The Dmax is highly related to performance in middle-aged females

Performance indicators and functional adaptive windows in competitive cyclists: effect of one-year strength and conditioning training programme

Changes and relationships between cycling performance indicators following a one-year strength and conditioning training have not been totally clarified. The aims of this study are to investigate (i) the effect of a combined one-year strength and conditioning training programme on performance indicators and the possible relationships between these indicators, and (ii) the existence of possible endurance-functional-adaptive windows (EFAWs) linked to changes in muscular strength and body composition markers. Functional and lactate threshold power (FTP and LTP), maximal strength (1RM) and body composition (body mass index [BMI], body cell mass [BCM] and phase angle [PA]) were measured at the beginning and the end of a one-year strength and conditioning training programme of thirty cyclists. Correlations, differences, and predictive analysis were performed among parameters. Significant differences were found between pre- and post-conditioning programme results for FTP, LTP, 1RM (p < 0.0001) and BCM (p = 0.038). When expressed as power output (W), FTP and LTP were significantly correlated with 1RM (r = 0.36, p = 0.005 and r = 0.37, p = 0.004, respectively), body mass (r = 0.30 and p = 0.02), BCM (r = 0.68, p < 0.001) and PA (r = 0.42 and 0.39, respectively and p < 0.001). When expressed as W·kg-¹, these power thresholds were strongly correlated with body mass (r = -0.56 and -0.61, respectively) and BMI (r = -0.57 and -0.61 respectively) with p < 0.001. Predictive polynomial regressions revealed possible endurance and strength adaptation zones. The present findings indicated beneficial impacts of one-year strength and conditioning training on cycling performance indicators, confirmed the correlation between performance indicators, and suggested the existence of different EFAWs. Strategies aiming to improve performance should consider cyclist characteristics and performance goals to achieve EFAWs and thereby enhance cycling performance.

Relationship Between Critical Power and Different Lactate Threshold Markers in Recreational Cyclists

Purpose: To analyze the relationship between critical power (CP) and different lactate threshold (LT2) markers in cyclists.

Methods: Seventeen male recreational cyclists [33 ± 5 years, peak power output (PO) = 4.5 ± 0.7 W/kg] were included in the study. The PO associated with four different fixed (onset of blood lactate accumulation) and individualized (Dmax_exp, Dmax_pol, and LT_Δ1) LT2 markers was determined during a maximal incremental cycling test, and CP was calculated from three trials of 1-, 5-, and 20-min duration. The relationship and agreement between each LT2 marker and CP were then analyzed.

Results: Strong correlations (r = 0.81–0.98 for all markers) and trivial-to-small non-significant differences (Hedges’ g = 0.01–0.17, bias = 1–9 W, and p > 0.05) were found between all LT2 markers and CP with the exception of Dmax_exp, which showed the strongest correlation but was slightly higher than the CP (Hedges’ g = 0.43, bias = 20 W, and p < 0.001). Wide limits of agreement (LoA) were, however, found for all LT2 markers compared with CP (from ±22 W for Dmax_exp to ±52 W for Dmax_pol), and unclear to most likely practically meaningful differences (PO differences between markers >1%, albeit <5%) were found between markers attending to magnitude-based inferences.

Conclusion: LT2 markers show a strong association and overall trivial-to-small differences with CP. Nevertheless, given the wide LoA and the likelihood of potentially meaningful differences between these endurance-related markers, caution should be employed when using them interchangeably.

Predicting Lactate Threshold With Rate of Perceived Exertion in Young Competitive Male Swimmers

The purpose of this study was to verify the effectiveness of the rate of perceived exertion threshold (RPET) for predicting young competitive swimmers' lactate threshold (LT) during incremental testing. We enrolled 13 male athletes (M age = 16, SD = 0.6 years) in an incremental test protocol consisting of eight repetitions of a 100-meter crawl with 2-minute intervals between each repetition. We collected data for blood lactate concentration ([La]) and Borg scale rate of perceived exertion (RPE) at the end of each repetition. The results obtained were: M RPET = 4.98, SD = 1.12 arbitrary units (A.U.) and M lactate threshold = 4.24, SD = 1.12 mmol.L^-1, with [La] and RPE identified by the maximal deviation (Dmax) method without a significant difference (p > 0.05) and large correlations between DmaxLa and DmaxRPE at variables for time (r = 0.64), velocity (r = 0.67) and percentage of personal best time (PB) (r = 0.60). These results suggest that RPET is a good predictor of LT in young competitive swimmers.

