Factors Influencing Running Velocity at Lactate Threshold in Male and Female Runners at Different Levels of Performance

Changes in running economy and attainable maximal oxygen consumption in response to prolonged running: The impact of training status

During prolonged running at moderate-to-high intensity, running economy (RE) deteriorates and attainable maximal oxygen consumption (VO2max) decreases. Whether these changes appear similarly in trained and untrained runners exercising at the same relative intensity is not clear. We recruited 10 trained runners (TR) and 10 active adults (AA), and compared RE and attainable VO2max before and after 1 h of running at 70% of VO2max. Submaximal VO2 increased more (p = 0.019) in AA (0.20 ± 0.13 L min-1) than in TR (0.07 ± 0.05 L min-1). Attainable VO2max decreased in AA (-0.21 ± 0.15 L min-1, p = 0.002), but remained unchanged in TR (-0.05 ± 0.10 L min-1, p = 0.18). Relative intensity (i.e., VO2/attainable VO2max), increased more (p = 0.001) in AA (8.3 ± 4.4%) than in TR (2.6 ± 1.9%). These results demonstrate that the ability to resist changes in RE and VO2max following prolonged running is superior in trained versus untrained runners, when exercising at the same relative intensity.

Repeated-sprint sets test: a new method for evaluating and forecasting fitness in elite young male soccer players

The objective of the current study was to explore the correlation between repeated sprint sets (RSS) ability and several physical attributes, including maximum sprint speed, maximal aerobic speed, maximal anaerobic speed, aerobic capacity, and explosive strength. Moreover, the aim was to assess the suitability of RSS as a comprehensive evaluation tool for physical qualities and to determine which physical field tests most accurately predict RSS in elite young male soccer players. A total of thirty-two young elite male soccer players (mean age 14.6 ± 0.3 years; predicted years from peak height velocity (PHV): - 0.4 ± 0.3; years in training: 3.7 ± 0.5) voluntarily participated in the study. The players participated in eight consecutive specific physical tests, with a minimum 72-h recovery between each session to minimize the impact of fatigue during the second trial. The participants completed the tests in the following order: RSS test, Vam-Eval test, a constant velocity test performed until exhaustion at 100% of vVO2max (tlim100), 20-m Multi-Stage Shuttle Run test (VMSRT), Yo-Yo Intermittent Recovery Test level 1 (Yo-Yo IR1), Maximal Anaerobic Shuttle Running Test (VMASRT), Maximal Sprinting Speed Test (20-m flying sprint), Countermovement Jump (CMJ), and Standing Long Jump test (SLJ). The results of the study showed that there were very large negative correlations between tlim100 and SST (sum of sprint times), and large negative correlations between Yo-Yo IR1, Vam-Eval, and SST during RSS in young elite male soccer players (p < 0.05). Additionally, VMASRT and SLJ demonstrated a moderate negative correlation with SST (p < 0.05). In contrast, significant positive correlations were found between 20-m flying sprint and the SST (p < 0.05). According to the stepwise multiple linear regression analysis, the primary predictors of SST, ranked by importance, were tlim100 and Yo-Yo IR1. These two predictors collectively accounted for 72% of the variance in players' SST (p < 0.0001). Due to the importance of aerobic capacity and short repeated accelerations/sprint sets for overall competitive performance in soccer, in conclusion, our results suggest that elite young male soccer players should perform both high intensity interval training and aeorobic capactity exercises as part of soccer training if the primary outcome is to improve repeated sprint ability performance.

Maximal Oxygen Uptake, Muscular Oxidative Capacity, and Ventilatory Threshold in Amateur Triathletes: Eight-Month Training Follow-Up

Purpose

Endurance sports performance is influenced by several factors, including maximal oxygen uptake (⩒O2max), the percentage of ⩒O2max that can be sustained in endurance events, running economy, and body composition. Traditionally, ⩒O2max can be measured as an absolute value, adjusted for body mass, reflecting the athlete's central capacity (maximal cardiac output), or adjusted for lean mass (LM), reflecting the athlete's peripheral capacity (muscular oxidative capacity). The present study aims to evaluate absolute, total body mass, and lower limb LM-adjusted ⩒O2max, ventilatory thresholds (VT), respiratory compensation points (RCP), and body composition during two training periods separated by 8 months.

