- and post-measurements. The mean linear model was: Hbmass = 0.009 (± 0.12) · age + 14.3 (± 3.2). Discussion Our results show, that for elite endurance athletes older than 23 years no substantial increase in Hbmass can be expected with sea-level training over the years despite high training loads usually accomplished by these athletes. References Prommer N, Sottas PE, Schoch C, Schumacher YO, and Schmidt W. Total Hemoglobin Mass - A New Parameter to Detect Blood Doping? Med Sci Sport Exerc 40: 2112-2118, 2008. Steiner T, and Wehrlin JP. Does Hemoglobin Mass Increase from Age 16 to 21 and 28 in Elite Endurance Athletes. Med Sci Sport Exerc 43: 1735-1743, 2011. Wehrlin JP, Marti B, and Hallén J. Hemoglobin Mass and Aerobic Performance at Moderate Altitude in Athletes. Adv Exp Med Biol 357-375, 2016.
Hemoglobin mass response to normobaric and hypobaric altitude training in senior male athletesTheoretical BackgroundOne main physiological adaptation to altitude training is an increase in hemoglobin mass (Hbmass). Recently, a meta-analysis has calculated that an increase in Hbmass of ~1.1%/100 h of hypoxic exposure at ≥2100 m can be expected (1). During the last decades, several types of altitude training have been developed, which can be performed under either hypobaric hy-poxia (HH) or normobaric hypoxia (NH). Whether NH and HH can be used equally for an alti-tude training camp on Hbmass adaptations is still unclear.Research QuestionsDoes normobaric and hypobaric altitude training evoke similar Hbmass responses and is there a substantial inter-individual variability in Hbmass response?MethodsTo compare mean and individual Hbmass responses during an 18-day live high-train low (LHTL) altitude training camp in either NH or HH, we designed a randomized matched con-trolled (n=28) (2) and a crossover (n=15) (3) study with endurance athletes. To more precisely quantify the individual Hbmass response to altitude training, we implemented error-reducing duplicate Hbmass measures. Furthermore, the hypothesis that athletes with a high initial Hbmass starting an altitude sojourn will have a limited ability to further increase their post-altitude Hbmass in endurance and team-sport athletes (n=58) was tested (4).ResultsHbmass increased similarly in HH (+4.4% and +4.5%, p
Hemoglobin mass and endurance performance in elite sportPerformance and maximal oxygen uptake (VO2max) in endurance sports is mainly limited by the oxygen supply to active muscle. Since total amount of hemoglobin (Hbmass) determines in large part the oxygen transport capacity of the blood, Hbmass is a main limiting factor for endurance performance. The importance of a high Hbmass in endurance athletes is also shown by the problem of blood doping in elite sport. It is well known, that senior elite endurance athletes are characterized by about 35% higher Hbmass than untrained individuals. From a sport practical point of view, therefore several key-questions arise: 1) Does Hbmass in senior endurance athletes incresase with endurance training over years? 2) Does Hbmass increase more in adolescent endurance athletes with a high load of endurance training than in control subjects between age 16 and 18.5 yrs? 3) Does normobaric and hypobaric altitude training in senior athletes evoke similar Hbmass responses and is there a substantial inter-individual var-iability in Hbmass response? In the three presentations of our session, these key-questions will be answered and an outlook for further investigations in this relevant field for endurance performance will be addressed.
