Total Energy Expenditure and ad Libitum Fluid/Nutrient Intake During a 24-Hour Mountain-Bike Event: A Case Study.

Previous studies have used the doubly labeled water method to evaluate the total energy expenditure (TEE) during Ironman, ultramarathon trail runs, and competitive road cycling. However, the technique has not been applied to a 24-hour cross-country mountain-bike event. PURPOSE: This case study aimed to measure the TEE, cycling metrics, and ad libitum nutrient/fluid intake during a 24-hour cross-country mountain-bike race. METHODS: A trained male cyclist (41 y, 74.1 kg, 172.4 cm) received an oral dose of doubly labeled water prior to the 24-hour event for the calculations of TEE and water turnover. Nude body weight and urine samples were collected prerace, during the race, and postrace. Total nutrient intake and total fluid intake in addition to cycling metrics (speed, power output, cadence, and heart rate) were continuously recorded during the event. RESULTS: The rider completed 383 km coupled with a vertical gain of 7737 m during the 24-hour event. Average speed, power, and heart rate were 16.3 (2) km·h-1, 122 (29) W, and 134 (18) beats·min-1, respectively. TEE and total nutrient intake were 41 and 23.5 MJ, respectively. Total carbohydrate intake was 1192 g with an average hourly intake of 58 (22) g·h-1. Total body weight was 75.3 and 72.3 kg prerace and postrace, respectively, with a measured ad libitum total fluid intake of 13.3 L and a water turnover of 17.2 L. CONCLUSIONS: These data provide novel insights for measures of TEE, total energy intake, and total fluid intake during an ultraendurance cross-country mountain-biking event and provide a foundation for future race/training needs.

Changes in Cost of Locomotion Are Higher after Endurance Cycling Than Running When Matched for Intensity and Duration.

INTRODUCTION: Cost of locomotion (C L ) has been shown to increase after endurance running and cycling bouts. The main purpose of this study was to compare, in the same participants, the effect of both modalities on C L when matched for relative intensity and duration. METHODS: Seventeen recreational athletes performed two incremental tests in running and cycling to determine the first ventilatory threshold then two 3-h bouts of exercise at 105% of threshold, with gas exchange measurements taken for 10 min at the start, middle and end of the 3 h to calculate C L . Neuromuscular fatigue during isometric knee extensor contractions and force-velocity profile on a cycle ergometer were assessed before and immediately after the 3-h trials. RESULTS: C L significantly increased at mid (+3.7%, P = 0.006) and end (+7.4%, P < 0.001) of exercise for cycling compared with start, whereas it did not change with time for running. Cardio-respiratory and metabolic variables changed similarly for cycling and running, therefore not explaining the time-course differences in C L between modalities. Changes in C L during cycling correlated significantly with loss of maximal force extrapolated from the force-velocity profile ( r = 0.637, P = 0.006) and changes in cadence ( r = 0.784, P < 0.001). CONCLUSIONS: The type of locomotion influences the effects of exercise on energy cost because 3 h of exercise at the same relative intensity caused a significant increase of cycling C L , and no changes in running C L . The changes in C L in cycling are likely due, at least in part, to fatigue in the locomotor muscles.

Effects of Different Pedaling Positions on Muscle Usage and Energy Expenditure in Amateur Cyclists.

BACKGROUND: Inappropriate cycling positions may affect muscle usage strategy and raise the level of fatigue or risk of sport injury. Dynamic bike fitting is a growing trend meant to help cyclists select proper bikes and adjust them to fit their ergometry. The purpose of this study is to investigate how the "knee forward of foot" (KFOF) distance, an important dynamic bike fitting variable, influences the muscle activation, muscle usage strategy, and rate of energy expenditure during cycling. METHODS: Six amateur cyclists were recruited to perform the short-distance ride test (SRT) and the graded exercise tests (GXT) with pedaling positions at four different KFOF distances (+20, 0, -20, and -40 mm). The surface electromyographic (EMG) and portable energy metabolism systems were used to monitor the muscle activation and energy expenditure. The outcome measures included the EMG root-mean-square (RMS) amplitudes of eight muscles in the lower extremity during the SRT, the regression line of the changes in the EMG RMS amplitude and median frequency (MF), and the heart rate and oxygen consumption during the GXT. RESULTS: Our results revealed significant differences in the muscle activation of vastus lateralis, vastus medialis, and semitendinosus among four different pedaling positions during the SRT. During GXT, no statistically significant differences in muscle usage strategy and energy expenditure were found among different KFOF. However, most cyclists had the highest rate of energy expenditure with either KFOF at -40 mm or 20 mm. CONCLUSIONS: The KFOF distance altered muscle activation in the SRT; however, no significant influence on the muscle usage strategy was found in the GXT. A higher rate of energy expenditure in the extreme pedaling positions of KFOF was observed in most amateur cyclists, so professional assistance for proper bike fitting was recommended.

