3000-m Performance Research Articles

Influence of the carbon fiber plate curvature of advanced footwear technology on the running energetic cost and 3000-m performance

This study aimed to explore the effect of two similar commercialized advanced footwear technology models differing mainly in their plate geometry (i.e., low and high curvature plate) on the running energetic cost in both non-fatigued and fatigued states. It also sought to determine their impacts on 3000-m performance. Twelve highly trained male athletes performed four 5-min trials (two advanced technology models, two trials). In each experimental session, athletes completed a 3000-m trial which was followed by a 5-min trial to test the running energetic cost when fatigued. Athletes exhibited a lower running energetic cost when wearing the low curvature plate in a non-fatigued state (P = 0.034; − 1.13 [− 1.92 to − 0.11] %), which persisted with better performance in the 3000-m trial (P = 0.017; − 0.42 [− 0.74 to − 0.09] %). However, in a fatigued state, non-significant differences were reported (P = 0.207). The low curvature plate seems to be more effective than the high curvature plate when running at low intensity in a fresh state as well as in a maximal high-intensity effort. However, non-significant differences between plate geometries were observed when fatigue was increased.

Prediction of 3000-m Running Performance Using Classic Physiological Respiratory Responses

Introduction: Knowing which physiological variables predict running performance could help coaches to optimize training prescription to improve running performance. Objective: The present study investigated which physiological respiratory responses could predict 3000-m running performance. Methods: Seventeen amateur runners (29.82±7.1years; 173.12±9.0cm; 64.59±9.3kg) performed a maximal graded running test on a treadmill. The ventilatory threshold (VT), respiratory compensation point (RCP), and maximal oxygen consumption (VO2max) were assessed, as well as the respective velocities (vVT, vRCP, vVO2max). After 72 to 96 hours the runners performed the 3000-m running field test. The relationships between variables were performed using Pearson product momentum correlations. Thereafter, simple and multiple regression models were applied. The significance level adopted was 5% (p<0.05). Results: The majority of physiological responses were positive and well related to each other (r≥0.70; p<0.05). Despite vVT, vRCP, and vVO2max demonstrating a higher and inverse relationship with 3000-m time (r=-0.92; r =-0.96; r =-0.89; p<0.05), the multiple regression model indicated that vRCP and vVO2max are the best variables to predict 3000-m performance in experienced amateur road runners (R2=0.94). The equation proposed by the model was: 3000-m(s)=1399.21–[31.65*vRCP(km.h-1)]–[12.06*vVO2max (km.h-1)]. Conclusion: The vRCP and vVO2max may be used to predict 3000-m performance using only a maximal running test on a treadmill. In practical terms, coaches and physical conditioners can use performance in the 3000-m to select different exercise running intensities to prescribe exercise training intensities.

The Effect of Physiological Performance Variables on 3000m Times in Collegiate Mid-Distance and Distance Runners

Collegiate mid-distance (MD) runners and distance (D) runners compete in the 3000m. Previous research has identified VO2max, velocity at lactate threshold (vLT), %VO2max at lactate threshold, and running economy (RE) to correlate with 3000m performance. Research is lacking on if differences in these variables, and pacing strategy, affects 3000m performance between groups. PURPOSE: To identify how physiological performance variables relate to 3000m time, and if differences in these variables, and pacing strategies, occurs between groups. METHODS: 11 male NCAA Division II runners (5 MD, 6 D) were used. Subjects completed a 3000m time trial on a synthetic 200m indoor track, where 3000m time and split times were recorded using a single-beam timing gate. A discontinuous 3-minute stage lactate threshold protocol was used to measure vLT, lactate threshold (LT), and running economy at 14.5km/h, 16km/h, and 17.5 km/h (RE14.5, RE16, RE17.5). A modified Astrand VO2max test was used to assess VO2max, with the speed set at 16.1km/h and grade increasing 2% every two minutes. RESULTS: VO2max (r=-.629), RE14.5 (r=.632), RE16 (r=.756), %VO2max at LT (r=0.675), 600-1200m time (r=.784), 1200-1800m time (r=.962), and 1800-2400m time (r=.719) significantly correlated to 3000m time (p<0.05), when merging subjects. In the D group, %VO2max at LT (r=.875), RE16 (r=.853), 600-1200m time (r=.882), and 1200-1800m time (r=.965) significantly correlated to 3000m time (p<0.05). In the MD group, 1200-1800m time (r=.932) significantly correlated to 3000m time (p<0.05), and VO2max had a trend towards significance with 3000m time (r=-.829, p=.083). Statistically different mean differences in VO2max (D=67.00±2.64 vs MD=63.56±1.52ml/kg/min), and vLT (D=15.10±0.19 vs MD=14.33±0.35km/h) was observed between groups (p<0.05). A graphical difference in pacing strategy was observed between groups. CONCLUSION: 1200-1800m time is the most important split time for 3000m performance. VO2max was the best physiological performance indicator in MD runners, and RE16 was the best physiological performance indicator in D runners. Runners should be trained differently according to their training status, to improve 3000m performance.