Inter-Individual Different Responses to Continuous and Interval Training in Recreational Middle-Aged Women Runners

A crucial subject in sports is identifying the inter-individual variation in response to training, which would allow creating individualized pre-training schedules, improving runner’s performance. We aimed to analyze heterogeneity in individual responses to two half-marathon training programs differing in running volume and intensity in middle-aged recreational women. 20 women (40 ± 7 years, 61 ± 7 kg, 167 ± 6 cm, and VO₂max = 48 ± 6 mL⋅kg^–1⋅min^–1) underwent either moderate-intensity continuous (MICT) or high-intensity interval (HIIT) 12-week training. They were evaluated before and after training with maximal incremental tests in the laboratory (VO₂max) and in the field (time to exhaustion, TTE; short interval series and long run). All the women participated in the same half-marathon and their finishing times were compared with their previous times. Although the improvements in the mean finishing times were not significant, MICT elicited a greater reduction (3 min 50 s, P = 0.298), with more women (70%) improving on their previous times, than HIIT (reduction of 2 min 34 s, P = 0.197, 50% responders). Laboratory tests showed more differences in the HIIT group (P = 0.008), while both groups presented homogeneous significant (P < 0.05) increases in TTE. Both in the short interval series and in the long run, HIIT induced better individual improvements, with a greater percentage of responders compared to MICT (100% vs 50% in the short series and 78% vs 38% in the long run). In conclusion, variability in inter-individual responses was observed after both MICT and HIIT, with some participants showing improvements (responders) while others did not (non-responders) in different performance parameters, reinforcing the idea that individualized training prescription is needed to optimize performance.

A field tool for the aerobic power evaluation of middle-aged female recreational runners

This study used time to exhaustion (TTE) to predict V̇O_2max in female recreational master runners. Forty-two middle-aged women (mean = 40.5 ± 5.9 years) who had trained for recreational running performed two Université de Montréal Track Tests in the facilities of the University of Barcelona (Spain). The first was performed on a treadmill (t), the second, on an athletics track (field: f). After measuring TTE and V̇O_2max on the treadmill, a first-order equation was obtained to estimate fV̇O_2max from fTTE. No significant difference was observed between the estimated fV̇O_2max (46.5 ± 2.9 mL·kg^-1·min^-1) and the measured tV̇O_2max (46.2 ± 5.3), with a mean value of the absolute differences of less than 8% of the tV̇O_2max average. High agreement between the two V̇O_2max values was also evident, as shown by the low bias of the differences and the Bland-Altman plot. The equation obtained is of interest to evaluate performance in middle-aged female recreational runners. It will allow coaches and runners to set running paces for training and could be used in training routines to determine improvements after a training program. Moreover, these tools could be used in the field to assess the physical fitness of middle-aged women, in efforts to preserve their health and physical function.