Effect of endurance training on the development of hemoglobin mass in male adolescent endurance athletesIt is well known, that adult elite endurance athletes are characterized by about 30-40% higher hemoglobin mass (Hbmass) than untrained subjects (1). However, it is unclear, whether this is due to endurance training, a better genetic predisposition of the athletes combined with a selection process, or other factors (2). Interestingly, Hbmass at age 16 years (yrs) is reported to be not different between endurance athletes and untrained subjects (3).Research QuestionDoes Hbmass increase more in adolescent endurance athletes with a high load of endurance training than in control subjects between age 16 and 18.5yrs?Methods:We measured Hbmass (CO-rebreathing) in 10 Swiss National Team endurance athletes (AG: cross-country skiers and triathletes) as well as in 12 age matched non endurance training controls (CG) every 0.5 yrs six times from age 16 to age 18.5yrs (T1 - T6) with the optimized carbon monoxide re-breathing technique.ResultsHbmass increased (p
Vorhersage von Treffern in Biathlonwettkämpfen mit maschinellem LernenTheoretischer HintergrundSchiessfehler in Biathlonwettkämpfen wirken sich bedeutend auf das Schlussklassement aus. Der erschwerende Effekt der vorangehenden körperlichen Belastung sowie biomechanische Einflussfaktoren auf die Trefferquote wurden bereits untersucht (Hoffman, Gilson, Westenburg, & Spencer, 1992; Sattlecker, Buchecker, Gressenbauer, Müller, & Lindinger, 2017). Al-lerdings ist bisher unbekannt, ob und wie genau sich einzelne Treffer und Fehlschüsse vorhersagen lassen. Für automatische Vorhersagen eignen sich Algorithmen aus dem maschi-nellen Lernen, welche komplexe Zusammenhänge aus gegebenen Daten generalisieren, um Vorhersagen für neue Fälle zu berechnen (Bauer & Kohavi, 1999).FragestellungenA) Welche Faktoren beeinflussen die Trefferquoten in Biathlonwettkämpfen?B) Wie gut lassen sich zukünftige Treffer und Fehlschüsse mit maschinellem Lernen vorhersagen?MethodeWir aggregierten und untersuchten Daten von 118‘300 Schüssen aus vier Wettkampfsaisons (2012/13 bis 2015/16) mittels explorativer Datenanalyse und trainierten verschiedene Vorher-sagemodelle aus dem maschinellen Lernen mittels zeitsegmentierter Kreuzvalidierung. Als Basismodell diente eine logistische Regression mit einer Eingangsvariablen. Zusätzlich wurden zwei komplexe Modelle verwendet: ein Boosting-Modell basierend auf Entscheidungsbäumen und ein künstliches neuronales Netzwerk. Mit den finalen Modellen berechneten wir Vorhersagen für 34‘340 zukünftige Schüsse der nächsten Wettkampfsaison (2016/17). ErgebnisseA) Tiefere Trefferquoten zeigten sich in den Disziplinen Sprint und Verfolgung verglichen mit den Disziplinen Einzel und Massenstart (p < 0.01, Cohen‘s h = 0.14). Im Stehendschiessen war die Trefferquote tiefer als im Liegendschiessen (p < 0.01, h = 0.15). Im Vergleich zu den anderen Schüssen in der gleichen Position zeigte der erste Liegendschuss und der fünfte Stehendschuss eine tiefere Trefferquote (p < 0.01, h = 0.08 und p < 0.05, h = 0.05). B) Das Boosting-Modell prognostizierte zukünftige Treffer und Fehlschüsse mit einer Fläche unter der ROC-Kurve von 0.62, 95% VI [0.60, 0.63], leicht besser als das künstliche neuronale Netzwerk (0.61, [0.60, 0.62], p < 0.01) und die logistische Regression (0.60, [0.59, 0.61], p < 0.01, Eingangsvariable: vorgängige positionsspezifische Trefferquote).DiskussionDie Trefferquote im Biathlon variiert zwischen den Disziplinen, den Schiesspositionen und den Schussnummern einer Serie. Die vorgängige positionsspezifische Trefferquote eines Athleten oder einer Athletin ist aber der wichtigste Faktor, um einzelne Treffer vorherzusagen. Ein gros-ser Zufallseffekt bleibt bestehen, den auch komplexe Modelle nicht relevant verringern können: Die Anzahl der Fehlschüsse eines Athleten oder einer Athletin pro Wettkampf variiert zufällig um ca. 1-2 Schüsse.Im Training sollte somit primär die allgemeine Trefferquote in beiden Schiesspositionen unter wettkampfnahen Bedingungen optimiert werden, evtl. mit einem besonderen Fokus auf dem ersten Liegendschuss und dem letzten Stehendschuss. Echtzeitvorhersagen der Trefferwahr-scheinlichkeiten einzelner Schüsse könnten zudem Wettkampfübertragungen bereichern.ReferenzenBauer, E., & Kohavi, R. (1999). An empirical comparison of voting classification algorithms: Bagging, boosting, and variants. Machine Learning, 36(1), 105-139.Hoffman, M. D., Gilson, P. M., Westenburg, T. M., & Spencer, W. A. (1992). Biathlon shooting performance after exercise of different intensities. International Journal of Sports Medicine, 13(3), 270-273.Sattlecker, G., Buchecker, M., Gressenbauer, C., Müller, E., & Lindinger, S. J. (2017). Factors discriminating high from low score performance in biathlon shooting. International Journal of Sports Physiology and Performance, 12(3), 377-384.
