Search Results

Purpose: To investigate the indirect measurement of 1-repetition-maximum (1RM) free-weight half-squat in high-level sprinters using the load–velocity relationship. Methods: Half-squat load and velocity data from 11 elite sprinters were collected in 2 separate testing sessions. Approximately 24 hours prior to the first testing session, sprinters completed a fatiguing high-intensity training session consisting of running intervals, staircase exercises, and body-weight exercises. Prior to the second testing session, sprinters had rested at least 48 hours. Two different prediction models (multiple-point method, 2-point method) were used to estimate 1RM based on the load and either mean or peak concentric velocity data of submaximal lifts (40%–90% 1RM). The criterion validity of all methods was examined through intraclass correlation coefficients, coefficient of variation (CV%), Bland–Altman plots, and the SEM. Results: None of the estimations were significantly different from the actual 1RM. The multiple-point method showed higher intraclass correlation coefficients (.91 to .97), with CVs from 3.6% to 11.7% and SEMs from 5.4% to 10.6%. The 2-point method showed slightly lower intraclass correlation coefficients (.76 to .95), with CVs 1.4% to 17.5% and SEMs from 9.8% to 26.1%. Bland–Altman plots revealed a mean random bias in estimation of 1RM for both methods (mean and peak velocity) ranging from 1.06 to 13.79 kg. Conclusion: Velocity-based methods can be used to roughly estimate 1RM in elite sprinters in the rested and fatigued conditions. However, all methods showed variations that limit their applicability for accurate load prescription for individual athletes.

Purpose: Inflammatory cytokines including interleukin-6 can upregulate hepcidin and decrease iron absorption. Endurance exercise is associated with transient increases in cytokines, which may alter the risk of iron deficiency (ID). This study examined whether chronic elevations in basal levels of cytokines and hepcidin were associated with ID in highly trained runners. Methods: Fifty-four collegiate runners (26 males and 28 females) living at ∼1625 m were recruited from an NCAA Division I cross-country team for this prospective cohort study. Over 2 seasons, fasted, preexercise blood draws were performed in the morning 4 times per season and were analyzed for hemoglobin concentration, ferritin, soluble transferrin receptor (sTfR), hepcidin, and 10 cytokines. Stages of ID were defined using ferritin, sTfR, and hemoglobin concentration. During the study, a registered dietician provided all runners with iron supplements using athletic department–created guidelines. Results: Fifty-seven percent of females and 35% of males exhibited stage 2 ID (ferritin <20 ng/mL or sTfR >29.5 nmol/L) at least once. Cytokines, ferritin, and sTfR exhibited changes through the 2 years, but changes in cytokines were not associated with alterations in hepcidin, ferritin, or sTfR. In males and females, lower ferritin was associated with lower hepcidin (both P < .0001). One female exhibited higher hepcidin and lower iron stores compared with other individuals, suggesting a different etiology of ID. Conclusion: ID is common in highly trained collegiate runners. In general, the high prevalence of ID in this population is not associated with alterations in basal hepcidin or cytokine levels.

Purpose: To compare the effects of variable-resistance complex training (VRCT) versus traditional complex training (TCT) on muscle architecture in rugby league players during a 6-week mesocycle. Methods: Twenty-four rugby league players competing in the British University & Colleges Sport (BUCS) Premier North Division were randomized to VRCT (n = 8), TCT (n = 8), or control (n = 8). Experimental groups completed a 6-week lower-body complex training intervention (2×/wk), which involved alternating high-load resistance exercise with plyometric exercise in the same session. The VRCT group performed resistance exercises at 70% of 1-repetition maximum (1RM) + 0% to 23% of 1RM from band resistance with a 90-second intracontrast rest interval, whereas the TCT group performed resistance exercise at 93% of 1RM with a 4-minute intracontrast rest interval. Muscle thickness (MT), pennation angle, and fascicle length (L _f) were assessed for the vastus lateralis (VL) and gastrocnemius medialis using ultrasound imaging. Results: Both TCT and VRCT groups significantly improved VL MT and VL L _f compared with control (all P < .05). Standardized within-group changes in MT and L _f (Cohen d _av  ± 95% CI) were moderate for TCT (d _av  = 0.91 ± 1.0; d _av  = 1.1 ± 1.1) and unclear for VRCT (d _av  = 0.44 ± 0.99; d _av  = 0.47 ± 0.99), respectively. Differences in change scores between TCT and VRCT were unclear. Conclusions: VRCT and TCT can be utilized during the competitive season to induce favorable MT and L _f muscle architecture adaptations for the VL. TCT may induce greater muscle architecture adaptations of the VL, whereas VRCT may be of more practical value given the shorter intracontrast rest interval between resistance and plyometric exercises.

