COVID-19 pandemic restrictions might have negatively affected the health-related physical fitness of children and adolescents. The aim of this study was to contrast the body composition and physical fitness data of two independent samples of children and adolescents obtained from an online database (DAFIS project) before (n = 15,287) and during (n = 2101) the first academic year of the COVID-19 pandemic. The results revealed higher values for the body mass index (p = 0.002), waist circumference (p < 0.001), and waist to hip and waist to height ratios (p < 0.001) during than before the pandemic, particularly in the case of boys. On the other hand, lower muscular fitness was observed for girls during the pandemic. Quantitative and qualitative analysis did not detect relevant changes in cardiorespiratory fitness in children or adolescents (p > 0.05). Our data suggested that pandemic constraints might have affected body composition and muscular fitness of children and adolescents. These results might be of interest for designing specific interventions oriented toward counteracting the negative effects of pandemic restrictions on health-related physical fitness.

This randomised controlled study examined the force–velocity relationship changes (force and velocity axis intercepts, slope and estimated maximum power) in response to 5-week training programmes differing in the set configuration. For each session, the traditional group performed 4 sets of 8 repetitions with 5 min of rest between sets and exercises, while the cluster group completed 16 sets of 2 repetitions with 1 min of rest between sets and 5 min between exercises. Both programmes were performed with the 10-repetition maximum load, including bench press, parallel squat, lat pull-down and leg curl exercises. Individual force-velocity profiles were obtained for bench press and squat using a linear velocity transducer before and after the intervention, along with lactate and mechanical performance during the intervention. Results showed in bench press similar changes of the force-velocity profile after both protocols (no shift of the slope and higher force and velocity axis intercept values). For the squat, significant changes in the slope (P = 0.001) and the velocity intercept (P = 0.002) towards a velocity profile were observed after cluster but not after traditional training. These results suggest that set configuration may modulate changes of force–velocity relationship, especially for squat.

The main aim of this study was to explore the variability in the load-velocity relationship through the use of multilevel mixed regression models. The relationship between relative load (% of one repetition maximum: %1RM) and velocity was obtained in a sample of high-level judokas and rugby players (8 women and 13 men) for the bench press (BP) and parallel squat (SQ). The load-velocity relationship for the squat was obtained for the external load (barbell load) and for the system mass (barbell plus body mass). The data were fitted by different multilevel mixed regression models. Including the sex factor in the models improved the goodness of fit for the BP but not for the squat exercises. All the models detected significant inter-individual variability in both intercepts and slopes (p < 0.05 in all the cases). A decrease of 0.15, 0.10 and 0.16 m/s of velocity for each 10% of increment in the relative load were estimated for BP and squat considering the external load and the system mass, respectively. The multilevel mixed regression models detected significant inter-individual variability in the slope and intercept of the load-velocity relationship what entails differences in the velocity associated with a fixed percentage (%) of the one-repetition maximum load.

Purpose: This study explored the changes in blood pressure and cardiac autonomic modulation after training programs differin in set configuration. Methods: Thirty-nine individuals were randomly assigned to a traditional, rest-redistribution, or control group. Throughout five weeks, the traditional and rest-redistribution groups performed 10 sessions of four exercises with the same load, number of repetitions, and total rest time, but with different inter-set rest duration and frequency (traditional group: 4 sets of 8 repetitions, 10 repetition maximum load, 5 min rest between sets and exercises; rest-redistribution group: 16 sets of 2 repetitions, 1 min rest between sets, 5 min rest between exercises). Heart rate and heart rate recovery were recorded during each training session, and heart rate variability, baroreflex sensitivity and effectiveness, blood pressure, and blood pressure variability were evaluated at rest bedore and after the interventions. Results: During the sessions, traditional sets entailed greater peak heart rate compared to rest-redistribution (P = .018) but mean heart rate, minimum heart rate, and heart rate recovery were similar between training programs (P >.05). Baroreflex effectiveness was reduced after the traditional intervention (P = .013). No changes were detected for the rest of the cardiovascular variables obtained at rest after intervention (P > .05). Conclusions: Despite some differences in heart rate response during exercise, neither traditional nor rest-redistribution resistance training protocols produced changes in cardiac autonomic modulation, sympathetic vasomotor tone, and cardiac baroreflex sensitivity of young healthy active individuals. However, traditional sets affected the baroreflex effectiveness.

Iglesias-Soler, E, Rial-Vázquez, J, Nine, I, Fariñas, J, Revuelta-Lera, B, and García-Ramos, A. Variability in the relationship between velocity loss and percentage of completed repetitions during horizontal leg press and bench press in postmenopausal women. J Strength Cond Res 38(9): 1576–1583, 2024—This study aimed to analyze the intersubject variability in the relationship between percentage of velocity loss (%VL) and percentage of repetitions performed out of maximum possible (%MNR) in postmenopausal women. Thirty-five postmenopausal active women (58 ± 3 years) performed sets leading to muscular failure, completing 10–13 repetitions, in both leg press (LP) and bench press (BP). Mean lift velocity of each repetition was expressed as a percentage of the fastest repetition, and repetitions were quantified as a percentage of the maximum number of repetitions completed in the set. Given the hierarchical structure of the data, %VL–%MNR relationships were fitted by linear mixed model regressions. A significant intersubject variability in the intercept (i.e., %MNR associated with 0%VL) was detected ( p < 0.001 in both LP and BP), even when centered values of the completed repetitions were included in the models. The estimated variance in the intercept for LP (117.39; SE : 45.41) was almost double that for BP (67.47; SE : 20.27). The variability observed in the intercept entailed variability in the estimated %MNR for specific %VL values. The use of velocity loss thresholds for estimating the intensity of effort in active postmenopausal women does not overcome uncertainty of more traditional methods.

Objective: This study aimed to ascertain the accuracy of measure arterial stiffness using the HUAWEI GT 3 Pro smartwatch and pOpmètre device against the SphygmoCor (algorithms: intersect tangent and maximum of the second derivate). Methods: Twenty-three physically active postmenopausal women (age: 58.9 ± 3.2 years; body mass index: 26.3 ± 4.8 kg/m²) were recruited. Carotid-femoral pulse wave velocity, finger-toe pulse wave velocity, and wrist-finger pulse wave velocity were obtained using SphygmoCor, pOpmètre and HUAWEI GT 3 Pro devices in a randomized order. Additionally, the pulse mean carotid-femoral and finger-toe pulse transit time was registered for SphygmoCor and pOpmètre, respectively. Results: Lower values of pulse wave velocity were recorded by HUAWEI in comparison with SphygmoCor with both algorithms, whereas no significant differences were detected between SphygmoCor and pOpmètre results. Pulse wave velocity values from SphygmoCor were positively correlated with pOpmètre results (r = 0.464 and r = 0.451 using intersect tangent and second derivative algorithms), whereas this was not the case with those obtained from HUAWEI. Coefficients of bias of Lin's concordance coefficients close to 1 (0.832 and 0.831 for intersect tangent and second derivative algorithm, respectively) and mean bias close to 0 from Bland-Altman analysis suggested an acceptable agreement between pulse wave velocity obtained from SphygmoCor and pOpmètre. Conclusions: Our results suggest an acceptable concordance of pulse wave velocity values recoded by SphygmoCor and pOpmètre, whereas this was not the case for data obtained from HUAWEI GT 3 Pro smartwatch. Therefore, the pOpmètre may be a viable alternative for assessing arterial stiffness, but measurement via the smartwatch device cannot be recommended.