Seasonal changes in aerobic fitness indices in elite cyclists

Time-course Changes of Field- and Laboratory-based Performance Indicators in Junior Cyclists Through a Season

This study aimed to assess the seasonal evolution of field-based and laboratory-based performance indicators in cyclists. Thirteen Junior male road cyclists (age 17.4±0.5 years) were followed up during a season, which was divided in three phases: early season (involving mainly training sessions), mid-season (including the first competitions), and late season (including the major competitions of the season). During each phase, field-based power output data were registered for the assessment of maximum mean power values, and laboratory-based endurance (ramp test and simulated 8-minute time trial), muscle strength/power (squat, lunge, hip thrust) and body composition indicators (dual-energy X-ray absorptiometry) were also assessed. A progressive (p<0.01) increase in maximum mean power values (e.g., 3.8±0.3 and 4.5±0.4 watts/kg in early and late season, respectively, for 60-minute efforts) and on 8-minute time trial performance (i.e., 5.3±0.3 and 5.6±0.4 watts/kg, respectively) was observed through the season. Yet, more "traditional" endurance indicators (i.e., ventilatory threshold, respiratory compensation point, or maximum oxygen uptake) seemed to show a ceiling effect beyond the mid-season. In addition, neither peak power output, body composition, nor muscle strength indicators followed a similar pattern to the aforementioned field-based indicators. In summary, in Junior cyclists field-based indicators seem more sensitive to monitor endurance cyclists' changes in actual fitness and performance capacity than more "traditional" laboratory-based markers in Junior cyclists.

Go, go …. You'll be happier. Psychological variables among cyclists during COVID-19 lockdowns

COVID-19 lockdowns involved radical changes in the habits and lifestyles of many. Notably, athletes saw their training routines altered. The relationship between lockdown effects and psychological variables was analysed using a sample comprising 1032 cyclists (average age: 42.97 years, s.d. = 8.94), taking part in the first cycling competition after lockdown. The target variables included psychological variables such as frustration tolerance, subjective vitality, autonomy self-determination, and affective status, as well as sociodemographic and training habits-related variables. The results showed that the constructs under analysis are related. Pre- and post-competition psychological variables were measured, and no significant differences were detected, except concerning subjective vitality. A regression analysis model was designed to analyse the impact of frustration tolerance, autonomy self-determination, and affective status on subjective vitality. The results reveal a lineal relationship (F = 71.789, p < .001) between subjective vitality and a set of independent variables: positive affects; health status; km of training per year; and frustration tolerance, which explain 46.7% of variance. Finally, since the variable that measures subjective vitality was shown to be significant, mediation analyses were undertaken to answer our hypothesis, following the results of the exploratory analysis. The results suggest that frustration tolerance has a direct effect on subjective vitality, and that this relationship is mediated by positive affects, health status, and km of training per year. It is concluded that exercising increases subjective vitality, which is affected by frustration tolerance, positive affects, health status and km of training per year. In addition, it can be argued that these three variables mediate the relationship between frustration tolerance and subjective vitality. Finally, it is worth stressing that, given the positive effects of exercise not only in physical health but also in psychological, social and personal wellbeing, self-determined attitudes in training should be encouraged, as this promotes self-efficacy and self-satisfaction, in both training and competition settings.

A 6-day high-intensity interval microcycle improves indicators of endurance performance in elite cross-country skiers

Purpose

The aim of this study was to compare the effects of a 6-day high-intensity interval (HIT) block [BLOCK, n = 12, maximal oxygen uptake (V̇O2max = 69. 6 ± 4.3 mL·min−1·kg−1)] with a time-matched period with usual training (CON, n = 12, V̇O2max = 69.2 ± 4.2 mL·min−1·kg−1) in well-trained cross-country (XC) skiers on physiological determinants and indicators of endurance performance. Furthermore, the study aimed to investigate the acute physiological responses, including time ≥90% of V̇O2max, and its associated reliability during repeated HIT sessions in the HIT microcycle.

Methods

Before the 6-day HIT block and following 5 days of recovery after the HIT block, both groups were tested on indicators of endurance performance. To quantify time ≥90% of V̇O2max during interval sessions in the HIT block, V̇O2 measurements were performed on the 1st, 2nd, and last HIT session in BLOCK.