Effect of competition-compatible precooling on distance running in humid heatTheoretical Background:The next two major competitions in athletics will be held in Doha, Qatar (World Championships 2019) and in Tokyo, Japan (Olympic Games 2020). On both occasions, extreme environmental conditions are expected: A wet bulb globe temperature (WBGT) of ~28°C in Doha and of ~30°C in Tokyo (Murata et al., 2016), indicating “high” and “excessive” temperatures, respectively (Racinais et al., 2015). High WBGT cause a fast increase of body core temperature (CT) during exercise and therefore impair endurance performance (Nybo et al., 2014).One commonly used means against the reduction of endurance performance induced by the rise of CT is “precooling”. It aims to delay the point where critically high CT is reached by lowering CT before the onset of exercise (Ross et al., 2013). Positive effects of precooling on endurance performance have been found, especially where different cooling modalities such as cold water immersion, cooling vests and ice slurries were combined (Racinais et al., 2015).However, most of the existing studies on precooling have executed precooling directly before exercise-onset. They are thus hardly compatible with the regulatory restrictions before major athletics competitions. For example, long distance runners competing in track events (most importantly the 5000 m event) are obliged to arrive in the “call-room” ~30 min before the start of their race. In the call-room, no personal precooling instruments like cooling vests or baths are allowed. Before entering the call room, athletes typically are transferred from their hotel to the competition stadium. Also during transfer and subsequent warm-up, precooling is not pos-sible without practical and regulatory restrictions. In order to implement precooling into the predetermined schedule, it would be necessary to extend the duration between precooling and the start of the race. This would likely reduce the chance of a performance benefit, as the effect of precooling could be “washed out” before the start. However, no study has investigated the effects of best-practice precooling compatible with the schedule before major athletics compe-titions on physiological parameters and on distance running performance so far.Research Question:What are the effects of competition-compatible precooling on A) body core temperature, B) heart rate, oxygen consumption and thermal perception as well as C) performance during dis-tance running in humid heat?....
Shooting in biathlon competitions substantially influences final rankings, but the predictability of hits and misses is unknown. The aims of the current study were A) to explore factors influencing biathlon shooting performance and B) to predict future hits and misses. We explored data from 118,300 shots from 4 seasons and trained various machine learning models before predicting 34,340 future shots (in the subsequent season). A) Lower hit rates were discovered in the sprint and pursuit disciplines compared to individual and mass start (P < 0.01, h = 0.14), in standing compared to prone shooting (P < 0.01, h = 0.15) and in the 1; st; prone and 5; th; standing shot (P < 0.01, h = 0.08 and P < 0.05, h = 0.05). B) A tree-based boosting model predicted future shots with an area under the ROC curve of 0.62, 95% CI [0.60, 0.63], slightly outperforming a simple logistic regression model and an artificial neural network (P < 0.01). The dominant predictor was an athlete's preceding mode-specific hit rate, but a high degree of randomness persisted, which complex models could not substantially reduce. Athletes should focus on overall mode-specific hit rates which epitomise shooting skill, while other influences seem minor.
