Predictors of individual adaptation to high-volume or high-intensity endurance training in recreational endurance runners

Effects of high-intensity interval and moderate-intensity continuous training on the anaerobic threshold of highly trained athletes in endurance sports: a systematic review with meta-analysis

INTRODUCTION

The anaerobic threshold (AT) is an important physiological index used as a parameter for predicting performance and evaluating adaptations induced by training. The aim of this study was to carry out a systematic literature review to survey the randomized studies that compared the effects of high-intensity interval training (HIIT) with the effects of moderate intensity continuous training (MICT) on the anaerobic threshold of highly trained athletes in endurance sports.

EVIDENCE ACQUISITION

The following databases were searched: MEDLINE, Embase, Cochrane Wiley, PubMed, SPORTDiscus, Web of Science, and ProQuest for randomized trials. The search terms covered the areas of HIIT and MICT. This study was registered in the International Prospective Register of Systematic under the number CRD42020155474.

EVIDENCE SYNTHESIS

Three studies were included for the qualitative and quantitative synthesis, totaling 72 participants, of whom 28 belonged to the MICT group and 44 to the HIIT group.

CONCLUSIONS

The summary result showed that HIIT promotes greater adaptation in the AT of highly trained athletes compared to continuous training (ES=0.73; 95% CI: 0.25-1.21); however, the certainty of evidence evaluated by the GRADE method is low and heterogeneity is high (I2=82%; P<0.01).

Interval training has more negative effects on sleep in adolescent speed skaters: a randomized cross controlled trial

Objective

Sleep is an essential component of athletic performance and recovery. This study aimed to investigate the effects of different types of high-intensity exercise on sleep parameters in adolescent speed skaters.

Methods

Eighteen male adolescent speed skaters underwent aerobic capacity testing, Wingate testing, and interval training in a randomized crossover design to assess strength output, heart rate, and blood lactate levels during exercise. Sleep quality after each type of exercise was evaluated using the Firstbeat Bodyguard 3 monitor.

Results

The results showed that Wingate testing and interval training led to decreased sleep duration, increased duration of stress, decreased RMSSD, and increased LF/HF ratio (p < 0.01). Conversely, aerobic capacity testing did not significantly affect sleep (p > 0.05). The impact of interval training on sleep parameters was more significant compared to aerobic capacity testing (p < 0.01) and Wingate testing (p < 0.01).

Conclusion

High-intensity anaerobic exercise has a profound impact on athletes' sleep, primarily resulting in decreased sleep duration, increased stress duration, decreased RMSSD, and increased LF/HF ratio.

Practices and Applications of Heart Rate Variability Monitoring in Endurance Athletes

Heart rate variability reflects fluctuations in the changes in consecutive heartbeats, providing insight into cardiac autonomic function and overall physiological state. Endurance athletes typically demonstrate better cardiac autonomic function than non-athletes, with lower resting heart rates and greater variability. The availability and use of heart rate variability metrics has increased in the broader population and may be particularly useful to endurance athletes. The purpose of this review is to characterize current practices and applications of heart rate variability analysis in endurance athletes. Important considerations for heart rate variability analysis will be discussed, including analysis techniques, monitoring tools, the importance of stationarity of data, body position, timing and duration of the recording window, average heart rate, and sex and age differences. Key factors affecting resting heart rate variability will be discussed, including exercise intensity, duration, modality, overall training load, and lifestyle factors. Training applications will be explored, including heart rate variability-guided training and the identification and monitoring of maladaptive states such as overtraining. Lastly, we will examine some alternative uses of heart rate variability, including during exercise, post-exercise, and for physiological forecasting and predicting performance.

Individualized Endurance Training Based on Recovery and Training Status in Recreational Runners

PURPOSE

Long-term development of endurance performance requires a proper balance between strain and recovery. Because responses and adaptations to training are highly individual, this study examined whether individually adjusted endurance training based on recovery and training status would lead to greater adaptations compared with a predefined program.