Results

BLOCK had a larger improvement than CON in maximal 1-min velocity achieved during the V̇O2max test (3.1 ± 3.1% vs. 1.2 ± 1.6%, respectively; p = 0.010) and velocity corresponding to 4 mmol·L−1 blood lactate (3.2 ± 2.9% vs. 0.6 ± 2.1%, respectively; p = 0.024). During submaximal exercise, BLOCK displayed a larger reduction in respiratory exchange ratio, blood lactate concentration, heart rate, and rate of perceived exertion (p &lt; 0.05) and a tendency towards less energy expenditure compared to CON (p = 0.073). The ICC of time ≥90% V̇O2max in the present study was 0.57, which indicates moderate reliability.

Conclusions

In well-trained XC skiers, BLOCK induced superior changes in indicators of endurance performance compared with CON, while time ≥90% of V̇O2max during the HIT sessions in the 6-day block had a moderate reliability.

Biomarker Changes in Oxygen Metabolism, Acid-Base Status, and Performance after the Off-Season in Well-Trained Cyclists

During the off-season, cyclists reduce their volume and intensity of training in order to recover the body from the high workload during the competitive season. Some studies have examined the effects of the off-season on cardiovascular, metabolic, and performance levels but have not evaluated oxygen metabolism, acid-base status, and electrolytes in cyclists. Therefore, our main objective was to analyze these markers in the off-season period (8 weeks) via finger capillary blood gasometry in well-trained cyclists. We found an increase in oxygen saturation (sO2) and oxyhemoglobin (O2Hb) (p ≤ 0.05) and a decrease in fat oxidation at maximum fat oxidation (FatMax) (p ≤ 0.05). In addition, we observed a decreasing trend of VO2 in the ventilatory threshold 2 (VT2) and maximum oxygen consumption (VO2MAX) (p ≤ 0.06) after the off-season in well-trained cyclists. Negative correlations were found between the pre–post off-season differences in the VO2 at ΔFatMax and ΔHCO3− (bicarbonate ion) and between power generated at the ΔeFTP (functional power threshold) and the ΔVO2MAX with the pH (r ≥ −0.446; p ≤ 0.05). After the off-season period, well-trained cyclists had increased markers of oxygen metabolism, decreased fat oxidation at low exercise intensities, and decreased VO2 at the VT2 and VO2MAX. Relationships were found between changes in the ΔeFTP and VO2MAX with changes in the pH and between the pH and HCO3− with changes in La−.

Physiological and Somatic Principal Components Determining VO2max in the Annual Training Cycle of Endurance Athletes

The purpose of the study was to assess the impact of training on the physiological variables achieved during the test effort in the macrocycle of road cyclists and their use in the maximal oxygen uptake (VO2max) prediction at individual training stages in the VO2max test. Nine well-trained male cyclists (age 25.6 ± 5.2 years and body weight 72.4 ± 7.35 kg) participated in the study and each phase of the macrocycle was followed by a time to exhaustion test (TTE) on the bicycle ergometer. The research showed that training loads significantly influence the maximum power (PPO), ventilation (VE) in the preparatory period (T1), time of the test (TTmax) at the start of the competition period (T2), percentage of body fat in total body weight (%FAT) and skeletal muscle mass (MMS) during the competition period (T3). Of the 16 variables taken for the analysis of the principal components (PC), the regression model determined one principal variable responsible for VO2max in the training macrocycle of cyclists, the relative value of maximum power (PPORV) and the accompanying variables in individual periods: breathing frequency (BF), delta blood lactate concentration (ΔLA), body fat (FAT) and MMS. Determining PC influencing the exercise capacity can be crucial in achieving the intended goals by athletes. Monitoring these indicators can help protect the health of professional athletes and provide guidelines in the training process, stimulate the body properly while protecting against overtraining.

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 (VO_2peak). Sixteen male XCO-MTB athletes (30.9 ± 5.2 years, 68.7 ± 5.6 kg, 175.0 ± 5.7 cm, and VO_2peak: 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 VO_2peak, 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; CI_95% = -0.84 to -0.10; p = 0.0008), and GE (r = -0.67; CI_95% = -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 VO_2peak and either CE (r = -0.45; CI_95% = -0.77-0.06; p = 0.08) or GE (r = -0.47; CI_95% = -0.78-0.04; p = 0.07). In conclusion, gross efficiency is an important component of XCO-MTB race performance. The VO_2peak 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.