Correlation between economy/efficiency and mountain biking cross-country race performance.

This study investigated the correlation between cycling economy (CE) and gross efficiency (GE) in Olympic cross-country mountain biking (XCO-MTB) race performance. Also was examined the correlation between CE, GE, and peak oxygen uptake (VO2peak). Sixteen male XCO-MTB athletes (30.9 ± 5.2 years, 68.7 ± 5.6 kg, 175.0 ± 5.7 cm, and VO2peak: 65.4 ± 4.9 mL·kg-1 min-1) completed two experimental sessions. On the first, anthropometric assessments and a maximal incremental test were performed. The maximal incremental test was performed in the cycle ergometer to determine VO2peak, CE, and GE. A week later, an XCO-MTB race was performed in the second visit, where the official race time was used as a performance indicator. An inverse, significant moderate correlation was found between race time (8318.3 ± 459.0 s) and both CE (r = -0.53; CI95% = -0.84 to -0.10; p = 0.0008), and GE (r = -0.67; CI95% = -0.89 to -0.22; p = 0.0001). However, the moderate correlation between CE and race time showed low power. No significant correlation was found between VO2peak and either CE (r = -0.45; CI95% = -0.77-0.06; p = 0.08) or GE (r = -0.47; CI95% = -0.78-0.04; p = 0.07). In conclusion, gross efficiency is an important component of XCO-MTB race performance. The VO2peak was not related to CE and GE. The evaluation of GE may be a useful addition to the battery of physiological tests in mountain bikers.Highlights The gross efficiency can be a performance indicator related to the Olympic cross-country mountain biking race;The cycling economy has a moderate association with race time, but its use as a measure related to Olympic cross-country mountain biking race performance should be carried out with caution;Despite VO2peak's influence on both cycling economy and gross efficiency measures, our results do not show a relationship with Olympic cross-country mountain biking athletes.

Training volume and amateur cyclists' health: a six-month follow-up from coinciding with a high-demand cycling event.

This study aimed to analyse the longitudinal association of amateur cycling training volume with health by comparing the proximity of participation in a high-demand cycling event. Variations in cycling training volume, behavioural cardiometabolic risk factors, and physical and psychosocial health were examined. Cyclists decreased their training volume by approximately 40% and their total physical activity volumes by approximately 20%, while controls maintained (~5%). A time*group interaction was found for men's physical conditioning, body mass index and anxiety and, independent of gender, for behavioural cardiometabolic risk factors. Variation in cycling training volume was positively correlated with variation in physical conditioning and total physical activity and negatively correlated with variation in body mass index. The high level of cycling training volume developed at the time coinciding with a high demand cycling event predisposes to better physical health and behavioural cardiometabolic risk factors, without negatively affect psychosocial health, compared with six month later.

The Effect of Upper-Body Positioning on the Aerodynamic-Physiological Economy of Time-Trial Cycling.