METHODS

Recreational runners were divided into predefined (PD; n = 14) or individualized (IND; n = 16) training groups. In IND, the training load was decreased, maintained, or increased twice a week based on nocturnal heart rate variability, perceived recovery, and heart rate-running speed index. Both groups performed 3-wk preparatory, 6-wk volume, and 6-wk interval periods. Incremental treadmill tests and 10-km running tests were performed before the preparatory period ( T0 ) and after the preparatory ( T1 ), volume ( T2 ), and interval ( T3 ) periods. The magnitude of training adaptations was defined based on the coefficient of variation between T0 and T1 tests (high >2×, low <0.5×).

RESULTS

Both groups improved ( P < 0.01) their maximal treadmill speed and 10-km time from T1 to T3 . The change in the 10-km time was greater in IND compared with PD (-6.2% ± 2.8% vs -2.9% ± 2.4%, P = 0.002). In addition, IND had more high responders (50% vs 29%) and fewer low responders (0% vs 21%) compared with PD in the change of maximal treadmill speed and 10-km performance (81% vs 23% and 13% vs 23%), respectively.

CONCLUSIONS

PD and IND induced positive training adaptations, but the individualized training seemed more beneficial in endurance performance. Moreover, IND increased the likelihood of high response and decreased the occurrence of low response to endurance training.

Physiological, Perceptual, and Performance Responses to the 2-Week Block of High- versus Low-Intensity Endurance Training

PURPOSE

This study examined the physiological, perceptual, and performance responses to a 2-wk block of increased training load and compared whether responses differ between high-intensity interval (HIIT) and low-intensity training (LIT).

METHODS

Thirty recreationally trained males and females performed a 2-wk block of 10 HIIT sessions (INT, n = 15) or 70% increased volume of LIT (VOL, n = 15). Running time in the 3000 m and basal serum and urine hormone concentrations were measured before (T1) and after the block (T2), and after a recovery week (T3). In addition, weekly averages of nocturnal heart rate variability (HRV) and perceived recovery were compared with the baseline.

RESULTS

Both groups improved their running time in the 3000 m from T1 to T2 (INT = -1.8% ± 1.6%, P = 0.003; VOL = -1.4% ± 1.7%, P = 0.017) and from T1 to T3 (INT = -2.5% ± 1.6%, P < 0.001; VOL = -2.2% ± 1.9%, P = 0.001). Resting norepinephrine concentration increased in INT from T1 to T2 (P = 0.01) and remained elevated at T3 (P = 0.018). The change in HRV from the baseline was different between the groups during the first week (INT = -1.0% ± 2.0% vs VOL = 1.8% ± 3.2%, P = 0.008). Muscle soreness increased only in INT (P < 0.001), and the change was different compared with VOL across the block and recovery weeks (P < 0.05).

CONCLUSIONS

HIIT and LIT blocks increased endurance performance in a short period. Although both protocols seemed to be tolerable for recreational athletes, a HIIT block may induce some negative responses such as increased muscle soreness and decreased parasympathetic activity.

High-Intensity Functional Training Guided by Individualized Heart Rate Variability Results in Similar Health and Fitness Improvements as Predetermined Training with Less Effort

Heart rate variability (HRV) may be useful for prescribing high-intensity functional training (HIFT) exercise programs. This study aimed to compare effects of HRV-guided and predetermined HIFT on cardiovascular function, body composition, and performance.

METHODS

Recreationally-active adults (n = 55) were randomly assigned to predetermined HIFT (n = 29, age = 24.1 ± 4.1 years) or HRV-guided HIFT (n = 26, age = 23.7 ± 4.5) groups. Both groups completed 11 weeks of daily HRV recordings, 6 weeks of HIFT (5 d·week-1), and pre- and post-test body composition and fitness assessments. Meaningful changes in resting HRV were used to modulate (i.e., reduce) HRV-guided participants' exercise intensity. Linear mixed models were used with Bonferroni post hoc adjustment for analysis.

RESULTS

All participants significantly improved resting heart rate, lean mass, fat mass, strength, and work capacity. However, no significant between-groups differences were observed for cardiovascular function, body composition, or fitness changes. The HRV-guided group spent significantly fewer training days at high intensity (mean difference = -13.56 ± 0.83 days; p < 0.001).