The Inclusion of Sprints in Low-Intensity Sessions During the Transition Period of Elite Cyclists Improves Endurance Performance 6 Weeks Into the Subsequent Preparatory Period

PURPOSE

To investigate the effects of including repeated sprints in a weekly low-intensity (LIT) session during a 3-week transition period on cycling performance 6 weeks into the subsequent preparatory period (PREP) in elite cyclists.

METHODS

Eleven elite male cyclists (age = 22.0 [3.8] y, body mass = 73.0 [5.8] kg, height = 186 [7] cm, maximal oxygen uptake [VO2max] = 5469 [384] mL·min-1) reduced their training load by 64% and performed only LIT sessions (CON, n = 6) or included 3 sets of 3 × 30-second maximal sprints in a weekly LIT session (SPR, n = 5) during a 3-week transition period. There was no difference in the reduction in training load during the transition period between groups. Physiological and performance measures were compared between the end of the competitive period and 6 weeks into the PREP.

RESULTS

SPR demonstrated a 7.3% (7.2%) improvement in mean power output during a 20-minute all-out test at PREP, which was greater than CON (-1.3% [4.6%]) (P = .048). SPR had a corresponding 7.0% (3.6%) improvement in average VO2 during the 20-minute all-out test, which was larger than the 0.7% (6.0%) change in CON (P = .042). No change in VO2max, gross efficiency, or power output at blood lactate concentration of 4 mmol·L-1 from competitive period to PREP occurred in either group.

CONCLUSION

Including sprints in a weekly LIT session during the transition period of elite cyclists provided a performance advantage 6 weeks into the subsequent PREP, which coincided with a higher performance VO2.

How Does a Sport Psychological Intervention Help Professional Cyclists to Cope With Their Mental Health During the COVID-19 Lockdown?

All around the world in March, due to COVID-19, competitive sport calendars were suddenly canceled, jeopardizing the training programs of athletes. Moreover, in Italy, the government banned all non-essential travel across the entire country from the beginning of March. Consequently, Italian cyclists were banned from leaving their homes and therefore unable to perform their ordinary training activities. The Italian Association of Professional Cyclists (ACCPI) early on during that period noticed that several cyclists were experiencing a worrying decrease in their mental well-being and asked the authors to set up an online Sport Psychology Intervention (SPI) during lockdown to enhance the athletes' mental health. Through a number of unprecedented events and considerations, the aim of the current investigation was to assess the Italian cyclists' mental health during the lockdown and its changes after the SPI. We validated the Italian version of the Sport Mental Health Continuum Short Form (Sport MHC-SF)-presented in Study 1-and then applied it to a sample of Italian professional cyclists-presented in Study 2-prior to and after the SPI. To achieve these objectives, the reliability and construct validity of the Italian version of the Sport MHC-SF were tested in Study 1. RM-MANOVA tests were run to evaluate the effect of SPI on cyclists in Study 2. A total of 185 Italian athletes were involved in the validation of the MHC in Study 1 and 38 professional cyclists in Study 2. Results from Study 1 suggested a three-factor higher order model of Sport MHC-SF [Model fit: χ²(df) = 471.252 (252), p < 0.000; CFI = 0.951; RMSEA = 0.049; RMR= 0.048]. MCFA showed that the default model kept invariance among groups of athletes (i.e., female, male, individual, and team sports). Results from Study 2 highlighted that professional cyclists who followed the SPI were able to cope better with psychological stressors, showing improved well-being compared to the athletes that did not. No significant differences were found for emotional and social well-being. The present multi-study paper contributes to the theoretical field with a validated measure of Sport MHC-SF translated in the Italian language and culture. It also provides practical implications related to cases of reduced mental health due to injury, illness, or similar situations of home confinement in the future.

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.

