Search

Fatigue has the potential to alter how impact forces are absorbed during running, heightening the risk of injury. Conflicting findings exist regarding alterations in both kinematics and plantar pressure. Thus, this systematic review and subsequent meta-analysis were conducted to investigate the impact of general and localized muscle fatigue on kinematics and plantar pressure distribution during running. Initial searches were executed on 30 November 2021 and updated on 29 April 2023, encompassing PubMed, The Cochrane Library, SPORTDiscus, and Web of Science without imposing any restrictions on publication dates or employing additional filters. Our PECOS criteria included cross-sectional studies on healthy adults during their treadmill running to mainly evaluate local muscle fatigue, plantar pressure distribution, biomechanics of running (kinematics, kinetics, and EMG results), and temporospatial parameters. The literature search identified 6626 records, with 4626 studies removed for titles and abstract screening. Two hundred and one articles were selected for full-text screening, and 20 studies were included in qualitative data synthesis. The pooled analysis showed a non-significant decrease in maximum pressure under the right forefoot's metatarsus, which was more than the left rearfoot after local muscle fatigue at a velocity of 15 km/h ( p -values = 0.48 and 0.62). The results were homogeneous and showed that local muscle fatigue did not significantly affect the right forefoot's stride frequency and length ( p -values = 0.75 and 0.38). Strength training for the foot muscles, mainly focusing on the dorsiflexors, is recommended to prevent running-related injuries. Utilizing a standardized knee and ankle joint muscle fatigue assessment protocol is advised. Future experiments should focus on various shoes for running and varying foot strike patterns for injury prevention.

This study aimed to examine the effects of manipulating the rest intervals during sprint interval training (SIT) on post-exercise hypotension and within-session oxygen consumption.Thirty healthy, trained adults (aged 30.9 ± 8.7 years; 14 males, 16 females; BMI 22.1 ± 2.3 kg/m 2 ; VO 2 max 50.7 ± 7.8 ml/kg/min) completed two different SIT protocols (4x 30-seconds all-out cycling sprints) with a one-week washout period. Sprint bouts were separated by either 1 (R1) or 3 (R3) minutes of active recovery. Both before and throughout the 45 min after the training, peripheral systolic (pSBP) and diastolic (pDBP) blood pressure, central systolic (cSBP) and diastolic (cDBP) blood pressure, aortic pulse wave velocity (aPWV), stroke volume (SV), and heart rate (HR) were assessed. Throughout the SIT protocols, oxygen consumption (VO 2 ) was monitored.There were no significant differences in time spent at 75%, 85%, 95%, and 100% of maximal VO 2 between R1 and R3. After R3, there was a significant reduction in pSBP, pDBP, cSBP, cDBP, and aPWV. After R1, there were no changes in the respective parameters. There were significant interaction effects in pSBD ( p  < 0.001), pDBP ( p  < 0.001), cSBP ( p  < 0.001), cDBP ( p  = 0.001), and aPWV ( p  = 0.033). HR significantly increased after both conditions. Only R1 resulted in a significant reduction in SV.Longer resting intervals during SIT bouts seem to result in more substantial post-exercise hypotension effects. Time spent at a high percentage of maximal VO 2 was not affected by rest interval manipulation.

This study assessed the post-exercise hypotension (PEH) effect in a sample of matched young and older adults after different sprint interval training (SIT) protocols. From forty-three participants enrolled in this study, twelve younger (24 ± 3 years) and 12 older (50 ± 7 years) participants, matched for the body mass index, systolic blood pressure, and VO 2 max-percentiles, were selected. The participants completed two SIT protocols consisting of 4 × 30 s exercise bouts interspersed by either one (SIT1) or three minutes (SIT3) of active rest. The peripheral systolic (pSBP) and diastolic (pDBP) blood pressure, central systolic (cSBP) and diastolic (cDBP) blood pressure, pulse wave velocity (PWV), and heart rate (HR) were obtained before and at different measurement time points (t5, t15, t30, t45) after the exercise. No significant time × group interactions were detected in pSBP ( p = 0.242, η² = 0.060), pDBP ( p = 0.379, η² = 0.046), cSBP ( p = 0.091, η² = 0.861), cDBP ( p = 0.625, η² = 0.033), PWV ( p = 0.133, η² = 0.076), and HR ( p = 0.190, η² = 0.123) after SIT1. For SIT3 no significant time × group interactions could be detected for pSBP ( p = 0.773, η² = 0.020), pDBP ( p = 0.972, η² = 0.006), cSBP ( p = 0.239, η² = 0.060), cDBP ( p = 0.535, η² = 0.036), PWV ( p = 0.402, η² = 0.044), and HR ( p = 0.933, η² = 0.009). Matched samples of young and older adults reveal similar PEH effects after HIIT. Accordingly, age does not seem to affect PEH after SIT. These results show that rest interval length and age modulate the PEH effect after SIT.