CONCLUSION

HRV-guided HIFT produced similar improvements in cardiovascular function, body composition, and fitness as predetermined HIFT, despite fewer days at high intensity. HRV shows promise for prescribing individualized exercise intensity during HIFT.

Effects of Increased Load of Low- Versus High-Intensity Endurance Training on Performance and Physiological Adaptations in Endurance Athletes

PURPOSE

To compare the effects of increased load of low- versus high-intensity endurance training on performance and physiological adaptations in well-trained endurance athletes.

METHODS

Following an 8-week preintervention period, 51 (36 men and 15 women) junior cross-country skiers and biathletes were randomly allocated into a low-intensity (LIG, n = 26) or high-intensity training group (HIG, n = 25) for an 8-week intervention period, load balanced using the overall training impulse score. Both groups performed an uphill running time trial and were assessed for laboratory performance and physiological profiling in treadmill running and roller-ski skating preintervention and postintervention.

RESULTS

Preintervention to postintervention changes in running time trial did not differ between groups (P = .44), with significant improvements in HIG (-2.3% [3.2%], P = .01) but not in LIG (-1.5% [2.9%], P = .20). There were no differences between groups in peak speed changes when incremental running and roller-ski skating to exhaustion (P = .30 and P = .20, respectively), with both modes being significantly improved in HIG (2.2% [3.1%] and 2.5% [3.4%], both P < .01) and in roller-ski skating for LIG (1.5% [2.4%], P < .01). There was a between-group difference in running maximal oxygen uptake changes (P = .04), tending to improve in HIG (3.0% [6.4%], P = .09) but not in LIG (-0.7% [4.6%], P = .25). Changes in roller-ski skating peak oxygen uptake differed between groups (P = .02), with significant improvements in HIG (3.6% [5.4%], P = .01) but not in LIG (-0.1% [0.17%], P = .62).

CONCLUSION

There was no significant difference in performance adaptations between increased load of low- versus high-intensity training in well-trained endurance athletes, although both methods improved performance. However, increased load of high-intensity training elicited better maximal oxygen uptake adaptations compared to increased load of low-intensity training.

The Use of a Smartphone Application in Monitoring HRV during an Altitude Training Camp in Professional Female Cyclists: A Preliminary Study

Altitude training is a common strategy to improve performance in endurance athletes. In this context, the monitoring of training and the athletes’ response is essential to ensure positive adaptations. Heart rate variability (HRV) has been proposed as a tool to evaluate stress and the response to training. In this regard, many smartphone applications have emerged allowing a wide access to recording HRV easily. The purpose of this study was to describe the changes of HRV using a validated smartphone application before (Pre-TC), during (TC), and after (Post-TC) an altitude training camp in female professional cyclists. Training load (TL) and vagal markers of heart rate variability (LnRMSSD, LnRMSSDcv) of seven professional female cyclists before, during, and after and altitude training camp were monitored. Training volume (SMD = 0.80), LnRMSSD (SMD = 1.06), and LnRMSSDcv (SMD = −0.98) showed moderate changes from Pre-TC to TC. Training volume (SMD = 0.74), TL (SMD = 0.75), LnRMSSD (SMD = −1.11) and LnRMSSDcv (SMD = 0.83) showed moderate changes from TC to Post-TC. Individual analysis showed that heart rate variability responded differently among subjects. The use of a smartphone application to measure HRV is a useful tool to evaluate the individual response to training in female cyclists.

The Effect of High-Intensity Interval Training Periods on Morning Serum Testosterone and Cortisol Levels and Physical Fitness in Men Aged 35-40 Years

BACKGROUND

Intensive physical activity largely modulates resting concentrations of blood cortisol (C) and testosterone (T) and their molar ratio, which is defined as the anabolic-catabolic index and expressed as T/C × 10². The aim of the study is to evaluate the effect of the author's high-intensity training program on T, C, T/C × 10², and selected physical fitness indices in men between 35 and 40 years of age.

