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There is no convincing evidence for the idea that a high power output at the maximal lactate steady state (POTwenty-one recreationally active participants performed stepwise incremental tests on the first and final testing day to measure GE and check for potential test-related training effects in terms of changes in the minimal lactate equivalent power output (∆PO_LEmin), 30-min constant load tests to determine MLSS, a ramp test and verification bout for [Formula: see text]O%[Formula: see text]OThese results challenge the assumption that PO

Background Current recommendations for physical exercise include information about the frequency, intensity, type, and duration of exercise. However, to date, there are no recommendations on what time of day one should exercise. The aim was to perform a systematic review with meta-analysis to investigate if the time of day of exercise training in intervention studies influences the degree of improvements in physical performance or health-related outcomes. Methods The databases EMBASE, PubMed, Cochrane Library, and SPORTDiscus were searched from inception to January 2023. Eligibility criteria were that the studies conducted structured endurance and/or strength training with a minimum of two exercise sessions per week for at least 2 weeks and compared exercise training between at least two different times of the day using a randomized crossover or parallel group design. Results From 14,125 screened articles, 26 articles were included in the systematic review of which seven were also included in the meta-analyses. Both the qualitative synthesis and the quantitative synthesis (i.e., meta-analysis) provide little evidence for or against the hypothesis that training at a specific time of day leads to more improvements in performance-related or health-related outcomes compared to other times. There was some evidence that there is a benefit when training and testing occur at the same time of day, mainly for performance-related outcomes. Overall, the risk of bias in most studies was high. Conclusions The current state of research provides evidence neither for nor against a specific time of the day being more beneficial, but provides evidence for larger effects when there is congruency between training and testing times. This review provides recommendations to improve the design and execution of future studies on this topic. Registration: PROSPERO (CRD42021246468).

Introduction Diurnal variations in physical performance can affect athletes' success in competitive sports depending on whether the time of peak performance concurs with the time of competition. The purpose of this systematic review was to investigate the diurnal variation in maximum endurance and strength performance. Methods The databases PubMed, EMBASE, and Web-of-Science were searched from inception to November 2020. The search string was externally reviewed according to PRESS guidelines, the review was conducted in accordance to PRISMA guidelines, and registered beforehand on PROSPERO. Eligibility criteria were that [1] the studies included humans, [2] any kind of maximum endurance or maximum strength test was performed at [3] a minimum of three different times of the day. There were no restrictions regarding study design, participants' sex, age or fitness levels. Results From 10,460 screened articles 63 articles met all three inclusion criteria. Meta-analysis on the harmonizable 29 studies provided evidence for diurnal variations in physical performance. In detail, the overall effect sizes (95% confidence intervals) were 0.23 (0.05; 0.40), 0.73 (0.37; 1.09), 0.39 (0.18; 0.60), and 0.79 (0.28, 1.30) for endurance exercise tests, maximum power output in Wingate-test, handgrip strength, and jump height all in favor of higher performance in the evening. The overall risk of bias in individual studies was moderately high. Conclusions There is strong evidence that anaerobic power as well as jump height are maximal between 13:00 and 19:00. There is some evidence that handgrip strength peaks between 13:00 and 21:00, but only little evidence that there is a time of peak performance in maximum endurance.