Effects of Including Sprints in One Weekly Low-Intensity Training Session During the Transition Period of Elite Cyclists

The purpose of this study was to investigate the effects of including 30-s sprints in one weekly low-intensity training (LIT) session during a 3-week transition period in elite cyclists. Sixteen male elite cyclists (maximal oxygen uptake, VO_2max: 72 ± 5 ml·kg^-1·min^-1) reduced their training load by ~60% for 3 weeks from the end of competitive season and performed only LIT or included 30-s sprints (SPR) in one weekly LIT-session. Performance and physiological capacities were evaluated during a prolonged (~2.5 h) test-session, including a strength test, a submaximal blood lactate profile test, an incremental test to exhaustion to determine VO_2max, 1 h continuous cycling including four maximal 30-s sprints, and a 20-min all-out test. In addition, mental recovery was evaluated using the Athlete Burnout Questionnaire (ARQ). The only significant between-group change during the transition period was an 8 ± 11% larger improvement in 30-s sprint performance in SPR compared to control (CON; SPR: 4 ± 5%, CON: -4 ± 5%, p = 0.01). Although not different from CON, SPR maintained 20-min all-out performance (-1 ± 5%, p = 0.37) and fractional utilization of VO_2max (1.9 ± 6.1%-points, p = 0.18) during the 20-min all-out test, whereas corresponding declines were observed in CON (-3 ± 5%, p = 0.04, and -2.5 ± 2.9%-points, p = 0.02, respectively). Power output at 4 mmol·L^-1 blood lactate concentration decreased similarly in SPR (-4 ± 4%, p = 0.02) and CON (-5 ± 5%, p = 0.01), while VO_2max, maximal aerobic power (W_max), and total burnout score were unaffected in both groups. Including sprints in one weekly LIT-session in the transition period improves sprint performance and maintains 20-min all-out power and fractional utilization of VO_2max without compromising mental recovery. Inclusion of sprints in LIT-sessions may therefore be a plausible, time-efficient strategy during short periods of reduced training.

Superior performance improvements in elite cyclists following short-interval vs effort-matched long-interval training

The purpose of this study was to compare the effects of 3 weeks with three weekly sessions (ie, nine sessions in total) of short intervals (SI; n = 9; 3 series with 13 × 30-second work intervals interspersed with 15-second recovery and 3-minutes recovery between series) against effort-matched (rate of perceived effort based) long intervals (LI; n = 9; 4 series of 5-minute work intervals with 2.5-minutes recovery between series) on performance parameters in elite cyclists ( V ˙ O 2max 73 ± 4 mL min^-1  kg^-1 ). There were no differences between groups in total volume and intensity distribution of training during the intervention period. SI achieved a larger (P < .05) relative improvement in peak aerobic power output than LI (3.7 ± 4.3% vs -0.3 ± 2.8%, respectively), fractional utilization of V ˙ O 2max at 4 mmol L^-1 [La^- ] (3.0 ± 5.8 percent points vs -3.5 ± 2.7 percent points, respectively), and larger relative increase in power output at 4 mmol L^-1 [La^- ] (2.0 ± 6.7% vs -2.8 ± 3.4, respectively), while there was no group difference in change of V ˙ O 2max . Improvements in performance measured as mean power output during 20-minute cycling test were greater (P < .01) in SI compared with LI (4.7 ± 4.4% vs -1.4 ± 2.2%, respectively). Mean effect size of the improvement in the above variables revealed a small to large effect of SI training vs LI training. The data thus demonstrate that the present SI protocol induces superior training adaptations compared with the present LI protocol in elite cyclists.

Gross Efficiency and The Relationship with Maximum Oxygen Uptake in Young Elite Cyclists During the Competitive Season

This study assessed gross efficiency (GE) during a single competitive season and determined the relationship between GE and maximum oxygen uptake (V̇O_2max) in young elite cyclists (n = 15, 20.1 ± 1.4 yrs, 177.5 ± 5.7 cm, 68.3 ± 6.2 kg, 45.2 ± 7.5 mm of six skinfolds) during a competitive season. Participants completed at two occasions (T1 = April; T2 = July), a progressive bike protocol (initial intensity = 100 W, 35 W increments every 3 min) until volitional exhaustion to assess V̇O_2max and submaximal variables. A single capillary blood sample was drawn from the left earlobe immediately after completion of each exercise load to determine lactate thresholds. Cyclists' GE was calculated as ([work accomplished/energy expended] x 100). No significant differences were obtained in GE at any workload between T1 and T2 or in the mean GE between T1 (19.3%) and T2 (19.4%) testing (p = 0.93). No significant association was found between mean GE and V̇O_2max at either T1 (r = -0.28, p = 0.30), or T2 (r = -0.27, p = 0.32). GE of young elite cyclists might not vary during the most important phase of the training season and GE was not related to V̇O_2max. A lower accumulated volume and intensity of training of these cyclists may account for their lower GE in comparison to older professional cyclists and might not have been enough to foster higher increases of GE in cyclists with lower V̇O_2max.