Effect of Contrast Water Therapy Duration on Recovery of Running Performance

To investigate whether contrast water therapy (CWT) assists acute recovery from high-intensity running and whether a dose-response relationship exists. Ten trained male runners completed 4 trials, each commencing with a 3000-m time trial, followed by 8 × 400-m intervals with 1 min of recovery. Ten minutes postexercise, participants performed 1 of 4 recovery protocols: CWT, by alternating 1 min hot (38°C) and 1 min cold (15°C) for 6 (CWT6), 12 (CWT12), or 18 min (CWT18), or a seated rest control trial. The 3000-m time trial was repeated 2 h later. 3000-m performance slowed from 632 ± 4 to 647 ± 4 s in control, 631 ± 4 to 642 ± 4 s in CWT6, 633 ± 4 to 648 ± 4 s in CWT12, and 631 ± 4 to 647 ± 4 s in CWT18. Following CWT6, performance (smallest worthwhile change of 0.3%) was substantially faster than control (87% probability, 0.8 ± 0.8% mean ± 90% confidence limit), however, there was no effect for CWT12 (34%, 0.0 ± 1.0%) or CWT18 (34%, -0.1 ± 0.8%). There were no substantial differences between conditions in exercise heart rates, or postexercise calf and thigh girths. Algometer thigh pain threshold during CWT12 was higher at all time points compared with control. Subjective measures of thermal sensation and muscle soreness were lower in all CWT conditions at some post-water-immersion time points compared with control; however, there were no consistent differences in whole body fatigue following CWT. Contrast water therapy for 6 min assisted acute recovery from high-intensity running; however, CWT duration did not have a dose-response effect on recovery of running performance.

Impairment of 3000-m Run Time at Altitude Is Influenced by Arterial Oxyhemoglobin Saturation

The decline in maximal oxygen uptake (ΔVO(2)max) with acute exposure to moderate altitude is dependent on the ability to maintain arterial oxyhemoglobin saturation (SaO2). This study examined if factors related to ΔVO(2)max at altitude are also related to the decline in race performance of elite athletes at altitude. Twenty-seven elite distance runners (18 men and 9 women, VO(2)max = 71.8 ± 7.2 mL·kg(-1)·min(-1)) performed a treadmill exercise at a constant speed that simulated their 3000-m race pace, both in normoxia and in 16.3% O2 (∼2100 m). Separate 3000-m time trials were completed at sea level (18 h before altitude exposure) and at 2100 m (48 h after arrival at altitude). Statistical significance was set at P ≤ 0.05. Group 3000-m performance was significantly slower at altitude versus sea level (48.5 ± 12.7 s), and the declines were significant in men (48.4 ± 14.6 s) and women (48.6 ± 8.9 s). Athletes grouped by low SaO2 during race pace in normoxia (SaO2 < 91%, n = 7) had a significantly larger ΔVO(2) in hypoxia (-9.2 ± 2.1 mL·kg(-1)·min(-1)) and Δ3000-m time at altitude (54.0 ± 13.7 s) compared with athletes with high SaO2 in normoxia (SaO2 > 93%, n = 7, ΔVO(2) = -3.5 ± 2.0 mL·kg(-1)·min(-1), Δ3000-m time = 38.9 ± 9.7 s). For all athletes, SaO2 during normoxic race pace running was significantly correlated with both ΔVO(2) (r = -0.68) and Δ3000-m time (r = -0.38). These results indicate that the degree of arterial oxyhemoglobin desaturation, already known to influence ΔVO(2)max at altitude, also contributes to the magnitude of decline in race performance at altitude.

Running Speed at Predicted Maximal Heart Rate as an Assessment of Maximal Aerobic Capacity in Trained Teenaged Runners

Purpose: The purpose of this study was to examine whether the running speed (vHRmax.pred) corresponding to a HRmax predicted by the formula [220-age (yrs)], is a useful physiologic index of endurance among trained young runners in a specified age group (12-20 yrs). Correlations were analyzed between vHRmax.pred and Vo2max, vVo2max (running speed corresponding to Vo2max,), vLT (running speed at a blood lactate level of 4 mmol·L−1), vHRmax.meas (running speed at the measured HRmax), and competitive 1500 and 3000-m performance times in 43 endurance-trained, teenaged runners (25 males, 18 females).Methods: Physiological variables (Vo2, HR, and La) were measured during progressive sub-maximal and maximal treadmill running. Running speeds corresponding to Vo2max, HRmax.meas, and HRmax.pred were estimated from regressions relating each individual's running speed to Vo2 and HR.Results: With a few exceptions, gender-specific correlation coefficients were significant between Vo2max, vVo2max, vLT, vHRmax.meas, and vHRmax.pred, with values ranging from 0.41 to 0.93 (p<0.05). vHRmax.pred was a significant predictor of running performance for both 1500 and 3000-m events (r=−0.62 and −0.52 in males, and −0.66 and −0.80 in females, respectively).Conclusion: The results suggested that vHRmax.pred is a useful predictor of endurance running performance in trained teenaged runners. This fact also suggested the possibility of developing an index of endurance running performance in untrained teenagers.