METHODS

The experiment was conducted on a group of 30 healthy men, divided into control and experimental groups. The experimental group followed a high-intensity 8-week training program, which included three sessions per week, each of them lasting 1 h and consisting of intensive-interval exercises followed by strength circuit exercises. The controls did not change their previous recreational physical activity. T, C, and T/C × 10² were measured before and after the experiment for all participants. Physical performance was examined using a standardized laboratory exercise test to determine maximal oxygen uptake (VO_2max).

RESULTS

There were statistically significant increases in T (by 36.7%) and T/C × 10² (by 59%), while C somewhat dropped (by 12%) in the experimental group. No changes in the hormonal indices were found in the control group. After completing the experimental training, there were no statistically significant changes in aerobic capacity, but it improved muscle strength in the men studied.

CONCLUSIONS

High-intensity interval training, continued over an 8-week period, modulates (significantly and positively) the balance between testosterone and cortisol levels and improves physical capacity in men aged 35-40 years.

Effect of four different forms of high intensity training on BDNF response to Wingate and Graded Exercise Test

This study examined the effects of a nine-week intervention of four different high-intensity training modalities [high-intensity functional training (HIFT), high-intensity interval training (HIIT), high-intensity power training (HIPT), and high-intensity endurance training (HIET)] on the resting concentration of brain-derived neurotropic factor (BDNF). In addition, we evaluated the BDNF responses to Graded Exercise Test (GXT) and Wingate Anaerobic Test (WAnT) in men. Thirty-five healthy individuals with body mass index 25.55 ± 2.35 kg/m2 voluntarily participated in this study and were randomly assigned into four training groups. During nine-weeks they completed three exercise sessions per week for one-hour. BDNF was analyzed before and after a GXT and WAnT in two stages: (stage 0-before training and stage 9-after nine weeks of training). At stage 0, an increase in BDNF concentration was observed in HIFT (33%; p < 0.05), HIPT (36%; p < 0.05) and HIIT (38%; p < 0.05) after GXT. Even though HIET showed an increase in BDNF (10%) this was not statistically significant (p > 0.05). At stage 9, higher BDNF levels after GXT were seen only for the HIFT (30%; p < 0.05) and HIIT (18%; p < 0.05) groups. Reduction in BDNF levels were noted after the WAnT in stage 0 for HIFT (- 47%; p < 0.01), HIPT (- 49%; p < 0.001), HIET (- 18%; p < 0.05)], with no changes in the HIIT group (- 2%). At stage 9, BDNF was also reduced after WAnT, although these changes were lower compared to stage 0. The reduced level of BDNF was noted in the HIFT (- 28%; p < 0.05), and HIPT (- 19%;p < 0.05) groups. Additionally, all groups saw an improvement in VO2max (8%; p < 0.001), while BDNF was also correlated with lactate and minute ventilation and selected WAnT parameters. Our research has shown that resting values of BDNF after nine weeks of different forms of high-intensity training (HIT) have not changed or were reduced. Resting BDNF measured at 3th (before GXT at stage 9) and 6th day after long lasting HITs (before WAnT at stage 9) did not differed (before GXT), but in comparison to the resting value before WAnT at the baseline state, was lower in three groups. It appears that BDNF levels after one bout of exercise is depended on duration time, intensity and type of test/exercise.

Relationships between Workload, Heart Rate Variability, and Performance in a Recreational Endurance Runner

BACKGROUND

The association between heart rate variability (HRV), training load (TL), and performance is poorly understood.

METHODS

A middle-aged recreational female runner was monitored during a competitive 20-wk macrocycle divided into first (M1) and second mesocycle (M2) in which best performances over 10 km and 21 km were recorded. Volume (km), session rating of perceived exertion (sRPE), TL, and monotony (mean TL/SD TL) were the workload parameters recorded. The root mean square of the successive differences in R-R intervals (RMSSD), its coefficient of variation (RMSSDcv), and the RMSSD:RR ratio were the HRV parameters monitored.