Physiological and Psychological Adaptations of Trained Cyclists to Spring Cycling Camps

The purpose of our study was to assess physiological adaptations and measure mood outcomes following a cycling training camp in competitive athletes. Fourteen competitive athletes (8 males, 6 females) performed 2 incremental tests to exhaustion before and after a training camp. Volume and intensity (load) of the training regimen were recorded. Submaximal and maximal metabolic data were analysed, as well as economy variables (gross mechanical efficiency and cycling economy). Skeletal muscle adaptations were assessed using near infrared spectroscopy (NIRS). For both genders (n = 14), peak power output, peak power output-W/kg ratio and peak power output-B[La] were significantly increased (p < 0.05) after the cycling training camp (p < 0.05). Significant increases occurred for gross mechanical efficiency measured at the lactate threshold (+4.9%) and at the same precamp lactate threshold power output (+2.9%). At the lactate threshold and Post Camp Lactate Threshold Power, cycling economy increased by 5.2 and 2.9%, respectively (p < 0.05). These power measurements were significantly correlated with individual fluctuations in deoxyhaemoglobin in the vastus lateralis for male cyclists only. Profile of Mood State questionnaire results showed that subcategories “Tension-Anxiety”, “Confusion”, “Fatigue” and “Total Global Score” significantly decreased after the training camp. Cycling training camps were associated with positive adaptations (increased cycling economy, gross mechanical efficiency and power output) as well as some mental benefits. This indicates that despite some significant physiological adaptations participants probably did not overreach during their CTC.

Physiological determinants of elite mountain bike cross-country Olympic performance

Detailed physiological phenotyping was hypothesized to have predictive value for Olympic distance cross-country mountain bike (XCO-MTB) performance. Additionally, mean (MPO) and peak power output (PPO) in 4 × 30 s all-out sprinting separated by 1 min was hypothesized as a simple measure with predictive value for XCO-MTB performance. Parameters indicative of body composition, cardiovascular function, power and strength were determined and related to XCO-MTB national championship performance (n = 11). Multiple linear regression demonstrated 98% of the variance (P < 0.001) in XCO-MTB performance (t_XCO-MTB; [min]) is explained by maximal oxygen uptake relative to body mass (VO_2peak,rel; [ml/kg/min]), 30 s all-out fatigue resistance (FI; [%]) and with a minor contribution from quadriceps femoris maximal torque (T_max; [Nm]): t_XCO-MTB = -0.217× VO_2peak,rel.-0.201× FI+ 0.012× T_max+ 85.4. Parameters with no additional predictive value included hemoglobin mass, leg peak blood flow, femoral artery diameter, knee-extensor peak workload, jump height, quadriceps femoris maximal voluntary contraction force and rate of force development. Additionally, multiple linear regression demonstrated parameters obtained from 4x30s repeated sprinting explained 88% of XCO-MTB variance (P < 0.001) with t_XCO-MTB = -5.7× MPO+ 5.0× PPO+ 55.9. In conclusion, XCO-MTB performance is predictable from VO_2peak,rel and 30 s all-out fatigue resistance. Additionally, power variables from a repeated sprint test provides a cost-effective way of monitoring athletes XCO-MTB performance.