PURPOSE: Cycling time trials (TTs) are characterized by riders' adopting aerodynamic positions to lessen the impact of aerodynamic drag on velocity. The optimal performance requirements for TTs likely exist on a continuum of rider aerodynamics versus physiological optimization, yet there is little empirical evidence to inform riders and coaches. The aim of the present study was to investigate the relationship between aerodynamic optimization, energy expenditure, heat production, and performance. METHODS: Eleven trained cyclists completed 5 submaximal exercise tests followed by a TT. Trials were completed at hip angles of 12° (more horizontal), 16°, 20°, 24° (more vertical), and their self-selected control position. RESULTS: The largest decrease in power output at anaerobic threshold compared with control occurred at 12° (-16 [20] W, P = .03; effect size [ES] = 0.8). There was a linear relationship between upper-body position and heat production (R2 = .414, P = .04) but no change in mean body temperature, suggesting that, as upper-body position and hip angle increase, convective and evaporative cooling also rise. The highest aerodynamic-physiological economy occurred at 12° (384 [53] W·CdA-1·L-1·min-1, ES = 0.4), and the lowest occurred at 24° (338 [28] W·CdA-1·L-1·min-1, ES = 0.7), versus control (367 [41] W·CdA-1·L-1·min-1). CONCLUSION: These data suggest that the physiological cost of reducing hip angle is outweighed by the aerodynamic benefit and that riders should favor aerodynamic optimization for shorter TT events. The impact on thermoregulation and performance in the field requires further investigation.

Crank length alters kinematics and kinetics, yet not the economy of recumbent handcyclists at constant handgrip speeds.

Handcycling performance is dependent on the physiological economy of the athlete; however, handbike configuration and the biomechanical interaction between the two are also vital. The purpose of this study was to examine the effect of crank length manipulations on physiological and biomechanical aspects of recumbent handcycling performance in highly trained recumbent handcyclists at a constant linear handgrip speed and sport-specific intensity. Nine competitive handcyclists completed a 3-minute trial in an adjustable recumbent handbike in four crank length settings (150, 160, 170 & 180 mm) at 70% peak power output. Handgrip speed was controlled (1.6 m·s-1 ) across trials with cadences ranging from 102 to 85 rpm. Physiological economy, heart rate, and ratings of perceived exertion were monitored in all trials. Handcycling kinetics were quantified using an SRM (Schoberer Rad Messtechnik) powermeter, and upper limb kinematics were determined using a 10-camera VICON motion capture system. Physiological responses were not significantly affected by crank length. However, greater torque was generated (P < .0005) and peak torque occurred earlier during the push and pull phase (P ≤ .001) in longer cranks. Statistical parametric mapping revealed that the timing and orientation of shoulder flexion, shoulder abduction, and elbow extension were significantly altered in different crank lengths. Despite the biomechanical adaptations, these findings suggest that at constant handgrip speeds (and varying cadence) highly trained handcyclists may select crank lengths between 150 and 180 mm without affecting their physiological performance. Until further research, factors such as anthropometrics, comfort, and self-selected cadence should be used to facilitate crank length selection in recumbent handcyclists.

Fuelling walking and cycling: human powered locomotion is associated with non-negligible greenhouse gas emissions.

Reducing motorized transport and increasing active transport (i.e. transport by walking, cycling and other active modes) may reduce greenhouse gas (GHG) emissions and improve health. But, active modes of transport are not zero emitters. We aimed to quantify GHG emissions from food production required to fuel extra physical activity for walking and cycling. We estimate the emissions (in kgCO2e) per kilometre travelled for walking and cycling from energy intake required to compensate for increased energy expenditure, and data on food-related GHG emissions. We assume that persons who shift from passive modes of transport (e.g. driving) have increased energy expenditure that may be compensated with increased food consumption. The GHG emissions associated with food intake required to fuel a kilometre of walking range between 0.05 kgCO2e/km in the least economically developed countries to 0.26 kgCO2e/km in the most economically developed countries. Emissions for cycling are approximately half those of walking. Emissions from food required for walking and cycling are not negligible in economically developed countries which have high dietary-related emissions. There is high uncertainty about the actual emissions associated with walking and cycling, and high variability based on country economic development. Our study highlights the need to consider emissions from other sectors when estimating net-emissions impacts from transport interventions.

The Aerodynamics and Energy Cost Assessment of an Able-Bodied Cyclist and Amputated Models by Computer Fluid Dynamics.