What is the central question of this study? It has been assumed that athletes embarking on an 'live high-train low' (LHTL) camp with already high initial haemoglobin mass (Hb; mass; ) have a limited ability to increase their Hb; mass; further post-intervention. Therefore, the relationship between initial Hb; mass; and post-intervention increase was tested with duplicate Hb; mass; measures and comparable hypoxic doses in male athletes. What is the main finding and its importance? There were trivial to moderate inverse relationships between initial Hb; mass; and percentage Hb; mass; increase in endurance and team-sport athletes after the LHTL camp, indicating that even athletes with higher initial Hb; mass; can reasonably expect Hb; mass; gains post-LHTL. It has been proposed that athletes with high initial values of haemoglobin mass (Hb; mass; ) will have a smaller Hb; mass; increase in response to 'live high-train low' (LHTL) altitude training. To verify this assumption, the relationship between initial absolute and relative Hb; mass; values and their respective Hb; mass; increase following LHTL in male endurance and team-sport athletes was investigated. Overall, 58 male athletes (35 well-trained endurance athletes and 23 elite male field hockey players) undertook an LHTL training camp with similar hypoxic doses (200-230 h). The Hb; mass; was measured in duplicate pre- and post-LHTL by the carbon monoxide rebreathing method. Although there was no relationship (r = 0.02, P = 0.91) between initial absolute Hb; mass; (in grams) and the percentage increase in absolute Hb; mass; , a moderate relationship (r = -0.31, P = 0.02) between initial relative Hb; mass; (in grams per kilogram) and the percentage increase in relative Hb; mass; was detected. Mean absolute and relative Hb; mass; increased to a similar extent (P ≥ 0.81) in endurance (from 916 ± 88 to 951 ± 96 g, +3.8%, P < 0.001 and from 13.1 ± 1.2 to 13.6 ± 1.1 g kg; -1; , +4.1%, P < 0.001, respectively) and team-sport athletes (from 920 ± 120 to 957 ± 127 g, +4.0%, P < 0.001 and from 11.9 ± 0.9 to 12.3 ± 0.9 g kg; -1; , +4.0%, P < 0.001, respectively) after LHTL. The direct comparison study using individual data of male endurance and team-sport athletes and strict methodological control (duplicate Hb; mass; measures and matched hypoxic dose) indicated that even athletes with higher initial Hb; mass; can reasonably expect Hb; mass; gain post-LHTL.
Although a low rolling resistance is advantageous in mountain bike cross-country racing, no studies have used the virtual elevation method to compare tyres from different manufacturers as used in international competitions so far. The aims of this study were to assess the reliability of this method, to compare the off-road rolling resistance between tyres and to calculate the influence on off-road speed. Nine 29-in. mountain bike cross-country tyres were tested on a course representing typical ground surface conditions 5 or 6 times. The coefficient of rolling resistance was estimated with the virtual elevation method by 3 investigators and corresponding off-road speeds were calculated. The virtual elevation method was highly reliable (typical error = 0.0006, 2.8%; limits of agreement
To compare individual hemoglobin mass (Hbmass) changes following a live high-train low (LHTL) altitude training camp under either normobaric hypoxia (NH) or hypobaric hypoxia (HH) conditions in endurance athletes.; In a crossover design with a one-year washout, 15 male triathletes randomly performed two 18-d LHTL training camps in either HH or NH. All athletes slept at 2250 m and trained at altitudes < 1200 m. Hbmass was measured in duplicate with the optimized carbon monoxide rebreathing method before (pre-) and immediately after (post-) each 18 d training camp.; Hbmass increased similarly in HH (916 to 957 g, 4.5 ± 2.2%, P < 0.001) and in NH (918 to 953 g, 3.8 ± 2.6%, P < 0.001). Hbmass changes did not differ between HH and NH (P = 0.42). There was substantial inter-individual variability among subjects to both interventions (i.e., individual responsiveness, or the individual variation in the response to an intervention free of technical noise): 0.9% in HH and 1.7% in NH. However, a correlation between intra-individual delta Hbmass changes (%) in HH and in NH (r = 0.52, P = 0.048) was observed.; HH and NH evoked similar mean Hbmass increases following LHTL. Among the mean Hbmass changes, there was a notable variation in individual Hbmass response, which tended to be reproducible.