Endurance Running Training Individually Guided by HRV in Untrained Women

da Silva, DF, Ferraro, ZM, Adamo, KB, and Machado, FA. Endurance running training individually guided by HRV in untrained women. J Strength Cond Res 33(3): 736-746, 2019-The aim of this study was to analyze the effects of heart rate variability (HRV)-guided training compared with a standardized prescription on (a) time to complete 5-km running performance (t5km), (b) peak treadmill running speed (Vpeak) and its time limit (tlim at Vpeak), and (c) autonomic cardiac modulation (i.e., parasympathetic activity and recovery) in untrained women. Additionally, we correlated changes in t5km with changes in Vpeak, tlim at Vpeak and autonomic cardiac modulation. Thirty-six untrained women were divided into a HRV-guided training group (HRVG) and a control group (CG). The CG followed a predefined program, alternating moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT). The determination of MICT or HIIT was based on the pretraining HRV for HRVG. MICT was performed if HRV was <mean - 1 SD of previous measures. Otherwise, HIIT was prescribed. The t5km, Vpeak, tlim at Vpeak, parasympathetic activity (i.e., rMSSD) and parasympathetic reactivation (i.e., HRR) were measured before and after the training period. The t5km decreased to a greater magnitude in the HRVG (-17.5 ± 5.6% vs. -14 ± 4.7%; Effect Size (ES) between-group difference = moderate). rMSSD and tlim at Vpeak only improved in HRVG (+23.3 ± 27.8% and +23.6 ± 31.9%, respectively). The HRVG experienced greater improvements in Vpeak and HRR (Vpeak: 10 ± 7.3% vs. 8.2 ± 4.7%; HRR: 19.1 ± 28.1% vs. 12.6 ± 12.9%; ES between-group difference = small). Although HRVG performed less MICT than CG, the volume of MICT was negatively related to changes in t5km. Vpeak changes were highly correlated with t5km changes. The greater improvements in HRVG for t5km and autonomic modulation reinforce the potential application of this tool.

Modifications of the Dmax method in comparison to the maximal lactate steady state in young male athletes

OBJECTIVE

To investigate the influence of different approaches for first-rise determination on the accuracy of Dmax as an estimate of the maximal lactate steady state (MLSS).

METHODS

Seventeen male cyclists and 18 male runners with different levels of endurance performance completed graded exercise tests either on a cycle ergometer or treadmill to determine Dmax, calculated by the final data point and five modifications of the first rise in blood lactate concentration. Two or more constant load tests over 30 min were performed to determine MLSS. Differences between the modifications of the first rise in blood lactate concentration as well as the corresponding Dmax variants and MLSS were tested, using one-way repeated measure ANOVA with Bonferroni post-hoc tests, and illustrated, using the Bland-Altman method. The absolute agreement was observed, using intra-class correlation coefficients, based on a single measure, absolute agreement, 2-way mixed effects model.

RESULTS

The peak power output/running velocity of the groups averaged 275 ± 43 W and 4.3 ± 0.4 m · s^-1, respectively. The mean power output/running velocity at MLSS was 229 ± 38 W and 3.77 ± 0.38 m · s^-1. For both running and cycling the original Dmax described by Cheng et al. was significantly lower than MLSS (p < 0.01). All modifications showed good agreement with MLSS (ICC ≥0.75). According to the Bland-Altman method the mean differences of the modifications compared to MLSS in cycling ranged from -7 (43) to 2 (41) W. In running the mean differences ranged from -0.12 (0.34) to -0.08 (0.35) m· s^-1.

CONCLUSION

We suggest using the first rise in blood lactate concentration for calculating Dmax instead of the first data point of a lactate curve as originally described. The approach of first rise determination has no substantial influence on the accuracy of Dmax compared to MLSS in cycling and running.

Is the Functional Threshold Power a Valid Surrogate of the Lactate Threshold?

PURPOSE

To analyze the relationship between functional threshold power (FTP) and the lactate threshold (LT).

METHODS

A total of 20 male cyclists performed an incremental test in which LT was determined. At least 48 h later, they performed a 20-min time trial, and 95% of the mean power output was defined as FTP. Participants were divided into recreational (peak power output < 4.5 W·kg-1; n = 11) or trained cyclists (peak power output > 4.5 W·kg-1; n = 9) according to their fitness status.

RESULTS

The FTP (240 [35] W) was overall not significantly different (effect size = 0.20; limits of agreement = -2.4% [11.5%]) from the LT (246 [24] W), and both markers were strongly correlated (r = .95; P < .0001). Accounting for the participants' fitness status, no significant differences were found between FTP and LT (effect size = 0.22; limits of agreement =2.1% [7.8%]) in trained cyclists, but FTP was significantly lower than the LT (P = .0004, effect size = 0.81; limits of agreement =-6.5% [8.3%]) in recreational cyclists. A significant relationship was found between relative peak power output and the bias between FTP and the LT markers (r = .77; P < .0001).