Background and Objectives: The aim of this study was to assess and compare the drag and energy cost of three cyclists assessed by computational fluid dynamics (CFD) and analytical procedures. Materials and methods: A transradial (Tr) and transtibial (Tt) were compared to a full-body cyclist at different speeds. An elite male cyclist with 65 kg of mass and 1.72 m of height volunteered for this research with his competition cloths, helmet and bicycle with 5 kg of mass. A 3D model of the bicycle and cyclist in the upright position was obtained for numerical simulations. Upon that, two more models were created, simulating elbow and knee-disarticulated athletes. Numerical simulations by computational fluid dynamics and analytical procedures were computed to assess drag and energy cost, respectively. Results: One-Way ANOVA presented no significant differences between cyclists for drag (F = 0.041; p = 0.960; η2 = 0.002) and energy cost (F = 0.42; p = 0.908; η2 = 0.002). Linear regression presented a very high adjustment for absolute drag values between able-bodied and Tr (R2 = 1.000; Ra2 = 1.000; SEE = 0.200) and Tt (R2 = 1.00; Ra2 = 1.000; SEE = 0.160). The linear regression for energy cost presented a very high adjustment for absolute values between able-bodied and Tr (R2 = 1.000; Ra2 = 1.000; SEE = 0.570) and Tt (R2 = 1.00; Ra2 = 1.00; SEE = 0.778). Conclusions: This study suggests that drag and energy cost was lower in the able-bodied, followed by the Tr and Tt cyclists.

Improving energy expenditure estimates from wearable devices: A machine learning approach.

A means of quantifying continuous, free-living energy expenditure (EE) would advance the study of bioenergetics. The aim of this study was to apply a non-linear, machine learning algorithm (random forest) to predict minute level EE for a range of activities using acceleration, physiological signals (e.g., heart rate, body temperature, galvanic skin response), and participant characteristics (e.g., sex, age, height, weight, body composition) collected from wearable devices (Fitbit charge 2, Polar H7, SenseWear Armband Mini and Actigraph GT3-x) as potential inputs. By utilising a leave-one-out cross-validation approach in 59 subjects, we investigated the predictive accuracy in sedentary, ambulatory, household, and cycling activities compared to indirect calorimetry (Vyntus CPX). Over all activities, correlations of at least r = 0.85 were achieved by the models. Root mean squared error ranged from 1 to 1.37 METs and all overall models were statistically equivalent to the criterion measure. Significantly lower error was observed for Actigraph and Sensewear models, when compared to the manufacturer provided estimates of the Sensewear Armband (p < 0.05). A high degree of accuracy in EE estimation was achieved by applying non-linear models to wearable devices which may offer a means to capture the energy cost of free-living activities.

Built environment changes and active transport to school among adolescents: BEATS Natural Experiment Study protocol.

INTRODUCTION: Natural experiments are considered a priority for examining causal associations between the built environment (BE) and physical activity (PA) because the randomised controlled trial design is rarely feasible. Few natural experiments have examined the effects of walking and cycling infrastructure on PA and active transport in adults, and none have examined the effects of such changes on PA and active transport to school among adolescents. We conducted the Built Environment and Active Transport to School (BEATS) Study in Dunedin city, New Zealand, in 2014-2017. Since 2014, on-road and off-road cycling infrastructure construction has occurred in some Dunedin neighbourhoods, including the neighbourhoods of 6 out of 12 secondary schools. Pedestrian-related infrastructure changes began in 2018. As an extension of the BEATS Study, the BEATS Natural Experiment (BEATS-NE) (2019-2022) will examine the effects of BE changes on adolescents' active transport to school in Dunedin, New Zealand. METHODS AND ANALYSIS: The BEATS-NE Study will employ contemporary ecological models for active transport that account for individual, social, environmental and policy factors. The published BEATS Study methodology (surveys, accelerometers, mapping, Geographic Information Science analysis and focus groups) and novel methods (environmental scan of school neighbourhoods and participatory mapping) will be used. A core component continues to be the community-based participatory approach with the sustained involvement of key stakeholders to generate locally relevant data, and facilitate knowledge translation into evidence-based policy and planning. ETHICS AND DISSEMINATION: The BEATS-NE Study has been approved by the University of Otago Ethics Committee (reference: 17/188). The results will be disseminated through scientific publications and symposia, and reports and presentations to stakeholders. TRIAL REGISTRATION NUMBER: ACTRN12619001335189.

