Preprint
Article

Strength Training Versus Core Exercises for the Optimization of Road Cycling Performance

Altmetrics

Downloads

216

Views

147

Comments

0

Submitted:

28 December 2023

Posted:

28 December 2023

You are already at the latest version

Alerts
Abstract
(1) Background: Conventional strength training and core exercises are commonly prescribed to improve cycling performance. Although previous studies have explored the utility of strength training in various cycling populations, this intervention has never been compared to core exercises; (2) Methods: 36 trained road cyclists were divided in 3 groups of 12 participants that performed either no strength training, conventional strength training or core exercises, in all cases together with their regular cycling training during a 12-week period. Peak power outputs across different durations (5 seconds, 60 seconds, 5 minutes, and 20 minutes) were recorded before and after the intervention; (3) Results: Conventional strength training is superior to core training and no strength training for all measured durations. At the same time, core training results in improved 5 second power output when compared to no strength training, while all the other measures are comparable among groups; (4) Conclusions: Conventional strength training is superior to core exercises and no strength training in trained road cyclists, and accordingly, it is recommended that this population incorporates strength training during their regular weekly workouts.
Keywords: 
Subject: Medicine and Pharmacology  -   Anatomy and Physiology

1. Introduction

Road cycling is an endurance sport characterized by large training volumes and prolonged periods of moderate force production [1,2]. However, during decisive competition phases, short high intensity efforts are necessary in order to perform [3]. This complex and variable requirements in force production may be addressed on the bike but, as previous evidence pointed out, the addition of conventional strength training may result in even better results. Strength training may delay activation of less efficient type II fibers, improve neuromuscular efficiency, convert fast-twitch type IIX fibers into more fatigue-resistant type IIA fibers and improve muscle-tendinous stiffness [4]. On the other hand, core training may have the potential to increase joint range and muscle extensibility; improve joint stability, enhance muscle performance, and optimize movement function [5].
The incorporation of strength training during the preparatory period of trained road cyclists has received increasing attention since the beginning of the century. Several authors have reported improvements in various markers of performance after the addition of conventional strength training increases in type IIA fiber proportions and decreases in type IIX; improvements in pedaling efficacy and cycling economy after fatigue; increases in peak power output, time trial performance and power output at fixed blood lactate concentrations are some of the highlighted changes [6,7,8]. However, some studies have also reported no effect of strength training when added to cycling training [9]. Although the consensus is towards a positive effect of these types of interventions, some degree of discrepancy still exists in the scientific and coaching field regarding the overall effect of strength training on cycling performance.
As road cycling is characterized by large training volumes performed under fixed postures in which the stabilizers and compensatory muscles of the trunk are being activated, the selective training of these muscle groups has received increased attention in the last years [2,10]. The practical coaching field has implemented training sessions with several exercises targeting the core muscles (transverse abdominis, multifidus, internal and external obliques, erector spinae, diaphragm, pelvic floor muscles, and the rectus abdominis [6]. Despite the general acceptance and broad implementation of these sessions, the scientific evidence behind these interventions is lacking as of today.
Previous research that investigated the effect of strength training interventions on cycling performance evaluated laboratory parameters such as lactate profiles, VO2 kinetics, muscle fiber composition and torque profiles [4]. Although these values are useful for the prediction of cycling performance, during the last years the attention has focused towards the power profile, which allows to accurately predict performance after the analysis of power outputs registered with a mobile power meter [3]. This method allows an accurate, flexible, and inexpensive longitudinal tracking of performance without resorting to the laboratory. Previous research has shown that 5-second, 60-second, 5-minute and 20-minute intervals can be used to track neuromuscular and glycolytic changes, maximal oxygen consumption and maximal metabolic stable state, respectively [11,12,13].
Given the relative uncertainty regarding the true effect of conventional strength training on cycling performance, the lack of previous studies regarding the utility of core training and the easy implementation of power profiling as a valid tool to monitor changes in performance experienced after strength training, the objective of the current study was to compare the power profile of trained road cyclists after 12 weeks of a) conventional strength training; b) core training and c) no strength training during the preparatory phase of the annual training plan.

2. Materials and Methods

The present investigation was designed as an exploratory training intervention study. The test protocol (described in detail below) was conducted at baseline (pre) and after 12 weeks of intervention (post). The study period (November to January) spanned from the off-season (noncompetitive season) and included the beginning of the preparation phase leading up to the competitive season.