RESULTS

During M2, RMSSD (p = 0.006) and RMSSD:RR (p = 0.002) were significantly increased, while RR was significantly reduced (p = 0.017). Significant correlations were identified between monotony and volume (r = 0.552; p = 0.012), RR (r = 0.447; p = 0.048), and RMSSD:RR (r = -0.458; p = 0.042). A sudden reduction in RMSSD (from 40.31 to 24.34 ms) was observed the day before the first symptoms of an influenza.

CONCLUSIONS

The current results confirm the practicality of concurrent HRV and sRPE monitoring in recreational runners, with the RMSSD:RR ratio indicative of specific adaptations. Excessive training volume may be associated to both elevated monotony and reduced RMSSD:RR. Identification of mesocycle patterns is recommended for better individualization of the periodization used.

Superior Adaptations in Adolescent Runners Using Heart Rate Variability (HRV)-Guided Training at Altitude

We evaluated the efficacy of heart rate variability (HRV)-guided training in adolescent athletes during a 2-week, high altitude (≈1900 m) training camp. Sixteen middle- and long-distance runners (4 female/12 male, 16.9 ± 1.0 years, 65.44 ± 4.03 mL·kg-1·min-1) were divided into 2 matched groups, both of which received the same training plan, but one of which acquired postwaking HRV values that were used to tailor the training prescription. During the camp, seven athletes in the HRV-guided group combined for a total of 32 training adjustments, whereas there were only 3 runners combined for 14 total training adjustments in the control group. A significant group by time interaction (p < 0.001) for VO2max was driven by VO2max improvements in the HRV group (+2.8 mL·kg-1·min-1, +4.27%; pBonf = 0.002) that were not observed in the control condition (+0.8 mL·kg-1·min-1, +1.26%; pBonf = 0.643). After returning from the camp, all athletes in the HRV group set a personal best, and six out of eight achieved their best positions in the National Championship, whereas only 75% of athletes in the control group set a personal best and five out of eight achieved their best positions in the National Championship. These data provide evidence in support of HRV-guided training as a way to optimize training prescriptions in adolescent athletes.

Monitoring Training and Recovery during a Period of Increased Intensity or Volume in Recreational Endurance Athletes

The purpose of the study was to examine the effects of progressively increased training intensity or volume on the nocturnal heart rate (HR) and heart rate variability (HRV), countermovement jump, perceived recovery, and heart rate-running speed index (HR-RS index). Another aim was to analyze how observed patterns during the training period in these monitoring variables were associated with the changes in endurance performance. Thirty recreationally trained participants performed a 10-week control period of regular training and a 10-week training period of either increased training intensity (INT, n = 13) or volume (VOL, n = 17). Changes in endurance performance were assessed by an incremental treadmill test. Both groups improved their maximal speed on the treadmill (INT 3.4 ± 3.2%, p < 0.001; VOL 2.1 ± 1.8%, p = 0.006). In the monitoring variables, only between-group difference (p = 0.013) was found in nocturnal HR, which decreased in INT (p = 0.016). In addition, perceived recovery decreased in VOL (p = 0.021) and tended to decrease in INT (p = 0.056). When all participants were divided into low-responders and responders in maximal running performance, the increase in the HR-RS index at the end of the training period was greater in responders (p = 0.005). In conclusion, current training periods of increased intensity or volume improved endurance performance to a similar extent. Countermovement jump and HRV remained unaffected, despite a slight decrease in perceived recovery. Long-term monitoring of the HR-RS index may help to predict positive adaptations, while interpretation of other recovery-related markers may need a more individualized approach.

Monitoring the Heart Rate Variability Responses to Training Loads in Competitive Swimmers Using a Smartphone Application and the Banister Impulse-Response Model

PURPOSE

First, to examine whether heart rate variability (HRV) responses can be modeled effectively via the Banister impulse-response model when the session rating of perceived exertion (sRPE) alone, and in combination with subjective well-being measures, are utilized. Second, to describe seasonal HRV responses and their associations with changes in critical speed (CS) in competitive swimmers.