CONCLUSIONS

FTP is a valid field test-based marker for the assessment of endurance fitness. However, caution should be taken when using FTP interchangeably with LT, as the bias between markers seems to depend on the athlete's fitness status. Whereas FTP provides a good estimate of LT in trained cyclists, in recreational cyclists, it may underestimate LT.

Using lactate threshold to predict 5-km treadmill running performance in veteran athletes

Measuring lactate threshold to predict endurance performance is difficult among veteran athletes, due to age-related decreases in net lactate concentration. The objective of this study was to determine whether lactate threshold, as assessed using the maximal deviation method (D_max), which is not dependent on net values of lactate, could be used as a more valid measure of 5-km treadmill running performance than other methods of determining lactate threshold. Veteran runners (18 male and 18 female, aged 47.3±6.7 years) performed an incremental exercise test to establish mean treadmill velocity at lactate threshold using D_max, a log-log method, a visual method, and a 4-mmol·L^-1 method, and, on a separate occasion, completed a 5-km time trial. Mean treadmill velocity at D_max was 12.2±1.8 km·h^-1, not being significantly different to mean treadmill velocity (12.1±1.8 km·h^-1) attained during the 5-km time trial (p>0.05); velocities were also significantly correlated (r=0.92, p<0.001), and limits of agreement narrow (-1.61 to 1.35 km·h^-1). Correlations were weaker and limits of agreement wider for the other methods of lactate threshold determination. Using a two-way, mixed-methods ANOVA, there was no significant effect of sex when using the different methods of determining T_lac (F_4,136=3.70, p=0.15). Mean treadmill velocity, when using D_max for determining lactate threshold, can be used to predict 5-km running performance among male and female veteran athletes.

Lack of concordance amongst measurements of individual anaerobic threshold and maximal lactate steady state on a cycle ergometer

INTRODUCTION

The calculation of exertion intensity, in which a change is produced in the metabolic processes which provide the energy to maintain physical work, has been defined as the anaerobic threshold (AT). The direct calculation of maximal lactate steady state (MLSS) would require exertion intensities over a long period of time and with sufficient rest periods which would prove significantly difficult for daily practice. Many protocols have been used for the indirect calculation of MLSS.

OBJECTIVES

The aim of this study is to determine if the results of measurements with 12 different AT calculation methods and calculation software [Keul, Simon, Stegmann, Bunc, Dickhuth (TKM and WLa), Dmax, Freiburg, Geiger-Hille, Log-Log, Lactate Minimum] can be used interchangeably, including the method of the fixed threshold of Mader/OBLA's 4 mmol/l and then to compare them with the direct measurement of MLSS.

METHODS

There were two parts to this research. Phase 1: results from 162 exertion tests chosen at random from the 1560 tests. Phase 2: sixteen athletes (n = 16) carried out different tests on five consecutive days.

RESULTS

There was very high concordance among all the methods [intraclass correlation coefficient (ICC) > 0.90], except Log-Log in relation to the Stegamnn, Dmax, Dickhuth-WLa and Geiger-Hille. The Dickhuth-TKM showed a high tendency towards concordance, with Dmax (2.2 W) and Dickhuth-WLa (0.1 W). The Dickhuth-TKM method presented a high tendency to concordance with Dickhuth-WLa (0.5 W), Freiburg (7.4 W), MLSS (2.0 W), Bunc (8.9 W), Dmax (0.1 W). The calculation of MLSS power showed a high tendency to concordance, with Dickhuth-TKM (2 W), Dmax (2.1 W), Dickhuth-WLa (1.5 W).

CONCLUSION

The fixed threshold of 4 mmol/l or OBLA produces slightly different and higher results than those obtained with all the methods analyzed, including MLSS, meaning an overestimation of power in the individual anaerobic threshold. The Dickhuth-TKM, Dmax and Dickhuth-WLa methods defined a high concordance on a cycle ergometer. Dickhuth-TKM, Dmax, Dickhuth-WLa described a high concordance with the power calculated to know the MLSS.