Different Training Loads Partially Influence Physiological Responses to the Preparation Period in Basketball

Ferioli, D, Bosio, A, La Torre, A, Carlomagno, D, Connolly, DR, and Rampinini, E. Different training loads partially influence physiological responses to preparation period in basketball. J Strength Cond Res 32(3): 790-797, 2018-The aim of this study was to compare the session rating of perceived exertion training load (sRPE-TL), training volume (TV), and the changes in physical fitness between professional (n = 14) and semiprofessional (n = 18) basketball players during the preparation period. Furthermore, relationships between sRPE-TL and TV with changes in physical fitness level were investigated. The players performed the Yo-Yo intermittent recovery test-level 1 (Yo-Yo IR1) before and after the preparation period. In addition, physiological responses to a standardized 6-minute continuous running test (Mognoni's test) and to a standardized 5-minute high-intensity intermittent running test (HIT) were measured. Session rating of perceived exertion-TL and TV were greater for professional (5,241 ± 1787 AU; 914 ± 122 minutes) compared with semiprofessional players (2,408 ± 487 AU; 583 ± 65 minutes). Despite these differences, Yo-Yo IR1 performance improvements (∼30%) and physiological adaptations to the Mognoni's test were similar between the 2 groups. Furthermore, physiological adaptations to HIT were slightly greater for professional compared with semiprofessional players; however, the magnitude of these effects was only small/moderate. No clear relationships were found between sRPE-TL and changes in Yo-Yo IR1 performance and Mognoni's test (rs ± 90% confidence interval [CI]: Yo-Yo IR1, 0.18 ± 0.30; Mognoni's test, -0.14 ± 0.29). Only moderate relationships were found between sRPE-TL and changes in HIT (rs ± 90% CI: [La], -0.48 ± 0.23; [H], -0.42 ± 0.25). These results raise doubts on the effectiveness of using high sRPE-TL and TV during the preparation period to improve the physical fitness level of players. The Yo-Yo IR1 seems to be sensitive to monitor changes induced by the preparation period; however, its use is not recommended to discriminate between adult basketball players of different competitive level.

Considerations on the Assessment and Use of Cycling Performance Metrics and their Integration in the Athlete's Biological Passport

Over the past few decades the possibility to capture real-time data from road cyclists has drastically improved. Given the increasing pressure for improved transparency and openness, there has been an increase in publication of cyclists' physiological and performance data. Recently, it has been suggested that the use of such performance biometrics may be used to strengthen the sensitivity and applicability of the Athlete Biological Passport (ABP) and aid in the fight against doping. This is an interesting concept which has merit, although there are several important factors that need to be considered. These factors include accuracy of the data collected and validity (and reliability) of the subsequent performance modeling. In order to guarantee high quality standards, the implementation of well-structured Quality-Systems within sporting organizations should be considered, and external certifications may be required. Various modeling techniques have been developed, many of which are based on fundamental intensity/time relationships. These models have increased our understanding of performance but are currently limited in their application, for example due to the largely unaccounted effects of environmental factors such as, heat and altitude. In conclusion, in order to use power data as a performance biometric to be integrated in the biological passport, a number of actions must be taken to ensure accuracy of the data and better understand road cycling performance in the field. This article aims to outline considerations in the quantification of cycling performance, also presenting an alternative method (i.e., monitoring race results) to allow for determination of unusual performance improvements.

The Effect of Different High-Intensity Periodization Models on Endurance Adaptations

PURPOSE

This study aimed to compare the effects of three different high-intensity training (HIT) models, balanced for total load but differing in training plan progression, on endurance adaptations.

METHODS

Sixty-three cyclists (peak oxygen uptake (V˙O2peak) 61.3 ± 5.8 mL·kg·min) were randomized to three training groups and instructed to follow a 12-wk training program consisting of 24 interval sessions, a high volume of low-intensity training, and laboratory testing. The increasing HIT group (n = 23) performed interval training as 4 × 16 min in weeks 1-4, 4 × 8 min in weeks 5-8, and 4 × 4 min in weeks 9-12. The decreasing HIT group (n = 20) performed interval sessions in the opposite mesocycle order as the increasing HIT group, and the mixed HIT group (n = 20) performed the interval prescriptions in a mixed distribution in all mesocycles. Interval sessions were prescribed as maximal session efforts and executed at mean values 4.7, 9.2, and 12.7 mmol·L blood lactate in 4 × 16-, 4 × 8-, and 4 × 4-min sessions, respectively (P < 0.001). Pre- and postintervention, cyclists were tested for mean power during a 40-min all-out trial, peak power output during incremental testing to exhaustion, V˙O2peak, and power at 4 mmol·L lactate.