METHODS

A total of 10 highly trained swimmers collected daily 1-minute HRV recordings, sRPE training load, and subjective well-being scores via a novel smartphone application for 15 weeks. The impulse-response model was used to describe chronic root mean square of the successive differences (rMSSD) responses to training, with sRPE and subjective well-being measures used as systems inputs. Changes in CS were obtained from a 3-minute all-out test completed in weeks 1 and 14.

RESULTS

The level of agreement between predicted and actual HRV data was R2 = .66 (.25) when sRPE alone was used. Model fits improved in the range of 4% to 21% when different subjective well-being measures were combined with sRPE, representing trivial-to-moderate improvements. There were no significant differences in weekly group averages of log-transformed (Ln) rMSSD (P = .34) or HRV coefficient of variation of Ln rMSSD (P = .12); however, small-to-large changes (d = 0.21-1.46) were observed in these parameters throughout the season. Large correlations were observed between seasonal changes in HRV measures and CS (changes in averages of Ln rMSSD: r = .51, P = .13; changes in coefficient of variation of Ln rMSSD: r = -.68, P = .03).

CONCLUSION

The impulse-response model and data collected via a novel smartphone application can be used to model HRV responses to swimming training and nontraining-related stressors. Large relationships between seasonal changes in measured HRV parameters and CS provide further evidence for incorporating a HRV-guided training approach.

HRV-Based Training for Improving VO2max in Endurance Athletes. A Systematic Review with Meta-Analysis

This review aimed to synthesize evidence regarding interventions based on heart rate variability (HRV)-guided training for VO_2max improvements in endurance athletes and address the issues that impact this performance enhancement. The Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, CINAHL Complete, the Web of Science Core Collection, Global Health, Current Contents Connect, and the SciELO citation index were searched. Inclusion criteria were: randomized controlled trials; studies with trained athletes enrolled in any regular endurance training; studies that recruited men, women, and both sexes combined; studies on endurance training controlled by HRV; studies that measured performance with VO_2max. A random-effects meta-analysis calculating the effect size (ES) was used. Moderator analyses (according to the athlete's level and gender) and metaregression (according to the number of participants in each group) were undertaken to examine differences in ES. HRV-guided training and control training enhanced the athletes' VO_2max (p < 0.0001), but the ES for the HRV-guided training group was significantly higher (p < 0.0001; ES_HRVG-CG = 0.187). The amateur level and female subgroup reported better and significant results (p < 0.0001) for VO_2max. HRV-guided training had a small (ES = 0.402) but positive effect on endurance athlete performance (VO_2max), conditioned by the athlete's level and sex.

Heart Rate Variability Mainly Relates to Cognitive Executive Functions and Improves Through Exergame Training in Older Adults: A Secondary Analysis of a 6-Month Randomized Controlled Trial

Heart rate variability (HRV) mirrors autonomic nervous system activities and might serve as a parameter to monitor health status in older adults. However, it is currently unknown which functional health measures, including cognitive, physical, and gait performance parameters, are most strongly related to HRV indices. This knowledge would enable implementing HRV assessments into health monitoring routines and training planning for older adults. Simultaneous cognitive-motor and exergame training may be effective to improve HRV indices but has not been investigated yet. Eighty-nine healthy older adults (≥70 years of age) were randomized into three groups: (1) virtual reality video game dancing, i.e., exergaming (DANCE); (2) treadmill walking with simultaneous verbal memory training (MEMORY); or (3) treadmill walking only (PHYS). Strength and balance exercises complemented each program. Over 6 months, two weekly 1-h training sessions were performed. HRV indices (standard deviation of N-N intervals, SDNN; root mean square of successive R-R interval differences, RMSSD; and absolute power of high-frequency band (0.15-0.4 Hz), HF power) and various measures of cognitive, physical, and gait performance were assessed at baseline and after 3 months and 6 months. Multiple linear regression analyses with planned comparisons were calculated. At baseline, 8-12% of HRV variance was significantly explained by cognitive executive functions and leg strength (inversely related). Verbal long-term memory, aerobic and functional fitness, and gait performance did not contribute to the model (SDNN: R² = 0.082, p = 0.016; RMSSD: R² = 0.121, p = 0.013; HF power: R² = 0.119, p = 0.015). After 6 months, DANCE improved HRV indices, while MEMORY and PHYS did not (time × intervention interactions: first-contrast DANCE/MEMORY vs. PHYS: SDNN p = 0.014 one-tailed, ΔR ² = 0.020 and RMSSD p = 0.052 one-tailed (trend), ΔR ² = 0.007; second-contrast DANCE vs. MEMORY: SDNN p = 0.002 one-tailed, ΔR ² = 0.035, RMSSD p = 0.017 one-tailed, ΔR ² = 0.012, and HF power p = 0.011 one-tailed, ΔR ² = 0.013). We conclude that mainly cognitive executive functions are associated with HRV indices and that exergame training improves global and parasympathetic autonomic nervous system activities in older adults. Periodic assessments of HRV in older citizens could be particularly beneficial to monitor cognitive health and provide indications for preventative exercise measures.

