No abstract

This aims of this study were (I) to determine the velocity variable and regression model which best fit the load-velocity relationship during the free-weight prone bench pull exercise, (II) to compare the reliability of the velocity attained at each percentage of the one-repetition maximum (1RM) between different velocity variables and regression models, and (III) to compare the within- and between-subject variability of the velocity attained at each %1RM. Eighteen men (14 rowers and four weightlifters) performed an incremental test during the free-weight prone bench pull exercise in two different sessions. General and individual load-velocity relationships were modelled through three velocity variables (mean velocity [MV], mean propulsive velocity [MPV] and peak velocity [PV]) and two regression models (linear and second-order polynomial). The main findings revealed that (I) the general (Pearson's correlation coefficient [ r ] range = 0.964–0.973) and individual (median r = 0.986 for MV, 0.989 for MPV, and 0.984 for PV) load-velocity relationships were highly linear, (II) the reliability of the velocity attained at each %1RM did not meaningfully differ between the velocity variables (coefficient of variation [CV] range = 2.55–7.61% for MV, 2.84–7.72% for MPV and 3.50–6.03% for PV) neither between the regression models (CV range = 2.55–7.72% and 2.73–5.25% for the linear and polynomial regressions, respectively), and (III) the within-subject variability of the velocity attained at each %1RM was lower than the between-subject variability for the light-moderate loads. No meaningful differences between the within- and between-subject CVs were observed for the MV of the 1RM trial (6.02% vs . 6.60%; CV ratio = 1.10), while the within-subject CV was lower for PV (6.36% vs . 7.56%; CV ratio = 1.19). These results suggest that the individual load-MV relationship should be determined with a linear regression model to obtain the most accurate prescription of the relative load during the free-weight prone bench pull exercise.

AimTo determine the absolute and relative reliability of functional trunk tests, using a functional electromechanical dynamometer to evaluate the isokinetic strength of trunk flexors and to determine the most reliable assessment condition, in order to compare the absolute and relative reliability of mean force and peak force of trunk flexors and to determine which isokinetic condition of evaluation is best related to the maximum isometric.MethodsTest-retest of thirty-seven physically active male student volunteers who performed the different protocols, isometric contraction and the combination of three velocities (V1 = 015 m s−1 , V2 = 0.30 m  s−1, V3 = 0.45 m s−1) and two range of movement (R1 = 25% cm ; R2 = 50% cm) protocols.ResultsAll protocols to evaluate trunk flexors showed an absolute reliability provided a stable repeatability for isometric and dynamic protocols with a coefficient of variation (CV) being below 10% and a high or very high relative reliability (0.69 < intraclass correlation coefficient [ICC] > 0.86). The more reliable strength manifestation (CV = 6.82%) to evaluate the concentric contraction of trunk flexors was mean force, with 0.15 m  s−1 and short range of movement (V1R1) condition. The most reliable strength manifestation to evaluate the eccentric contraction of trunk flexors was peak force, with 0.15 m  s−1 and a large range of movement (V1R2; CV = 5.07%), and the most reliable way to evaluate isometric trunk flexors was by peak force (CV = 7.72%). The mean force of eccentric trunk flexor strength with 0.45 m  s−1 and short range of movement (V3R1) condition (r = 0.73) was best related to the maximum isometric contraction.ConclusionFunctional electromechanical dynamometry is a reliable evaluation system for assessment of trunk flexor strength.

Cuevas-Aburto, J, Jukic, I, Chirosa-Ríos, LJ, González-Hernández, JM, Janicijevic, D, Barboza-González, P, Guede-Rojas, F, and García-Ramos, A. Effect of traditional, cluster, and rest redistribution set configurations on neuromuscular and perceptual responses during strength-oriented resistance training. J Strength Cond Res 36(6): 1490–1497, 2022—This study aimed to compare the acute effect of traditional (TR), cluster (CL), and rest redistribution (RR) set configurations on neuromuscular and perceptual measures of fatigue. Thirty-one resistance-trained men randomly performed a Control session and 3 experimental sessions consisting of the squat (SQ) and bench press (BP) exercises performed against the 10 repetition maximum load using TR (3 sets of 6 repetitions; 3 minutes of interset rest), CL (3 sets of 6 repetitions; 30 seconds of intraset rest every 2 repetitions; 3 minutes of interset rest), and RR (9 sets of 2 repetitions; 45 seconds of interset rest) set configurations. A significant effect of “set configuration” (p = 0.002) was observed for barbell velocity. The average velocity of the training session was lower for TR compared with CL (% difference = 5.09% in SQ and 5.68% in BP) and RR (% difference = 5.92% in SQ and 2.71% in BP). The 3 set configurations induced comparable decrements in countermovement jump height (% difference from −6.0% to −8.1%) and throwing velocity (% difference from −0.6% to −1.2%). Ratings of perceived exertion (RPE-10) values collected after the sets were higher for TR (SQ: 6.9 ± 0.7 a.u.; BP: 6.8 ± 0.8 a.u.) compared with CL (SQ: 6.2 ± 0.8 a.u.; BP: 6.4 ± 0.7 a.u.) and RR (SQ: 6.2 ± 0.8 a.u.; BP: 6.6 ± 0.9 a.u.), while the session RPE did not differ between the set configurations (p = 0.595). CL and RR set configurations allow for higher velocities and lower RPE values during resistance training sessions not performed to failure in comparison with a TR set configuration.