Purpose: To compare the effects of variable-resistance complex training (VRCT) versus traditional complex training (TCT) on strength, power, speed, and leg stiffness (K_leg) in rugby league players during a 6-week mesocycle. Methods: Twenty-four rugby league players competing in the British University and Colleges Sport Premier North Division were randomized to VRCT (n = 8), TCT (n = 8), or control (CON; n = 8). Experimental groups completed a 6-week lower-body complex training intervention (2×/wk) that involved alternating high-load resistance exercise with plyometric exercise within the same session. The VRCT group performed resistance exercises at 70% of 1-repetition maximum (1RM) + 0% to 23% of 1RM from band resistance with a 90-second intracontrast rest interval, whereas the TCT group performed resistance exercise at 93% of 1RM with a 4-minute intracontrast rest interval. Back-squat 1RM, countermovement jump peak power, reactive strength index, sprint times, and K_leg were assessed pretraining and posttraining. Results: VRCT and TCT significantly improved 1RM back squat, countermovement jump peak power, and 5-m sprint time (all P < .05). VRCT also improved K_leg, whereas TCT improved 10- and 20-m sprint times (all P < .05). Between groups, both VRCT and TCT improved 1RM back squat compared with CON (both P < .001). Additionally, VRCT improved K_leg compared with CON (right leg: P = .016) and TCT improved 20-m sprint time compared with CON (P = .042). Conclusions: VRCT and TCT can be implemented during the competitive season to improve strength, power, and 5-m sprint time. VRCT may lead to greater improvements in reactive strength index and K_leg, whereas TCT may enhance 10- and 20-m sprint times.

Purpose: Velocity-based training is used to prescribe and monitor resistance training based on velocity outputs measured with tracking devices. When tracking devices are unavailable or impractical to use, perceived velocity loss (PVL) can be used as a substitute, assuming sufficient accuracy. Here, we investigated the accuracy of PVL equal to 20% and 40% relative to the first repetition in the bench-press exercise. Methods: Following a familiarization session, 26 resistance-trained men performed 4 sets of the bench-press exercise using 4 different loads based on their individual load–velocity relationships (∼40%–90% of 1-repetition maximum [1RM]), completed in a randomized order. Participants verbally reported their PVL at 20% and 40% velocity loss during the sets. PVL accuracy was calculated as the absolute difference between the timing of reporting PVL and the actual repetition number corresponding to 20% and 40% velocity loss measured with a linear encoder. Results: Linear mixed-effects model analysis revealed 4 main findings. First, across all conditions, the absolute average PVL error was 1 repetition. Second, the PVL accuracy was not significantly different between the PVL thresholds (β = 0.16, P = .267). Third, greater accuracy was observed in loads corresponding to the midportion of the individual load–velocity relationships (∼50%–60% 1RM) compared with lighter (<50% 1RM, β = 0.89, P < .001) and heavier loads (>60% 1RM, 0.63 ≤ β ≤ 0.84, all P values < .001). Fourth, PVL accuracy decreased with consecutive repetitions (β = 0.05, P = .017). Conclusions: PVL can be implemented as a monitoring and prescription method when velocity-tracking devices are impractical or absent.