Patients and Methods

Thirteen competitive amateur triathletes [seven men (40.7±13.7 years old, 76.3±8.3kg, and 173.9±4.8cm) and six women (43.5±6.9 years old, 55.0±2.7kg, 164.9±5.2cm)] were evaluated for body composition with dual-energy X-ray absorptiometry and ⩒O2max, VT, RPC, and maximal aerobic speed (MAS) with a cardiorespiratory maximal treadmill test.

Results

The absolute ⩒O2max (p = 0.003, d = 1.05), body mass-adjusted ⩒O2max (p < 0.001, d = 1.2859), and MAS (p = 0.047, d = 0.6139) values differed significantly across evaluation periods. Lower limb LM-adjusted ⩒O2max (p = 0.083, d = -0.0418), %⩒O2max at VT (p = 0.541, d = -0.1746), speed at VT (p = 0.337, d = -0.2774), % ⩒O2max at RCP (p = 0.776, d = 0.0806), and speed at RCP (p = 0.436, d = 0.2234) showed no difference.

Conclusion

The sensitivities of ⩒O2max adjusted for body mass and ⩒O2max adjusted for LM to detect changes in physical training state differ. Furthermore, decreases in physical fitness level, as evaluated by ⩒O2max values, are not accompanied by changes in VT.

Comparative analysis of cardiorespiratory fitness, bio-motor abilities, and body composition indicators among sprint kayakers of different age groups and expertise levels

This study compared cardiorespiratory fitness, bio-motor abilities, and body composition indexes of sprint kayakers categorized into three different age groups and two expertise levels of international- and club-level athletes. Seventy-three male juniors (n = 14, age = 16.2 ± 0.8), under 23 [U23 (n = 15, age = 20.2 ± 1.6)], professionals (n = 16, age = 27.1 ± 4.8), club-level (n = 15, age = 26.9 ± 6.6), and international-level (n = 13, age = 27.3 ± 3.2) sprint kayakers were studied. Cardiorespiratory fitness (assessed using incremental exercise test), 500 and 1,000-m paddling performance (assessed using kayak ergometer), upper-body power (assessed using 30 s all-out Wingate test) and strength (assessed through one repetition tests for bench press, cable row, and prone bench pull exercises), as well as body composition indexes (measured using dual-energy X-ray absorptiometry) were evaluated on four occasions separated by 48 h recovery. U23 and, especially, professionals indicated significantly (p < 0.05) greater outcomes for the majority of the cardiorespiratory fitness parameters [maximal oxygen uptake (VO2max), velocity corresponding to VO2max, Oxygen pulse, maximal ventilation, and second ventilatory threshold] and 500 and 1,000-m performance. U23 and professional sprint kayakers significantly (p < 0.05) differed in the first ventilatory threshold and 500, and 1,000-m performance but not in VO2max or the second ventilatory threshold. Professionals also showed a lower fat mass, higher muscle mass, and higher strength (bench press, prone bench pull, and seated cable row) and power than U23 and junior kayakers. Strength and power indicators had significantly greater values in U23 athletes compared to juniors. International-level athletes also showed superior VO2max, velocity corresponding to VO2max, middle (500-m), and long-distance (1,000-m) time trial performance, strength and power, lower fat, and higher muscle mass than club-level sprint kayakers. Cardiorespiratory fitness (particularly ventilatory threshold), body composition, and muscle strength/power are the best differentiating factors for sprint kayakers of different ages and expertise levels. These findings could aid coaches in prescribing training programs focusing on improving determining factors in paddling performance, as well as in predicting performance and identifying talent.