A flattening of the oxygen uptake–work rate relationship at severe exercise indicates the achievement of maximum oxygen uptake $$\left({\text{VO}}_{2\max } \right)$$ VO 2 max . Unfortunately, a distinct plateau $$\left( {{{\text{VO}}}_{2} {\text{pl}}} \right)$$ VO 2 pl at $${{\text{VO}}}_{2\max }$$ VO 2 max is not found in all participants. The aim of this investigation was to critically review the influence of research methods and physiological factors on the $${{\text{VO}}}_{2} {\text{pl}}$$ VO 2 pl incidence. It is shown that many studies used inappropriate definitions or methodical approaches to check for the occurrence of a $${{\text{VO}}}_{2} {\text{pl}}$$ VO 2 pl . In contrast to the widespread assumptions it is unclear whether there is higher $${{\text{VO}}}_{2} {\text{pl}}$$ VO 2 pl incidence in (uphill) running compared to cycling exercise or in discontinuous compared to continuous incremental exercise tests. Furthermore, most studies that evaluated the validity of supramaximal verification phases, reported verification bout durations, which are too short to ensure that $${{\text{VO}}}_{2\max }$$ VO 2 max have been achieved by all participants. As a result, there is little evidence for a higher $${{\text{VO}}}_{2} {\text{pl}}$$ VO 2 pl incidence and a corresponding advantage for the diagnoses of $${{\text{VO}}}_{2\max }$$ VO 2 max when incremental tests are supplemented by supramaximal verification bouts. Preliminary evidence suggests that the occurrence of a $${{\text{VO}}}_{2} {\text{pl}}$$ VO 2 pl in continuous incremental tests is determined by physiological factors like anaerobic capacity, $${{\text{VO}}}_{2}$$ VO 2 -kinetics and accumulation of metabolites in the submaximal intensity domain. Subsequent studies should take more attention to the use of valid $${{\text{VO}}}_{2} {\text{pl}}$$ VO 2 pl definitions, which require a cut-off at ~ 50% of the submaximal $${{\text{VO}}}_{2}$$ VO 2 increase and rather large sampling intervals. Furthermore, if verification bouts are used to verify the achievement of $${{\text{VO}}}_{{2{\text{peak}}}}$$ VO 2 peak /$${{\text{VO}}}_{2\max }$$ VO 2 max , it should be ensured that they can be sustained for sufficient durations.

Background: Grip strength is used to estimate whole-body strength for health surveillance purposes. Explosive strength is considered important, yet economic measures able to detect early deterioration of neuromuscular capabilities are lacking. Whether handgrip maximum rate of force development (GRFD) or whole-body strength tests are better predictors of lower body power than handgrip maximum strength (GFmax) and their trajectories throughout the life span are unknown. Hypothesis: GRFD should be more closely related to lower body power than GFmax, and its trajectories over the life span should more closely follow that of lower body power. Study Design: Cross-sectional. Level of Evidence: Level 2b. Methods: A total of 613 healthy participants aged 20 to 91 years were tested for countermovement jump peak power, GFmax, handgrip rate of force development, and midthigh pull peak force (MTP). Cubic splines and linear models were built for age trajectories, generalized additive models for quintile curves, and linear regression was used to assess predictive quality. Results: Peak power (Pmax) declined linearly to 60% of young adult level, with GRFD, GFmax, and MTP remaining stable up to age 50 years and then declining more sharply to 52% to 71% of young adult levels. Trajectories were similar for male and female participants. GRFD (β = 0.17) and MTP (β = 0.08) were worse predictors of Pmax than GFmax (β = 0.24) in models adjusted for age, sex, lean body mass, and vigorous physical activity levels. Conclusion: GRFD was not superior to maximum strength in predicting lower body power. For health surveillance purposes, it therefore appears that GFmax tests are more economical and equally good predictors of lower body explosive strength at older age. The data provided can be used as norm values for healthy subjects. Clinical Relevance: Incorporating countermovement jump testing for early detection of declines in explosive capabilities might be advised.