RESULTS

All groups improved 5%-10% in mean power during a 40-min all-out trial, peak power output, and V˙O2peak postintervention (P < 0.05), but no adaptation differences emerged among the three training groups (P > 0.05). Further, an individual response analysis indicated similar likelihood of large, moderate, or nonresponses, respectively, in response to each training group (P > 0.05).

CONCLUSIONS

This study suggests that organizing different interval sessions in a specific periodized mesocycle order or in a mixed distribution during a 12-wk training period has little or no effect on training adaptation when the overall training load is the same.

Blood-Borne Markers of Fatigue in Competitive Athletes - Results from Simulated Training Camps

Assessing current fatigue of athletes to fine-tune training prescriptions is a critical task in competitive sports. Blood-borne surrogate markers are widely used despite the scarcity of validation trials with representative subjects and interventions. Moreover, differences between training modes and disciplines (e.g. due to differences in eccentric force production or calorie turnover) have rarely been studied within a consistent design. Therefore, we investigated blood-borne fatigue markers during and after discipline-specific simulated training camps. A comprehensive panel of blood-born indicators was measured in 73 competitive athletes (28 cyclists, 22 team sports, 23 strength) at 3 time-points: after a run-in resting phase (d 1), after a 6-day induction of fatigue (d 8) and following a subsequent 2-day recovery period (d 11). Venous blood samples were collected between 8 and 10 a.m. Courses of blood-borne indicators are considered as fatigue dependent if a significant deviation from baseline is present at day 8 (Δfatigue) which significantly regresses towards baseline until day 11 (Δrecovery). With cycling, a fatigue dependent course was observed for creatine kinase (CK; Δfatigue 54±84 U/l; Δrecovery -60±83 U/l), urea (Δfatigue 11±9 mg/dl; Δrecovery -10±10 mg/dl), free testosterone (Δfatigue -1.3±2.1 pg/ml; Δrecovery 0.8±1.5 pg/ml) and insulin linke growth factor 1 (IGF-1; Δfatigue -56±28 ng/ml; Δrecovery 53±29 ng/ml). For urea and IGF-1 95% confidence intervals for days 1 and 11 did not overlap with day 8. With strength and high-intensity interval training, respectively, fatigue-dependent courses and separated 95% confidence intervals were present for CK (strength: Δfatigue 582±649 U/l; Δrecovery -618±419 U/l; HIIT: Δfatigue 863±952 U/l; Δrecovery -741±842 U/l) only. These results indicate that, within a comprehensive panel of blood-borne markers, changes in fatigue are most accurately reflected by urea and IGF-1 for cycling and by CK for strength training and team sport players.

Visual Impairment does not Limit Training Effects in Development of Aerobic and Anaerobic Capacity in Tandem Cyclists

The study aimed to investigate the differences in the effects of 7-month training on aerobic and anaerobic capacity in tandem cycling athletes with and without visual impairment. In this study, Polish elite (n=13) and sub-elite (n=13) visually impaired (VI) (n=13; 40.8 ±12.8 years) and properly sighted (PS) (n=13; 36.7 ±12.2 years) tandem-cycling athletes participated voluntarily in 7-month routine training. The following pre-/post-training measurements were conducted on separate days: maximal oxygen uptake (VO_2max) was estimated with age correction using the Physical Working Capacity test on a bicycle ergometer according to the Astrand-Ryhming method. Maximal power output (P_max) was evaluated using the Quebec test on a bicycle ergometer. At baseline, VO_2max (47.8 ±14.1 vs 42.0 ±8.3 ml/kg/min, respectively) and P_max (11.5 ±1.5 vs 11.5 ±1.0 W/kg) did not differ significantly between PS and VI cyclists. However, differences in aerobic capacity were considered as clinically significant. Two-way ANOVA revealed that after 7 month training, there were statistically significant increases in VO_2max (p=0.003) and P_max (p=0.009) among VI (VO_2max, +9.1%; P_max, +6.3%) and PS (VO_2max, +9.1%; P_max, +11.7%) cyclists, however, no time × visual impairment interaction effect was found (VO_2max, p=0.467; P_max, p=0.364). After training, VO_2max (p=0.03), but not P_max (p=0.13), was significantly greater in elite compared to sub-elite tandem cyclists. VI and PS tandem cyclists showed similar rates of improvement in VO_2max and P_max after 7-month training. VO_2max was a significant determinant of success in tandem cycling. This is one of the first studies providing reference values for aerobic and anaerobic capacity in visually impaired cyclists.