Running economy and effort after cycling: Effect of methodological choices.

Prior exercise can negatively affect movement economy of a subsequent task. However, the impact of cycling exercise on the energy cost of subsequent running is difficult to ascertain, possibly because of the use of different methods of calculating economy. We examined the influence of a simulated cycling bout on running physiological cost (running economy, heart rate and ventilation rates) and perceptual responses (ratings of perceived exertion and effort) by comparing two running bouts, performed before and after cycling using different running economy calculation methods. Seventeen competitive male triathletes ran at race pace before and after a simulated Olympic-distance cycling bout. Running economy was calculated as V̇O2 (mL∙kg-1∙min-1), oxygen cost (EO2, mL∙kg-1∙m-1) and aerobic energy cost (Eaer, J∙kg-1∙m-1). All measures of running economy and perceptual responses indicated significant alterations imposed by prior cycling. Despite a good level of agreement with minimal bias between calculation methods, differences (p < 0.05) were observed between Eaer and both V̇O2 and EO2. The results confirmed that prior cycling increased physiological cost and perceptual responses in a subsequent running bout. It is recommended that Eaer be calculated as a more valid measure of running economy alongside perceptual responses to assist in the identification of individual responses in running economy following cycling.

Understanding the contribution of public- and restricted-access places to overall and domain-specific physical activity among Mexican adults: A cross-sectional study.

Latin Americans engage in physical activity (PA) in unique ways and use a wider range of places for PA than those commonly studied in high-income settings. We examined the contribution of a variety of places and domains of PA to meeting PA recommendations among a sample of adults (18-65 y) from all over Mexico. This was a cross-sectional study conducted in 2017 (n = 3 686). Overall and domain-specific PA was measured using the Global Physical Activity Questionnaire. Use of places for PA was self-reported. Places were classified as private or public. In 2018, associations between specific places and meeting PA recommendations (≥150 mins/week) were estimated using multivariate logistic regression models. In total 72.1% met PA recommendations. The proportion meeting recommendations through domain-specific PA was highest for leisure-time PA (50.0%), followed by travel-related (39.1%) and work-related (24.9%) PA. The most commonly reported places for PA were home (43%), parks (40.7%) and streets (39.4%) (public). Use of most public places was positively associated with meeting PA recommendations, mainly through travel-related PA (Streets OR 2.05 [95% CI 1.71-2.45]; Cycling paths OR 1.91 [1.37-2.68]). Using private places was more strongly associated with PA, mainly leisure-time PA (Gyms OR 9.66 [7.34-12.70]); Sports facilities OR 5.03 [3.27-7.74]). In conclusion, public and private places were important contributors to PA. While public places may be a powerful setting for PA promotion, increasing the equitable access for all to private places may also represent an effective strategy to increase PA among Mexican adults.

How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies.

OBJECTIVE: To determine the accuracy of wrist and arm-worn activity monitors' estimates of energy expenditure (EE). DATA SOURCES: SportDISCUS (EBSCOHost), PubMed, MEDLINE (Ovid), PsycINFO (EBSCOHost), Embase (Ovid) and CINAHL (EBSCOHost). DESIGN: A random effects meta-analysis was performed to evaluate the difference in EE estimates between activity monitors and criterion measurements. Moderator analyses were conducted to determine the benefit of additional sensors and to compare the accuracy of devices used for research purposes with commercially available devices. ELIGIBILITY CRITERIA: We included studies validating EE estimates from wrist-worn or arm-worn activity monitors against criterion measures (indirect calorimetry, room calorimeters and doubly labelled water) in healthy adult populations. RESULTS: 60 studies (104 effect sizes) were included in the meta-analysis. Devices showed variable accuracy depending on activity type. Large and significant heterogeneity was observed for many devices (I2 >75%). Combining heart rate or heat sensing technology with accelerometry decreased the error in most activity types. Research-grade devices were statistically more accurate for comparisons of total EE but less accurate than commercial devices during ambulatory activity and sedentary tasks. CONCLUSIONS: EE estimates from wrist and arm-worn devices differ in accuracy depending on activity type. Addition of physiological sensors improves estimates of EE, and research-grade devices are superior for total EE. These data highlight the need to improve estimates of EE from wearable devices, and one way this can be achieved is with the addition of heart rate to accelerometry. PROSPEROREGISTRATION NUMBER: CRD42018085016.