Muscle function assessed by the non-invasive method acoustic myography (AMG) in a Danish group of healthy adults

Acoustic myography (AMG) is a non-invasive method to assess muscle function during daily activities. AMG has great scope for assessment of musculoskeletal problems. The aim of this study was to create an AMG data set for general clinical use and relate these findings to age and gender. 10 healthy subjects (5 men/5 women), in each decade from 20 to 69 years of age (n = 50), were assessed. Their clinical health was tested. AMG measurements were carried out on muscles involved in defined movements of the upper and lower extremities. Muscle performance was measured using efficiency (E-score) and fibre recruitment (temporal (T-score) and spatial (S-score) summation). AMG-measurements showed good reproducibility. In each age group, it was found that for all those daily living skills measured, there was no gender difference. A walking and stair climbing test revealed that both legs are used equally and in a balanced way in healthy subjects. Moreover, there was no change in this function with increasing age up to 69 years. However, a cycling test with loading revealed that in elderly subjects the coordination of muscle use is impaired compared to that of the younger adults. Finally, a flexion test of the arm revealed an age-related decrease in the efficiency/coordination of m.Biceps alone, and a keyboard writing test suggests no effect on m.Trapezius. This reference data set now illustrates the reproducibility and ease of use of acoustic myography in the clinic and provides a means of assessing individuals with musculoskeletal problems.

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Acoustic myography is a non-invasive, real-time and repeatable tool for assessing musculoskeletal problems in the clinic.

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A walking and stair climbing test revealed both legs to be used in a balanced way in healthy subjects, with no age effect.

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A cycling test with loading showed that coordination of muscle use was impaired with increasing age.

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A flexion test of the arm revealed an age-related decrease in the efficiency/coordination of m.Biceps alone.

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This reference data set illustrates the ease of use of this technique in the clinic for musculoskeletal problems.

Factors Affecting Training and Physical Performance in Recreational Endurance Runners

Endurance running has become an immensely popular sporting activity, with millions of recreational runners around the world. Despite the great popularity of endurance running as a recreational activity during leisure time, there is no consensus on the best practice for recreational runners to effectively train to reach their individual objectives and improve physical performance in a healthy manner. Moreover, there are lots of anecdotal data without scientific support, while most scientific evidence on endurance running was developed from studies observing both recreational and professional athletes of different levels. Further, the transference of all this information to only recreational runners is difficult due to differences in the genetic predisposition for endurance running, the time available for training, and physical, psychological, and physiological characteristics. Therefore, the aim of this review is to present a selection of scientific evidence regarding endurance running to provide training guidelines to be used by recreational runners and their coaches. The review will focus on some key aspects of the training process, such as periodization, training methods and monitoring, performance prediction, running technique, and prevention and management of injuries associated with endurance running.