The aim of this study was to compare the accuracy among a high number of current mobile cycling power meters used by elite and recreational cyclists against a first principle-based mathematical model of treadmill cycling. 54 power meters from 9 manufacturers used by 32 cyclists were calibrated. While the cyclist coasted downhill on a motorised treadmill, a back-pulling system was adjusted to counter the downhill force. The system was then loaded 3 times with 4 different masses while the cyclist pedalled to keep his position. The mean deviation (trueness) to the model and coefficient of variation (precision) were analysed. The mean deviations of the power meters were -0.9±3.2% (mean±SD) with 6 power meters deviating by more than±5%. The coefficients of variation of the power meters were 1.2±0.9% (mean±SD), with Stages varying more than SRM (p
The main aim of the present study was to quantify the magnitude of differences introduced when estimating a given blood volume compartment (e.g. plasma volume) through the direct determination of another compartment (e.g. red cell volume) by multiplication of venous haematocrit and/or haemoglobin concentration. However, since whole body haematocrit is higher than venous haematocrit such an approach might comprise certain errors. To test this experimentally, four different methods for detecting blood volumes and haemoglobin mass (Hb; mass; ) were compared, namely the carbon monoxide (CO) re-breathing (for Hb; mass; ), the indocyanine green (ICG; for plasma volume [PV]) and the sodium fluorescein (SoF; for red blood cell volume [RBCV]) methods. No difference between ICG and CO re-breathing derived PV could be established when a whole body/venous haematocrit correction factor of 0.91 was applied (p = 0.11, r = 0.43, mean difference -340 ± 612 mL). In contrast, when comparing RBCV derived by the CO re-breathing and the SoF method, the SoF method revealed lower RBCV values as compared to the CO re-breathing method (p
The purpose of this study was to analyse the effect of bike type – the 26-inch-wheel bike (26” bike) and the 29-inch-wheel bike (29” bike) - on performance in elite mountain bikers. Ten Swiss National Team athletes (7 male, 3 female) completed 6 trials with individual start on a simulated cross-country course with 35 minutes of active recovery between trials (3 trials on a 26” bike and 3 trials on a 29” bike, alternate order, randomised start-bike). The course consisted of two separate sections expected to favour either the 29” bike (section A) or the 26” bike (section B). For each trial performance, power output, cadence and heart rate were recorded and athletes’ experiences were documented. Mean overall performance (time: 304 ± 27 s vs. 311 ± 29 s; p < 0.01) as well as performance in section A (p < 0.001) and B (p < 0.05) were better when using the 29” bike. No significant differences were observed for power output, cadence or heart rate. Athletes rated the 29” bike as better for performance in general, passing obstacles and traction. The 29” bike supports superior performance for elite mountain bikers, even on sections supposed to favour the 26” bike.
We investigated the changes in physiological and performance parameters after a Live High-Train Low (LHTL) altitude camp in normobaric (NH) or hypobaric hypoxia (HH) to reproduce the actual training practices of endurance athletes using a crossover-designed study.; Well-trained triathletes (n = 16) were split into two groups and completed two 18-day LTHL camps during which they trained at 1100-1200 m and lived at 2250 m (P i O2 = 111.9 ± 0.6 vs. 111.6 ± 0.6 mmHg) under NH (hypoxic chamber; FiO2 18.05 ± 0.03%) or HH (real altitude; barometric pressure 580.2 ± 2.9 mmHg) conditions. The subjects completed the NH and HH camps with a 1-year washout period. Measurements and protocol were identical for both phases of the crossover study. Oxygen saturation (S p O2) was constantly recorded nightly. P i O2 and training loads were matched daily. Blood samples and VO2max were measured before (Pre-) and 1 day after (Post-1) LHTL. A 3-km running-test was performed near sea level before and 1, 7, and 21 days after training camps.; Total hypoxic exposure was lower for NH than for HH during LHTL (230 vs. 310 h; P < 0.001). Nocturnal S p O2 was higher in NH than in HH (92.4 ± 1.2 vs. 91.3 ± 1.0%, P < 0.001). VO2max increased to the same extent for NH and HH (4.9 ± 5.6 vs. 3.2 ± 5.1%). No difference was found in hematological parameters. The 3-km run time was significantly faster in both conditions 21 days after LHTL (4.5 ± 5.0 vs. 6.2 ± 6.4% for NH and HH), and no difference between conditions was found at any time.; Increases in VO2max and performance enhancement were similar between NH and HH conditions.
To compare hemoglobin mass (Hb(mass)) changes during an 18-d live high-train low (LHTL) altitude training camp in normobaric hypoxia (NH) and hypobaric hypoxia (HH).; Twenty-eight well-trained male triathletes were split into three groups (NH: n = 10, HH: n = 11, control [CON]: n = 7) and participated in an 18-d LHTL camp. NH and HH slept at 2250 m, whereas CON slept, and all groups trained at altitudes 0.08) and remained unchanged in CON (+0.2%, P = 0.89).; HH and NH evoked similar Hb(mass) increases for the same hypoxic dose and after 18-d LHTL. The wide variability in individual Hb(mass) responses in HH and NH emphasizes the importance of individual Hb(mass) evaluation of altitude training.