Physiological Features of Olympic-Distance Amateur Triathletes, as Well as Their Associations with Performance in Women and Men: A Cross-Sectional Study

The purpose of this study was to verify the physiological and anthropometric determinants of triathlon performance in female and male athletes. This study included 40 triathletes (20 male and 20 female). Dual-energy X-ray absorptiometry (DEXA) was used to assess body composition, and an incremental cardiopulmonary test was used to assess physiological variables. A questionnaire about physical training habits was also completed by the athletes. Athletes competed in the Olympic-distance triathlon race. For the female group, the total race time can be predicted by V̇O₂max (β = -131, t = -6.61, p < 0.001), lean mass (β = -61.4, t = -2.66, p = 0.018), and triathlon experience (β = -886.1, t = -3.01, p = 0.009) (r² = 0.825, p < 0.05). For the male group, the total race time can be predicted by maximal aerobic speed (β = -294.1, t = -2.89, p = 0.010) and percentage of body fat (β = 53.6, t = 2.20, p = 0.042) (r² = 0.578, p < 0.05). The variables that can predict the performance of men are not the same as those that can predict the triathlon performance of women. These data can help athletes and coaches develop performance-enhancing strategies.

Modeling lactate threshold in young squad athletes: influence of sex, maximal oxygen uptake, and cost of running

PURPOSE

This study aimed to investigate: 1. The influence of sex and age on the accuracy of the classical model of endurance performance, including maximal oxygen uptake ([Formula: see text]), its fraction (LT2_%), and cost of running (C_R), for calculating running speed at lactate threshold 2 (vLT2) in young athletes. 2. The impact of different C_R determination methods on the accuracy of the model. 3. The contributions of [Formula: see text], LT2_%, and C_R to vLT2 in different sexes.

METHODS

45 male and 55 female young squad athletes from different sports (age: 15.4 ± 1.3 years; [Formula: see text]: 51.4 ± 6.8 [Formula: see text]) performed an incremental treadmill test to determine [Formula: see text], LT2_%, C_R, and vLT2. C_R was assessed at a fixed running speed (2.8 [Formula: see text]), at lactate threshold 1 (LT1), and at 80% of [Formula: see text], respectively.

RESULTS

Experimentally determined and modeled vLT2 were highly consistent independent of sex and age (ICC [Formula: see text] 0.959). The accuracy of vLT2 modeling was improved by reducing random variation using individualized C_R at 80% [Formula: see text] (± 4%) compared to C_R at LT1 (± 7%) and at a fixed speed (± 8%). 97% of the total variance of vLT2 was explained by [Formula: see text], LT2_%, and C_R. While [Formula: see text] and C_R showed the highest unique (96.5% and 31.9% of total [Formula: see text], respectively) and common (- 31.6%) contributions to the regression model, LT2_% made the smallest contribution (7.5%).

CONCLUSION

Our findings indicate: 1. High accuracy of the classical model of endurance performance in calculating vLT2 in young athletes independent of age and sex. 2. The importance of work rate selection in determining C_R to accurately predict vLT2. 3. The largest contribution of [Formula: see text] and C_R to vLT2, the latter being more important in female athletes than in males, and the least contribution of LT2_%.

Is Maximal Lactate Accumulation Rate Promising for Improving 5000-m Prediction in Running?

Endurance running performance can be predicted by maximal oxygen uptake (V̇O2max), the fractional utilisation of oxygen uptake (%V̇O2max) and running economy at lactate threshold (REOBLA). This study aims to assess maximal lactate accumulation rate (ċLamax) in terms of improving running performance prediction in trained athletes. Forty-four competitive female and male runners/triathletes performed an incremental step test, a 100-m sprint test and a ramp test to determine their metabolic profile. Stepwise linear regression was used to predict 5000-m time trial performance. Split times were recorded every 200-m to examine the ‘finishing kick’. Females had a slower t5k and a lower V̇O2max, ċLamax, ‘finishing kick’ and REOBLA. Augmenting Joyner’s model by means of ċLamax explained an additional 4.4% of variance in performance. When performing the same analysis exclusively for males, ċLamax was not included. ċLamax significantly correlated with %V̇O2max (r=-0.439, p=0.003) and the ‘finishing kick’ (r=0.389, p=0.010). ċLamax allows for significant (yet minor) improvements in 5000-m performance prediction in a mixed-sex group. This margin of improvement might differ in middle-distance events. Due to the relationship to the ‘finishing kick’, ċLamax might be related to individual pacing strategies, which should be assessed in future research.