Background: The purpose of this study was to determine the reliability for the strength and movement velocity of the concentric phase from the five Sit-to-Stand (5STS), using three incremental loads measured by a functional electromechanical dynamometer (FEMD) in healthy young adults. Methods: The average and peak strength and velocity values of sixteen healthy adults (mean ± standard deviation (SD): age = 22.81 ± 2.13 years) were recorded at 5, 10 and 15 kg. To evaluate the reliability of FEMD, the intraclass correlation coefficient (ICC), standard error of measurement (SEM) and coefficient of variation (CV) were obtained. Results: Reliability was high for the 10 kg (CV range: 3.70–4.18%, ICC range: 0.95–0.98) and 15 kg conditions (CV range: 1.64–3.02%, ICC: 0.99) at average and peak strength, and reliability was high for the 5 kg (CV range: 1.71–2.84%, ICC range: 0.96–0.99), 10 kg (CV range: 0.74–1.84%, ICC range: 0.99–1.00) and 15 kg conditions (CV range: 0.79–3.11%, ICC range: 0.99–1.00) at average and peak velocity. Conclusions: The findings of this study demonstrate that FEMD is a reliable instrument to measure the average and peak strength and velocity values during the five STS in healthy young adults.

Grip strength is higher in men than women, it decreases with age and is higher in the dominant hand.

Background: Maximal voluntary isometric handgrip strength (MVIHS) is influenced by age, sex, and handedness. Aim: To assess the association of MVIHS with age, sex, and handedness in older adults. Material and Methods: MVIHS was measured using a digital dynamometer in 60 men and 60 women aged 73 ± 6 years. Weight, height and handedness were also recorded. For analysis purposes, participants were divided into two age groups (65 to 70.9 years of age and ≥ 71 years). Results: A negative correlation was observed between age and MVIHS in the non-dominant (r = -0.65 and -0.59 in men and women, respectively) and dominant hands (r = -0.71 and -0.64 in men and women, respectively). When age and MVIHS were correlated in the group aged 65-70 years, a significant correlation was observed in the non-dominant (r = -045 and -0.61 in men and women, respectively) and dominant hands (r = -0.47 and -0.64 in men and women, respectively). In the group aged ≥ 71 years, a stronger correlation with age was also observed in the non-dominant (r = -0.92 and -0.90 in men and women, respectively) and dominant hands (r = -0.95 and -0.90 in men and women, respectively). MVIHS was 2.8 to 8.9% lower in the non-dominant than in the dominant hand in all age groups. MVIHS was lower in women than in men in both age groups. Conclusions: MVIHS declines with age (especially after 71 years of age), is higher in men than women, and higher in the dominant than the non-dominant hand.

Background: The functional fitness of older people may be associated with their nutritional status. Aim: To assess the association between of anthropometric measures with functional fitness in older people. Material and Methods: Cross-sectional study conducted in 75 participants aged 65 to 89 years. Body mass index (BMI), waist-to-height ratio (WHtR), fat mass (FM) and skeletal muscle mass index (SMI) were calculated from anthropometric measures. The functional fitness was determined using the Senior Fitness Test battery. Results: BMI and FM indicated obesity, and WHtR indicated cardiometabolic risk in 49%, 55% and 83% of participants, respectively. SMI indicated a low muscle mass in 91% of females. Performance standards of chair stand, arm curl, 2-min step test and 8-foot up-and-go tests were met in 1%, 8%, 1% and 89% of participants, respectively. Significant negative correlations were found between 2-min step test and BMI, WHtR and FM (r =-0.26,-0.31 and-0.48 respectively). Back scratch had a negative correlation with BMI (r =-0.23) and SMI (rho =-0.28). Significant positive correlations were found between 8-foot up-and-go, WHtR (rho = 0.28) and FM (rho = 0.23), and between 2-min step test and SMI (rho = 0.28). The coefficient of determination (R²) between 2-min step test with BMI, WHtR and FM were 0.05, 0.08 and 0.22, respectively, while the R² between back scratch and BMI was 0.04. Multiple regression models indicated that FM affected the 2-min step test independently of BMI and WHtR (adjusted R² = 0.22), however age and sex negatively influenced these associations. Conclusions: Functional fitness of older adults is influenced by nutritional anthropometric measures, particularly BMI, WHtR and FM for aerobic capacity, and BMI for upper limb flexibility.