The influence of the regression model and final speed criteria on the reliability of lactate threshold determined by the Dmax method in endurance-trained runners

Few studies verified the reliability of the lactate threshold determined by Dmax method (LT_Dmax) in runners and it remains unclear the effect of the regression model and the final speed on the reliability of LT_Dmax. This study aimed to examine the test-retest reliability of the speed at LT_Dmax in runners, considering the effects of the regression models (exponential-plus-constant vs third-order polynomial) and final speed criteria (complete vs proportional). Seventeen male, recreational runners performed 2 identical incremental exercise tests, with increments of 1 km·h^-1 each for 3 min on treadmill to determine peak treadmill speed (V_peak) and lactate threshold. Earlobe capillary blood samples were collected during rest between the stages. The V_peak was defined as the speed of the last complete stage (complete final speed criterion) and as the speed of the last complete stage added to the fraction of the incomplete stage (proportional final speed criterion). Lactate threshold was determined from exponential-plus-constant and from third-order polynomial regression models with both complete and proportional final speed criteria and from fixed blood lactate level of 3.5 mmol·L^-1 (LT_3.5mM). The LT_Dmax obtained from the exponential-plus-constant regression model presented higher reliability (coefficient of variation (CV) ≤ 3.7%) than the LT_Dmax calculated from the third-order polynomial regression model (CV ≤ 5.8%) and LT_3.5mM (CV = 5.4%). The proportional final speed criterion is more appropriate when using the exponential-plus-constant regression model, but less appropriate when using the third-order polynomial regression model. In conclusion, exponential-plus-constant using the proportional final speed criterion is preferred over LT_3.5mM and over third-order polynomial regression model to determine a reliable LT_Dmax.

Post-analysis methods for lactate threshold depend on training intensity and aerobic capacity in runners. An experimental laboratory study

CONTEXT AND OBJECTIVE

This study aimed to evaluate different mathematical post-analysis methods of determining lactate threshold in highly and lowly trained endurance runners.

DESIGN AND SETTING

Experimental laboratory study, in a tertiary-level public university hospital.

METHOD

Twenty-seven male endurance runners were divided into two training load groups: lowly trained (frequency < 4 times per week, < 6 consecutive months, training velocity ≥ 5.0 min/km) and highly trained (frequency ≥ 4 times per week, ≥ 6 consecutive months, training velocity < 5.0 min/km). The subjects performed an incremental treadmill protocol, with 1 km/h increases at each subsequent 4-minute stage. -Fingerprint -blood-lactate analysis was performed at the end of each stage. The lactate threshold (i.e. the running velocity at which blood lactate levels began to exponentially increase) was measured using three different methods: increase in blood lactate of 1 mmol/l at stages (DT1), absolute 4 mmol/l blood lactate concentration (4 mmol), and the semi-log method (semi-log). ANOVA was used to compare different lactate threshold methods and training groups.

RESULTS

Highly trained athletes showed significantly greater lactate thresholds than lowly trained runners, regardless of the calculation method used. When all the subject data were combined, DT1 and semi-log were not different, while 4 mmol was significantly lower than the other two methods. These same trends were observed when comparing lactate threshold methods in the lowly trained group. However, 4 mmol was only significantly lower than DT1 in the highly trained group.

CONCLUSION

The 4 mmol protocol did not show lactate threshold measurements comparable with DT1 and semi-log protocols among lowly trained athletes.

Reliability of peak running speeds obtained from different incremental treadmill protocols

This study compared the values and reliability of peak running speeds from incremental treadmill protocols with different speed increments. Thirty-one men, recreational, endurance-trained runners performed, in an alternate order, three continuous tests with different speed increments (0.5, 1 and 2 km · h(-1)). The tests were repeated using the same order. Peak speed was identified as (1) the greatest speed that could be maintained for a complete minute (Vpeak-60s), (2) the speed of the last complete stage (Vpeak-C) and (3) the speed of the last complete stage added to the product of the speed increment and the completed fraction of the incomplete stage (Vpeak-P). The Vpeak-P was the most reliable, independent of the incremental test protocol (1.5% ≤ CV ≤ 1.8%), and differently from Vpeak-C (1.8% ≤ CV ≤ 2.6%) and Vpeak-60s (1.6% ≤ CV ≤ 3.8%), the Vpeak-P was only slightly influenced by the incremental test protocol. The results suggest that Vpeak-P should be used to assess aerobic capability and monitor training effects and that other determinations of peak speed should be avoided.