Comparative analysis of endurance, strength and body composition indicators in professional, under-23 and junior cyclists

Purpose: To compare endurance, strength and body composition indicators between cyclists of three different competition age categories.

Methods: Fifty-one male road cyclists classified as either junior (n = 13, age 16.4 ± 0.5 years), under-23 [(U23), n = 24, 19.2 ± 1.3 years] or professional (n = 14, 26.1 ± 4.8 years) were studied. Endurance (assessed through a maximal incremental test and an 8-minute time-trial), strength/power (assessed through incremental loading tests for the squat, lunge and hip thrust exercises) and body composition (assessed through dual energy X-ray absorptiometry) were determined on three different testing sessions.

Results: U23 and, particularly professional, cyclists attained significantly (p < 0.05) higher values than juniors for most of the analyzed endurance indicators [time-trial performance, maximum oxygen uptake (VO_2max), peak power output (PPO), respiratory compensation point (RCP), and ventilatory threshold (VT)]. Significant differences (p < 0.05) between U23 and professionals were also found for time-trial performance, PPO and VT, but not for other markers such as VO_2max or RCP. Professional cyclists also showed significantly (p < 0.05) lower relative fat mass and higher muscle mass levels than U23 and, particularly, juniors. No consistent differences between age categories were found for muscle strength/power indicators.

Conclusion: Endurance (particularly time-trial performance, PPO and VT) and body composition (fat and muscle mass) appear as factors that best differentiate between cyclists of different age categories, whereas no consistent differences are found for muscle strength/power. These findings might help in performance prediction and/or talent identification and may aid in guiding coaches in the design of training programs focused on improving those variables that appear more determinant.

Prediction of Functional Threshold Power from Graded Exercise Test Data in Highly-Trained Individuals

The purpose of the current investigation was to derive an equation that could predict Functional Threshold Power (FTP) from Graded Exercise Test (GxT) data. The FTP test has been demonstrated to represent the highest cycling power output that can be maintained in a quasi-steady state for 60-min. Previous investigations to determine a comparable marker derived from a Graded Exercise test have had limited success to date. Consequently, the current study aimed to predict FTP from GxT data to provide an additional index of cycling performance. FTP has been reported to provide an insight not provided by a GxT and, in addition, does not require a formal exercise testing facility. The study design facilitated a deliberate and transparent sequence of statistical decisions, resolved in part from the perspective of exercise physiology. Seventy triathletes (male n=50, female n=20) completed cycling GxT and FTP tests in sequential order. Collected data (power output, blood lactate indices, VO₂peak, body mass) were analysed using stepwise regression to identify the key parameters for predicting FTP, and confirmed using a Leave One Out (LOO) cross-validation. As a consequence of wittingly including some likely transiently highly correlated parameters on the basis of a physiological argument, the model's function is limited to predicting FTP. This investigation concluded the model (FTP = -6.62 + 0.32 FBLC-4 + 0.42 BM + 0.46 Pmax) was the prediction model of choice.