Energy Expenditure Equation Choice: Effects on Cycling Efficiency and its Reliability.

PURPOSE: There are several published equations to calculate energy expenditure (EE) from gas exchanges. The authors assessed whether using different EE equations would affect gross efficiency (GE) estimates and their reliability. METHODS: Eleven male and 3 female cyclists (age 33 [10] y; height: 178 [11] cm; body mass: 76.0 [15.1] kg; maximal oxygen uptake: 51.4 [5.1] mL·kg-1·min-1; peak power output: 4.69 [0.45] W·kg-1) completed 5 visits to the laboratory on separate occasions. In the first visit, participants completed a maximal ramp test to characterize their physiological profile. In visits 2 to 5, participants performed 4 identical submaximal exercise trials to assess GE and its reliability. Each trial included three 7-minute bouts at 60%, 70%, and 80% of the gas exchange threshold. EE was calculated with 4 equations by Péronnet and Massicotte, Lusk, Brouwer, and Garby and Astrup. RESULTS: All 4 EE equations produced GE estimates that differed from each other (all P < .001). Reliability parameters were only affected when the typical error was expressed in absolute GE units, suggesting a negligible effect-related to the magnitude of GE produced by each EE equation. The mean coefficient of variation for GE across different exercise intensities and calculation methods was 4.2%. CONCLUSIONS: Although changing the EE equation does not affect GE reliability, exercise scientists and coaches should be aware that different EE equations produce different GE estimates. Researchers are advised to share their raw data to allow for GE recalculation, enabling comparison between previous and future studies.

Barriers and Motivators of Bicycling by Gender Among Older Adult Bicyclists in the Midwest.

Introduction. Physical activity (PA), particularly low-impact activities like bicycling, can improve health in older adults. However, bicycling rates are lower in the Midwest than other regions in the United States. Therefore, it is important to identify unique social, personal, and environmental factors that inhibit or promote bicycling, and how these are associated with PA. The influences of these factors were explored using the social ecological model. Method. A cross-sectional online survey was developed using previously validated local and national bicycling questionnaires, then distributed to Midwestern bicyclists 50 years and older. Exploratory factor analysis was conducted to understand the influences of social, personal, and environmental barriers and promoters on bicycling patterns. All models were conducted separately by gender, and accounted for age, race, education, marital status, income, and employment. Results. Social promoters (B = 0.386, p = .002), such as having friends/family that bicycle were associated with greater PA. Personal promoters (B = -0.311, p = .006) such as needing to lose weight were associated with reduced PA. Environmental factors had no associations with PA. However, individual environmental components, such as number of vehicles on the roads, were significantly associated with PA for both males and females. Females reported more barriers than males. The overall model accounted for 16.1% of the total variance in PA levels. Conclusion. Interventions to promote PA via bicycling in older adults should focus on social factors, while also reducing personal-level factors for males. Interventions for females could focus on reducing specific personal, social, and environmental barriers.

Horizontal Crank Position Affects Economy and Upper Limb Kinematics of Recumbent Handcyclists.