Due to physiological and morphological differences, younger and older athletes may recover differently from training loads. High-intensity interval training (HIIT) protocols are useful for studying the progression of recovery. It was the objective of this study to determine age differences in performance and recovery following different HIIT protocols., Methods: 12 younger (24.5 ± 3.7 years) and 12 older (47.3 ± 8.6 years) well-trained cyclists and triathletes took part in this study. Between the age groups there were no significant differences in relative peak power to fat-free mass, maximal heart rate (HR), training volume, and VO 2max -percentiles (%). Participants performed different HIIT protocols consisting of 4 × 30 s Wingate tests with different active rest intervals (1, 3, or 10 min). Peak and average power, lactate, HR, respiratory exchange ratio (RER), subjective rating of perceived exertion (RPE), and recovery (Total Quality Recovery scale, TQR) were assessed., Results: During the different HIIT protocols, metabolic, cardiovascular, and subjective recovery were similar between the two groups. No significant differences were found in average lactate concentration, peak and average power, fatigue (%), %HR max , RER, RPE, and TQR values between the groups ( p > 0.05)., Conclusion: The findings of this study indicate that recovery following HIIT does not differ between the two age groups. Furthermore, older and younger participants displayed similar lactate kinetics after the intermittent exercise protocols.

There is only very limited data examining cardiovascular responses in real-world endurance training/competition. The present study examines the influence of a marathon race on non-linear dynamics of heart rate (HR) variability (HRV). Eleven male recreational runners performed a self-paced marathon road race on an almost flat profile. During the race, heart rate and beat-to-beat (RR) intervals were recorded continuously. Besides HRV time-domain measurements, fractal correlation properties using short-term scaling exponent alpha1 of Detrended Fluctuation Analysis (DFA-alpha1) were calculated. The mean finishing time was 3:10:22 ± 0:17:56 h:min:s with a blood lactate concentration of 4.04 ± 1.12 mmol/L at the end of the race. Comparing the beginning to the end segment of the marathon race (Begin vs. End) significant increases could be found for km split time (p < .001, d = .934) and for HR (p = .010, d = .804). Significant decreases could be found for meanRR (p = .013, d = .798) and DFA-alpha1 (p = .003, d = 1.132). DFA-alpha1 showed an appropriate dynamic range throughout the race consisting of both uncorrelated and anti-correlated values. Lactate was consistent with sustained high intensity exercise when measured at the end of the event. Despite the runners slowing after halfway, DFA-alpha1 continued to fall to values seen in the highest intensity domain during incremental exercise testing in agreement with lactate assessment. Therefore, the discrepancy between the reduced running pace with that of the decline of DFA-alpha1, demonstrate the benefit of using this dimensionless HRV index as a biomarker of internal load during exercise over the course of a marathon race., (© Journal of Sports Science and Medicine.)

Purpose: To identify whether the use of active recovery (ACT) the day after high-intensity interval training (HIIT) benefits recovery and to assess whether individual responses to ACT are repeatable., Methods: Eleven well-trained, male intermittent-sport athletes (age: 25.5 ± 1.8 y) completed 4 HIIT sessions, each separated by a 2-week washout period. Of the 4 sessions, 2 were followed by passive recovery (PAS) and 2 by 60 minutes of moderate biking (ACT) 24 hours postexercise in the following sequences: ACT→PAS→ACT→PAS or PAS→ACT→PAS→ACT. Before and after HIIT and after 24 and 48 hours of recovery, maximal voluntary isometric strength (MVIC), countermovement jump height (CMJ), tensiomyographic markers of muscle fatigue (TMG), serum concentration of creatine kinase (CK), muscle soreness (MS), and perceived stress state (PS) were determined., Results: A 3-way repeated-measure analysis of variance with a triple-nested random effects model revealed a significant (P < .05) fatigue-related time effect of HIIT on markers of fatigue (MVIC↓; CMJ↓; TMG↑; CK↑; MS↑; PS↑). No significant (P > .05) main effect of recovery strategy was detected. In 9 subjects, the individual results revealed inconsistent and nonrepeatable responses to ACT, while a consistent and repeatable positive or negative response to ACT was found in 2 individuals., Conclusions: The repeated failure of ACT to limit the severity of fatigue was found both at the group level and with most individuals. However, a small percentage of athletes may be more likely to benefit repeatedly from either ACT or PAS. Therefore, the use of ACT should be individualized.

Postexercise recovery is a fundamental component for continuous performance enhancement. Due to physiological and morphological changes in aging and alterations in performance capacity, athletes of different ages may recover at different rates from physical exercise. Differences in body composition, physiological function, and exercise performance between men and women may also have a direct influence on restoration processes., Purpose: This brief review examines current research to indicate possible differences in recovery processes between male and female athletes of different age groups. The paper focuses on postexercise recovery following sprint and endurance tests and tries to identify determinants that modulate possible differences in recovery between male and female subjects of different age groups., Results: The literature analysis indicates age- and sex-dependent differences in short- and long-term recovery. Short-term recovery differs among children, adults, and masters. Children have shorter lactate half-life and a faster cardiac and respiratory recovery compared to adults. Additionally, children and masters require shorter recovery periods during interval bouts than trained adults. Trained women show a slower cardiac and respiratory recovery compared to trained men. Long-term recovery is strongly determined by the extent of muscle damage. Trained adults tend to have more extensive muscle damage compared to masters and children., Conclusion: The influence of age and sex on the recovery process varies among the different functional systems and depends on the time of the recovery processes. Irrespective of age and sex, the performance capacity of the individual determines the recovery process after high-intensity and endurance exercise.