Purpose To determine age-dependent cutoff values for secondary exhaustion criteria for a general population free of exercise limiting chronic conditions; to describe the percentage of participants reaching commonly used exhaustion criteria during a cardiopulmonary exercise test (CPET); and to analyze their oxygen uptake at the respective criteria to quantify the impact of a given criterion on the respective oxygen uptake (V˙O2) values. Methods Data from the COmPLETE-Health Study were analyzed involving participants from 20 to 91 yr of age. All underwent a CPET to maximal voluntary exertion using a cycle ergometer. To determine new exhaustion criteria, based on maximal respiratory exchange ratio (RERmax) and age-predicted maximal HR (APMHR), one-sided lower tolerance intervals for the tests confirming V˙O2 plateau status were calculated using a confidence level of 95% and a coverage of 90%. Results A total of 274 men and 252 women participated in the study. Participants were nearly equally distributed across age decades from 20 to >80 yr. A V˙O2 plateau was present in 32%. There were only minor differences in secondary exhaustion criteria between participants exhibiting a V˙O2 plateau and participants not showing a V˙O2 plateau. New exhaustion criteria according to the tolerance intervals for the age group of 20 to 39 yr were: RERmax ≥ 1.13, APMHR210 - age ≥ 96%, and APMHR208 × 0.7 age ≥ 93%; for the age group of 40 to 59 yr: RERmax ≥ 1.10, APMHR210 - age ≥ 99%, and APMHR208 × 0.7 age ≥ 92%; and, for the age group of 60 to 69 yr: RERmax ≥ 1.06, APMHR210 - age ≥ 99%, and APMHR208 × 0.7 age ≥ 89%. Conclusions The proposed cutoff values for secondary criteria reduce the risk of underestimating V˙O2max. Lower values would increase false-positive results, assuming participants are exhausted although, in fact, they are not.

The aim was to determine the minimum maximum oxygen uptake (V˙O2max) criteria cut-offs in highly trained athletes (i.e., maximum RER [RERmax], maximum HR [HRmax], maximum RPE [RPEmax], and maximum blood lactate concentration [BLmax]) necessary to determine maximum oxygen uptake (V˙O2max) during cardiopulmonary exercise tests (CPET), by balancing type I and type II errors. A further aim was to investigate if the defined cutoffs would be robust to diurnal and to day-to-day variations.Data from two CPET studies involving young athletes were analyzed. In the first study, 70 male participants performed one CPET until exhaustion to define cutoffs. In the second study, eight males and five females performed one CPET on seven consecutive days at six different times of day (i.e., diurnal variation). The time of the CPET was identical on the sixth and seventh days (i.e., day-to-day variation). To ensure comparability both studies were carried out under the same conditions.Participants' mean V˙O2max was 63.0 ± 5.3 mL·kg·min. RERmax ≥1.10 was reached by 100%, HRmax ≥95% of age-predicted HRmax by 99%, RPEmax ≥19 by 100%, and BLmax ≥8 mmol·L by 100% of participants, respectively. Regarding the intraday variations, latter cutoffs were not reached in two cases for RERmax and in one case for HRmax and BLmax. Intraclass correlations for the day-to-day variability were r = 0.823 for RERmax, r = 0.828 for HRmax, and r = 0.380 for BLmax, respectively.The proposed high cut-off values for secondary criteria provide some assurance that V˙O2max may have been achieved in athletes without increasing type II errors. However, type I errors may still occur indicating that further methods such as V˙O2-plateau or V˙O2-validation may be required.

Purpose Cardiopulmonary exercise testing (CPET) is an important measurement in clinical practice and its primary outcome, maximal oxygen uptake (V[Combining Dot Above]O2peak), is inversely associated with morbidity and mortality. The purpose of this study is to provide CPET reference values for maximal and submaximal parameters across the adult age spectrum of a healthy European cohort, to compare V[Combining Dot Above]O2peak values with other reference datasets and to analyze the associations between physical activity (PA) levels and CPET parameters. Methods In this cross-sectional study, we prospectively recruited 502 participants (47% female) from 20 to 90 years old. The subjects performed a CPET on a cycle ergometer using a ramp protocol. PA was objectively and continuously measured over 14 days using a triaxial accelerometer. Quantile curves were calculated for CPET parameters. To investigate the associations between CPET parameters and PA levels, linear regression analysis was performed. Results V[Combining Dot Above]O2peak values observed in the group of 20-29 years were 46.6±7.9 and 39.3±6.5 (mL/kg/min) for males and females, respectively. On average, each age category (10-year increments) showed a 10% lower V[Combining Dot Above]O2peak relative to the next younger age category. V[Combining Dot Above]O2peak values of previous studies were, on average 7.5 (mL/kg/min) (20%) lower for males and 6.5 (mL/kg/min) (21%) lower for females. There was strong evidence supporting a positive association between V[Combining Dot Above]O2peak (mL/kg/min) and the level of habitual PA performed at vigorous PA (estimate 0.26; p Conclusion Maximal and submaximal CPET reference values over a large age range are novel and differences to other studies are clinically highly relevant. Objectively measured vigorous-intensity PA showed a strong positive association with higher V[Combining Dot Above]O2peak and other performance-related CPET parameters, supporting the implementation of higher intensity aerobic exercise in health promotion.