Deciphering V̇ O2,max: limits of the genetic approach

Maximal oxygen consumption (V̇ _O2,max) denotes the upper limit of aerobic energy flux through the cascade of oxygen transfer from the environment to tissue mitochondria, essentially to skeletal muscle mitochondria during intense exercise. A high V̇ _O2,max is a key component for athletic success in human and animal endurance sports. From a public health perspective, a high V̇ _O2,max is a validated negative predictor for cardiovascular disease and all-cause mortality. V̇ _O2,max varies by more than twofold between sedentary subjects and shows a heritability value greater than 50%. Likewise, the capacity for an individual's V̇ _O2,max to be increased with exercise training (i.e. its trainability) varies massively between subjects, independent of each subject's V̇ _O2,max in the absence of training (i.e. their sedentary V̇ _O2,max), and with a similarly high heritability. Athletic as well as public health interests have prompted a search for the genetic profile of sedentary V̇ _O2,max and of trainability. Candidate-gene studies, gene-expression studies and genome-wide-association studies (GWAS) have not been able to identify a genetic signature that distinguishes subjects or athletes with a favorable V̇ _O2,max phenotype or a high trainability from controls. Here, I propose that multigenetic phenotypes such as V̇ _O2,max are emergent properties of multiple underlying transcriptomic networks modified by epistasis, the epigenome and the epitranscriptome. The genetic approach is thus considered to be necessary but insufficient for furthering our understanding of multigenetic higher-level functions.

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.

Somatic, Endurance Performance and Heart Rate Variability Profiles of Professional Soccer Players Grouped According to Age

This cross-sectional study compared somatic, endurance performance determinants and heart rate variability (HRV) profiles of professional soccer players divided into different age groups: GI (17–19.9 years; n = 23), GII (20–24.9 years; n = 45), GIII (25–29.9 years; n = 30), and GIV (30–39 years; n = 26). Players underwent somatic and HRV assessment and maximal exercise testing. HRV was analyzed by spectral analysis of HRV, and high (HF) and low (LF) frequency power was transformed by a natural logarithm (Ln). Players in GIV (83 ± 7 kg) were heavier (p < 0.05) compared to both GI (73 ± 6 kg), and GII (78 ± 6 kg). Significantly lower maximal oxygen uptake (VO2max, ml•kg^-1•min^-1) was observed for GIV (56.6 ± 3.8) compared to GI (59.6 ± 3.9), GII (59.4 ± 4.2) and GIV (59.7 ± 4.1). All agegroups, except for GII, demonstrated comparable relative maximal power output (Pmax). For supine HRV, significantly lower Ln HF (ms2) was identified in both GIII (7.1 ± 0.8) and GIV (6.9 ± 1.0) compared to GI (7.9 ± 0.6) and GII (7.7 ± 0.9). In conclusion, soccer players aged >25 years showed negligible differences in Pmax unlike the age group differences demonstrated in VO2max. A shift towards relative sympathetic dominance, particularly due to reduced vagal activity, was apparent after approximately 8 years of competing at the professional level.

Heart rate variability in the standing position reflects training adaptation in professional soccer players

PURPOSE

To show that heart rate variability (HRV) in the standing position better reflects the way in which athletes adapt to training in so-called intermittent sports than the indicator of resting parasympathetic tone usually employed in endurance sports.

METHODS

Twenty professional soccer players (intermittent sport) took part in a 5-week training session divided into three successive periods: "Warm-up", "Intensive training" and "Tapering". At the beginning and end of each of the three periods, a stand test was carried out and the heart rate was recorded, beat by beat (Polar Team 2). We analysed HRV to determine the indicator mostly used to demonstrate training adaptation in endurance sports (lnRMSSD supine, natural logarithm of root mean square of the successive differences) as well as indicators obtained by means of spectral analysis in both supine and standing position.

RESULTS

A decrease in heart rate was observed in the supine position at rest during training (-5.2 ± 1.3 bpm) while lnRMSSD and spectral analysis indicators remained unchanged. The "Warm-up" caused an increase in spectral analysis total power in standing position which was further highlighted by "Tapering" (3.39 ± 0.09, 3.61 ± 0.08 and 3.65 ± 0.09 log ms(2), respectively). However, the autonomic changes are probably more complex than a change in autonomic activity or balance since spectral analysis autonomic indicators remained unchanged.

CONCLUSIONS

HRV in the standing position could monitor training adaptation in intermittent sports contrary to the indicator usually employed in endurance sports. However, the significance of the HRV change in the standing position during training remains unclear.