PURPOSE: To determine the effects of horizontal crank position on economy and upper limb kinematics in recumbent handcycling. METHODS: Fifteen trained handcyclists performed trials at 50% and 70% of their peak aerobic power output (POPeak), determined during a maximal exercise test, in each horizontal crank position. Four horizontal crank positions, 94%, 97%, 100%, and 103% of arm length, were investigated. Horizontal crank positions were defined as the distance between the acromion angle to the center of the handgrip, while the crank arm was parallel to the floor and pointing away from the participant. Economy and upper limb kinematics were calculated during the final minute of each 3-min trial. RESULTS: Horizontal crank position significantly affected handcycling economy at 70% POPeak (P < 0.01) but not at 50% POPeak (P = 0.44). The 97% horizontal crank position (16.0 [1.5] mL·min·W) was significantly more economical than the 94% (16.7 (1.9) mL·min·W) (P = 0.04) and 103% (16.6 (1.7) mL·min·W) (P < 0.01) positions. The 100% horizontal crank position (16.2 (1.7) mL·min·W) was significantly more economical than the 103% position (P < 0.01). Statistical parametric mapping indicated that an increase in horizontal crank position, from 94% to 103%, caused a significant increase in elbow extension, shoulder flexion, adduction, internal rotation, scapular internal rotation, wrist flexion, clavicle depression and clavicle protraction between 0% and 50% (0°-180°) of the cycle (P < 0.05). CONCLUSIONS: Positioning the cranks at 97% to 100% of the athletes' arm length improved handcycling economy at 70% POPeak as, potentially, the musculature surrounding the joints of the upper limb were in a more favorable position to produce force economically.

Assessment of the physical fitness of road cyclists in the step and ramp protocols of the incremental test.

BACKGROUND: The incremental test in laboratory conditions is a method commonly used to evaluate the maximal oxygen uptake and peak power output, which are the good predictors of cycling performance. But the best-designed protocol remains unknown. Therefore, the aim of this study was to examine the physiological and biochemical responses in the incremental ramp on cycle ergometer and to compare with the commonly used step in young road cyclists. METHODS: Fifty-seven road cyclists took part in the experiment. The tests included two visits to the laboratory during which the anthropometric measurements, incremental test on a cycle ergometer, and examination of acid-base balance and blood lactate concentration were made. A randomly selected half of the subjects made, as the first one, the STEP (50W·3min-1) Test and the RAMP Test (~0,27W·sec-1) a week later. The remaining cyclists made tests in the reverse order. RESULTS: The peak power output obtained in the RAMP was significantly higher than obtained in the STEP by 18.13W (P<0.05). The maximal oxygen uptake was higher by 1.5 (mL∙kg-1∙min-1) during the RAMP (P<0.05). The postexercise blood lactate concentration was significantly higher by 0.94 mmol∙L-1(P<0.05) in STEP. CONCLUSIONS: We recommend the use of RAMP Test with linearly increasing workload to determine peak power output, maximal oxygen uptake and ventilatory threshold to precisely programming and control training of young road cyclists.

Energy Expenditure during Extreme Endurance Exercise: The Giro d'Italia.

PURPOSE: Little data are available on doubly labeled water (DLW) assessed total daily energy expenditure (TDEE) during extreme endurance exercise. Doubly labeled water is considered the gold standard to measure TDEE, but different calculations are being used, which may have a large impact on the results. The aim of the current study was to measure TDEE during the Giro d'Italia and apply two different calculation methods. METHODS: Seven male cyclists (age, 28 ± 5 yr; body mass index, 22.1 ± 2.1 kg·m) completed the 24-d professional cycling race "Giro d'Italia" in which a total distance of 3445 km was covered, including 10 mountain stages. Total daily energy expenditure was measured over the entire duration of the race, with the ingestion of DLW at three different time points. To calculate TDEE and body composition, the isotope dilution space was calculated using two different techniques, the "plateau" and "intercept" technique. RESULTS: The %fat mass at baseline was 7.8% and 16.8% with the plateau and intercept technique respectively and did not significantly change over the course of the race. Total daily energy expenditure was on average 32.3 ± 3.4 MJ·d using the plateau technique versus 28.9 ± 3.2 using the intercept technique, resulting in an average physical activity level (PAL) of 4.37 ± 0.43 versus 3.91 ± 0.39, respectively. The dilution space ratio was on average 1.030 with the plateau and 1.060 with the intercept technique. CONCLUSIONS: Given that the observed dilution space ratio with the plateau technique is similar as the expected ratio from literature and the % fat mass of 7.8% is more realistic for the athletes being studied, we propose the application of the plateau rather than the intercept method, when using DLW during extreme endurance exercise.