To examine the validity of popular smartphone accelerometer applications and a consumer activity wristband compared to a widely used research accelerometer while assessing the impact of the phone's position on the accuracy of step detection. Twenty volunteers from 2 different age groups (Group A: 18-25 years, n = 10; Group B 45-70 years, n = 10) were equipped with 3 iPhone SE smartphones (placed in pants pocket, shoulder bag, and backpack), 1 Samsung Galaxy S6 Edge (pants pocket), 1 Garmin Vivofit 2 wristband, and 2 ActiGraph wGTX+ devices (worn at wrist and hip) while walking on a treadmill (1.6, 3.2, 4.8, and 6.0 km/h) and completing a walking course. All smartphones included 6 accelerometer applications. Video observation was used as gold standard. Validity was evaluated by comparing each device with the gold standard using mean absolute percentage errors (MAPE). The MAPE of the iPhone SE (all positions) and the Garmin Vivofit was small (

Light has a stimulating effect on physical performance if scheduled according to the chronotype, but dose-dependent effects on performance have not yet been examined. Three groups of healthy men (25.1 ± 3.1 years) were exposed to light for different durations in a parallel group design before a 40-min time-trial. In each group, subjects were exposed to either bright light (BL, 4420 lx) or moderate light (ML, 230 lx) in a randomized order in a crossover design. The durations of light exposure were 120 min prior to and during exercise (2HEX; n = 16), 60 min prior to and during exercise (1HEX; n = 10), or only for 60 min prior to exercise (1H; n = 15). Total work performed during the time-trial in kJ in the 2HEX group was significantly higher in the BL setting (527 kJ) than in ML (512 kJ) (P = 0.002), but not in 1HEX (BL: 485 kJ; ML: 498 kJ) or 1H (BL: 519 kJ; ML: 514 kJ) (P = 0.770; P = 0.485). There was a significant (P = 0.006) positive dose-response relationship between the duration of light exposure and the work performed over the three doses of light exposure. A long duration light exposure is an effective tool to increase total work in a medium length time-trial in subjects normalized for their individual chronotype.

To assess which type of evening light exposure has the greatest effect on reaction time and maximum handgrip strength. These were pre-specified secondary outcomes in a trial which primarily investigated the influence of light on cycling performance. Seventy-four male athletes were allocated at random to either bright light (BRIGHT), monochromatic blue light (BLUE), or a control condition (CONTROL). Light exposure lasted for 60 min and started 17 h after the individual midpoint of sleep. Reaction time, handgrip strength, and melatonin levels were measured before and after the light exposure. We used analysis of covariance to compare the groups with respect to the investigated outcomes. Two participants had to be excluded retrospectively. The remaining 72 participants had a median age of 23 years. The adjusted difference in reaction time was −1 ms [95% confidence interval (CI) −8, 6] for participants in BRIGHT and 2 ms (95% CI −5, 9) for participants in BLUE, both relative to participants in CONTROL. The adjusted difference in handgrip strength was 0.9 kg (95% CI −1.5, 3.3) for participants in BRIGHT and −0.3 kg (95% CI −2.7, 2.0) for participants in BLUE, both relative to participants in CONTROL. After the light exposure, 17% of participants in BRIGHT, 22% in BLUE, and 29% in CONTROL showed melatonin concentrations of 2 pg/ml or higher. The results suggest that bright light might reduce melatonin levels but neither bright nor blue light exposure in the evening seem to improve reaction time or handgrip strength in athletes.