Influence of regression model and initial intensity of an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and running performance

This study investigated the influence of the regression model and initial intensity during an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and performance in elite-standard runners. Twenty-three well-trained runners completed a discontinuous incremental running test on a treadmill. Speed started at 9 km · h(-1) and increased by 1.5 km · h(-1) every 4 min until exhaustion, with a minute of recovery for blood collection. Lactate-speed data were fitted by exponential and polynomial models. The lactate threshold was determined for both models, using all the co-ordinates, excluding the first and excluding the first and second points. The exponential lactate threshold was greater than the polynomial equivalent in any co-ordinate condition (P < 0.001). For both models, the lactate threshold was lower when all co-ordinates were used than when the first and the first and second points were excluded (P < 0.001). 10-km race pace was correlated with both the exponential and polynomial lactate thresholds for all the co-ordinate conditions (r ≥ 0.75, P < 0.001 and r ≥ 0.56, P < 0.05, respectively). The results suggest that the exponential lactate threshold should be used instead of the polynomial equivalent since it is more strongly associated with performance and is independent of the initial intensity of the test.

Incremental test design, peak 'aerobic' running speed and endurance performance in runners

OBJECTIVES

Peak running speed obtained during an incremental treadmill test (Vpeak) is a good predictor of endurance run performance. However, the best-designed protocol for Vpeak determination and the best Vpeak definition remain unknown. Therefore, this study examined the influence of stage duration and Vpeak definition on the relationship between Vpeak and endurance run performance.

DESIGN

Relationship.

METHODS

Twenty-seven male, recreational, endurance-trained runners (10-km running pace: 10-17 k mh(-1)) performed, in counterbalanced order, three continuous incremental treadmill tests of different stage durations (1-, 2-, or 3-min) to determine Vpeak, and two 5-km and two 10-km time trials on a 400-m track to obtain their 5-km and 10-km run performances. Vpeak was defined as either (a) the highest speed that could be maintained for a complete minute (Vpeak-60 s), (b) the speed of the last complete stage (Vpeak-C), or (c) the speed of the last complete stage added to the multiplication of the speed increment by the completed fraction of the incomplete stage (Vpeak-P).

RESULTS

The Vpeak determined during the 3-min stage duration protocol was the most highly correlated with both the 5-km (r=0.95) and 10-km (r=0.92) running performances and these relationships were minimally influenced by the Vpeak definition. However, independent of the stage duration, the Vpeak-P provided the highest correlation with both running performances.

CONCLUSIONS

Incremental treadmill tests comprising 3-min stage duration is preferred to 1-min and 2-min stage duration protocols in order to determine Vpeak to accurately predict 5-km and 10-km running performances. Further, Vpeak-P should be used as standard for the determination of Vpeak.

Influence of regression model and incremental test protocol on the relationship between lactate threshold using the maximal-deviation method and performance in female runners

This study examined the influence of the regression model and initial intensity of an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and the endurance performance. Sixteen non-competitive, recreational female runners performed a discontinuous incremental treadmill test. The initial speed was set at 7 km · h⁻¹, and increased every 3 min by 1 km · h⁻¹ with a 30-s rest between the stages used for earlobe capillary blood sample collection. Lactate-speed data were fitted by an exponential-plus-constant and a third-order polynomial equation. The lactate threshold was determined for both regression equations, using all the coordinates, excluding the first and excluding the first and second initial points. Mean speed of a 10-km road race was the performance index (3.04 ± 0.22 m · s⁻¹). The exponentially-derived lactate threshold had a higher correlation (0.98 ≤ r ≤ 0.99) and smaller standard error of estimate (SEE) (0.04 ≤ SEE ≤ 0.05 m · s⁻¹) with performance than the polynomially-derived equivalent (0.83 ≤ r ≤ 0.89; 0.10 ≤ SEE ≤ 0.13 m · s⁻¹). The exponential lactate threshold was greater than the polynomial equivalent (P < 0.05). The results suggest that the exponential lactate threshold is a valid performance index that is independent of the initial intensity of the incremental test and better than the polynomial equivalent.