Due to physiological and anatomical sex differences, there are variations in the training response, and the recovery periods following exercise may be different. High-intensity interval training (HIIT) protocols are well-suited to differentially investigate the course of recovery. This study was conducted to determine sex-specific differences in the recovery following HIIT intervals interspersed with recovery phases of different lengths., Methods: Well-trained cyclists and triathletes (n = 11 females, n = 11 males) participated in this study. There were no significant sex differences in maximal heart rate (HR), relative peak power to body mass and fat-free mass, training volume, and VO 2max -percentiles (females: 91.8 ± 5.5 %, males: 94.6 ± 5.4 %). A 30 s Wingate test was performed four times, separated by different active recovery periods (1, 3, or 10 min). Lactate, HR, oxygen uptake, and subjective rating of exertion and recovery were determined., Results: For the recovery time of three and ten minutes, men showed significantly higher lactate concentrations ( p = 0.04, p = 0.004). Contrary, HR recovery and subjective recovery were significant slower in women than in men., Conclusion: During HIIT, women may be more resistant to fatigue and have a greater ability to recover metabolically, but have a slower HR and subjective recovery.

Background: Intermittent fasting (IF) combined with exercise has been suggested to enhance weight loss. However, both procedures might negatively influence acid-base status. The aim of this study was to determine the combined effects of IF, exercise training and alkaline supplementation in overweight subjects on body composition and running performance., Methods: 80 overweight subjects of age 45.5 ± 7.8 years were assigned to IF or non-intermittent fasting (nIF). Furthermore, subjects were randomly assigned to take either an alkaline supplement (IF-v, nIF-v) or a placebo (IF-p, nIF-p) twice a day. All subjects performed a personalized endurance exercise program (3-4 times/week for 12 weeks). Body weight, body composition, running performance and acid-base parameters were determined before (pre) and after the 12-week program (post)., Results: 68 participants completed the study. There was a significant effect on body weight loss, body fat loss, visceral fat loss and running performance enhancement in all groups ( p < 0.01) for pre and post measurements. Body weight decreased in all groups (IF-p: -5.80 ± 0.77 kg and nIF-p: -3.40 ± 0.58 kg; IF-v: -8.28 ± 0.75 kg and nIF-v: -5.59 ± 0.87 kg). In both dietary strategies, weight loss was significantly further enhanced by alkaline supplementation. The increase in running velocity was significantly higher in IF combined with alkaline supplementation (IF-v 1.73 ± 0.23 km/h and IF-p 0.97 ± 0.20 km/h). In addition, alkaline supplementation increased plasma HCO 3 - concentration and urinary pH., Conclusion: Exercise training in combination with IF and alkaline supplementation is an effective strategy to reduce body weight and improve running performance in a 12-week intervention.

Objective: In two independent study arms, we determine the effects of strength training (ST) and high-intensity interval training (HIIT) overload on cardiac autonomic modulation by measuring heart rate (HR) and vagal heart rate variability (HRV). Methods: In the study, 37 well-trained athletes (ST: 7 female, 12 male; HIIT: 9 female, 9 male) were subjected to orthostatic tests (HR and HRV recordings) each day during a 4-day baseline period, a 6-day overload microcycle, and a 4-day recovery period. Discipline-specific performance was assessed before and 1 and 4 days after training. Results: Following ST overload, supine HR, and vagal HRV (Ln RMSSD) were clearly increased and decreased (small effects), respectively, and the standing recordings remained unchanged. In contrast, HIIT overload resulted in decreased HR and increased Ln RMSSD in the standing position (small effects), whereas supine recordings remained unaltered. During the recovery period, these responses were reversed (ST: small effects, HIIT: trivial to small effects). The correlations between changes in HR, vagal HRV measures, and performance were weak or inconsistent. At the group and individual levels, moderate to strong negative correlations were found between HR and Ln RMSSD when analyzing changes between testing days (ST: supine and standing position, HIIT: standing position) and individual time series, respectively. Use of rolling 2-4-day averages enabled more precise estimation of mean changes with smaller confidence intervals compared to single-day values of HR or Ln RMSSD. However, the use of averaged values displayed unclear effects for evaluating associations between HR, vagal HRV measures, and performance changes, and have the potential to be detrimental for classification of individual short-term responses. Conclusion: Measures of HR and Ln RMSSD during an orthostatic test could reveal different autonomic responses following ST or HIIT which may not be discovered by supine or standing measures alone. However, these autonomic changes were not consistently related to short-term changes in performance and the use of rolling averages may alter these relationships differently on group and individual level.