Strength training improves performance and pedaling characteristics in elite cyclists

The purpose was to investigate the effect of 25 weeks heavy strength training in young elite cyclists. Nine cyclists performed endurance training and heavy strength training (ES) while seven cyclists performed endurance training only (E). ES, but not E, resulted in increases in isometric half squat performance, lean lower body mass, peak power output during Wingate test, peak aerobic power output (W(max)), power output at 4 mmol L(-1)[la(-)], mean power output during 40-min all-out trial, and earlier occurrence of peak torque during the pedal stroke (P < 0.05). ES achieved superior improvements in W(max) and mean power output during 40-min all-out trial compared with E (P < 0.05). The improvement in 40-min all-out performance was associated with the change toward achieving peak torque earlier in the pedal stroke (r = 0.66, P < 0.01). Neither of the groups displayed alterations in VO2max or cycling economy. In conclusion, heavy strength training leads to improved cycling performance in elite cyclists as evidenced by a superior effect size of ES training vs E training on relative improvements in power output at 4 mmol L(-1)[la(-)], peak power output during 30-s Wingate test, W(max), and mean power output during 40-min all-out trial.

In-season strength maintenance training increases well-trained cyclists' performance

We investigated the effects of strength maintenance training on thigh muscle cross-sectional area (CSA), leg strength, determinants of cycling performance, and cycling performance. Well-trained cyclists completed either (1) usual endurance training supplemented with heavy strength training twice a week during a 12-week preparatory period followed by strength maintenance training once a week during the first 13 weeks of a competition period (E + S; n = 6 [♂ = 6]), or (2) usual endurance training during the whole intervention period (E; n = 6 [♂ = 5, ♀ = 1]). Following the preparatory period, E + S increased thigh muscle CSA and 1RM (p < 0.05), while no changes were observed in E. Both groups increased maximal oxygen consumption and mean power output in the 40-min all-out trial (p < 0.05). At 13 weeks into the competition period, E + S had preserved the increase in CSA and strength from the preparatory period. From the beginning of the preparatory period to 13 weeks into the competition period, E + S increased peak power output in the Wingate test, power output at 2 mmol l(-1) [la(-)], maximal aerobic power output (W (max)), and mean power output in the 40-min all-out trial (p < 0.05). The relative improvements in the last two measurements were larger than in E (p < 0.05). For E, W (max) and power output at 2 mmol l(-1) [la(-)] remained unchanged. In conclusion, in well-trained cyclists, strength maintenance training in a competition period preserved increases in thigh muscle CSA and leg strength attained in a preceding preparatory period and further improved cycling performance determinants and performance.

The effect of training volume and intensity on competitive cyclists’ efficiency

The impact of different intensity training on cycling efficiency in competitive cyclists is unknown. Twenty-nine endurance-trained competitive male cyclists completed 3 laboratory visits during a 12-week training period. At each visit, their cycling efficiency and maximal oxygen uptake were determined. After the first visit, cyclists were randomly split into 2 groups (A and B). Over the first 6 weeks, between tests 1 and 2, group A was prescribed specific high-intensity training sessions, whereas group B was restricted in the amount of intensive work undertaken. After test 2 and for the second 6-week period, group B was allowed to conduct high-intensity training. Gross efficiency (GE) increased in group A (+1.6 ± 1.4%; p < 0.05) following the high-intensity training, whereas no significant change was seen in group B (+0.1 ± 0.7%; p > 0.05). Group B cyclists increased their GE between tests 2 and 3 (+1.4 ± 0.8%; p < 0.05) but no changes in GE were observed in group A over this period (+0.4 ± 0.4%; p > 0.05). Delta efficiency (DE) did not change significantly in either group across the study period. This study demonstrates that GE is increased following high-intensity training in competitive male cyclists after 12 weeks.