Sex Differences in VO2max and the Impact on Endurance-Exercise Performance

It was not until 1984 that women were permitted to compete in the Olympic marathon. Today, more women than men participate in road racing in all distances except the marathon where participation is near equal. From the period of 1985 to 2004, the women’s marathon record improved at a rate three times greater than men’s. This has led many to question whether women are capable of surpassing men despite the fact that there remains a 10–12% performance gap in all distance events. The progressive developments in sports performance research and training, beginning with A.V. Hill’s establishment of the concept of VO_2max, have allowed endurance athletes to continue performance feats previously thought to be impossible. However, even today women are significantly underrepresented in sports performance research. By focusing more research on the female physiology and sex differences between men and women, we can better define how women differ from men in adapting to training and potentially use this information to improve endurance-exercise performance in women. The male advantage in endurance-exercise performance has commonly been attributed to their higher VO_2max, even when expressed as mL/kg/min. It is widely known that oxygen delivery is the primary limiting factor in elite athletes when it comes to improving VO_2max, but little research has explored the sex differences in oxygen delivery. Thus, the purpose of this review is to highlight what is known about the sex differences in the physiological factors contributing to VO_2max, more specifically oxygen delivery, and the impacts on performance.

Relationships Between Maximal Aerobic Speed, Lactate Threshold, and Double Poling Velocity at Lactate Threshold in Cross-Country Skiers

Purpose

To investigate the relationships between maximal aerobic speed (MAS), lactate threshold in per cent of peak oxygen uptake (LT) and velocity at LT (LT_v) in cross-country skiers. Secondly, we aimed to explore the fit of an equation previously used in cyclists and runners in a cohort of well-trained, competitive cross-country skiers for calculation of LT_v. Thirdly, we aimed to investigate if a new LT_v could still be calculated after a period of regular training only by providing a new MAS.

Methods

Ninety-five competitive cross-country skiers (65 males and 30 females) were tested for maximal oxygen uptake (VO_2max), peak oxygen uptake in double poling (DP-VO_2peak), oxygen cost of double poling (C_DP), LT, and LT_v. Thirty-five skiers volunteered to be tested 3 months later to evaluate potential changes in LT and LT_v.

Results

Velocity at LT was mainly determined by MAS (r = 0.88, p < 0.01). LT did not show a significant impact on LT_v. The product of MAS·LT precisely predicted LT_v at baseline (r = 0.99, SEE = 2.4%), and by only measuring MAS, a new LT_v could be accurately calculated (r = 0.92, SEE = 6.8%) 3 months later in a sub-set of the initial 95 skiers (n = 35).

Conclusion

The results suggest that LT has minor impact on LT_v in DP tested in a laboratory. LT_v seemed to be predominantly determined by MAS, and we suggest to put more focus on MAS and less on LT and LT_v in regular testing to evaluate aerobic performance capacity in DP.

Aerobic and Anaerobic Speed Predicts 800-m Running Performance in Young Recreational Runners

The main aim was to investigate the impact of maximal aerobic speed (MAS), maximal anaerobic speed (MANS), and time to exhaustion (TTE) at 130% MAS, on 800-m running time performance (800TT). A second aim was to investigate the impact of anaerobic speed reserve (ASR), i.e., the relative difference between MAS and MANS, on TTE. A total of 22 healthy students classified as recreational runners participated in a cross-sectional study. They were tested for maximal oxygen consumption (VO_2max), oxygen cost of running (C_R), time performance at 100 m (100TT), time performance at 800 m (800TT), and TTE. MAS was calculated as VO_2max × C_R^–1, and MANS was calculated as 100TT velocity. Both MAS and MANS correlated individually with 800TT (r = –0.74 and –0.67, respectively, p < 0.01), and the product of MAS and MANS correlated strongly (r = –0.82, p < 0.01) with 800TT. TTE did not correlate with 800TT. Both ASR and % MANS correlated strongly with TTE (r = 0.90 and –0.90, respectively, p < 0.01). These results showed that 800TT was first and foremost dependent on MAS and MANS, and with no impact from TTE. It seemed that TTE was merely a product of each runner’s individual ASR. We suggest a simplified model of testing and training for 800TT, namely, by focusing on VO_2max, C_R, and short sprint velocity, i.e., MAS and MANS.