2.1. Participants

Thirty-six cyclists volunteered to participate in this study (age = 28.8 (4.2) [21,37] years, height = 179.3 (5.1) [169,190] cm, body mass = 69.1 (4.5) [60,80] kg). After initial measurements, participants were randomly allocated into three groups of n = 12. All participants trained at the same performance center and were assessed in the same facilities, instruments and by the same researcher. The inclusion criteria were: (a) current owner of a cycling license (World Tour, Elite/ U23, Masters, or recreational); (b) absence of surgical procedures and injuries in the 6 months prior to the study; and (c) absence of drug use in the 6 months prior to the study. After being informed of the benefits and potential risks of the investigation, each subject completed a health-screening questionnaire and provided written informed consent before participation in the study [14]. The study followed the ethical guidelines of the 2013 Declaration of Helsinki and received approval from the Research Ethics Committee of the autonomous region of Aragon, Spain (PI23/131). Grouped participant characteristics can be found in Table 1.

2.2. Procedures

Subjects performed the anthropometric evaluation and cycling test on two separate occasions, before and after the 12 weeks of intervention. All evaluations were performed during the same morning hours (between 10:00 AM and 12:00 AM) to control for diurnal hormonal variations. Data were collected under similar environmental conditions (17–18° C, 45–55% relative humidity). All subjects performed both tests on their own bikes set up on a Tacx Neo 2T Smart bike trainer (Tacx International, Rijksstraatweg, the Netherlands). Power output was measured with the Favero Assioma pedals [11]. Maximal oxygen consumption was estimated through a formula based on relative power output obtained during the 5-minute interval [15].
In order to obtain the power profile of each participant, subjects performed the testing protocol suggested by Allen & Coggan, which includes 5-second, 60-second, 5-minute, and 20-minute maximal efforts [2,17,18,19]. Participants could view their progress on a computer monitor and were provided with information regarding time to completion and gear choice. All other information was blinded, no verbal encouragement was provided, and water was allowed ad libitum. FTP was determined as 95% of the mean power output of the 20-minute effort. Maximal power outputs for each selected duration were registered in relative values (w/kg) considering the weight obtained during the anthropometric evaluation.

2.3. Anthropometric Evaluation

The body mass and fat mas of all cyclists was assessed through the electrical impedance method (BC-602; Tanita Co., Tokyo, Japan) in the morning hours. Height was measured with a SECA 214 stadiometer (Seca; Hamburg, Germany), which is graduated up to 1 mm.

2.4. Endurance Training

All participants performed the same training sessions during the 12 weeks of the intervention period. Training was prescribed based on six power zones relative to the functional threshold power, which was calculated by subtracting 5% to the maximal 20-minute power output obtained in the baseline testing [2]. The power zones were set up as follows: <55% Zone 1; 56-75% Zone 2; 76-90% Zone 3; 91-105% Zone 4; 106-120% Zone 5 and >121% Zone 6 [2]. Participants performed 4 weekly sessions riding in Zone 2 (2h on Tuesday, 2h on Thursday, 4h on Saturday and 4h on Sunday). Compliance was verified by analyzing files obtained from the bike computer of the participant. 34 out of 36 participants (94%) achieved a compliance of >90% when Training Stress Score of the full intervention period was assessed.

2.5. Strength Training

The strength training exercises were based on previous research (half squat, leg press with one leg at a time, one-legged hip flexion, and ankle plantar flexion) and were performed twice weekly (Monday and Wednesday) [16]. 3-minute rests were allowed between sets. All cyclists were supervised by an investigator at all workouts during the first 2 weeks and thereafter at least once every second week throughout the intervention period. During the 12 weeks of the intervention period, cyclists trained with 6 repetition maximum (RM) sets. The cyclists were encouraged to increase their RM loads after 4 and 8 weeks of the intervention period and they were allowed assistance on the last repetition. The number of sets in each exercise was always three. Over the entire training period, one session was not performed due to illness.

2.6. Core Training

The core exercises (glute bridge, abdominal plank and prone back extension) were performed as recommended in a previous study designed with cyclists [20]. The glute bridge and prone back extension consisted of a 2-second concentric phase, 2-second isometric phase and 4-second eccentric phase. Both exercises incorporated 10 repetitions for each set. The abdominal plank was maintained for 30 seconds. 8 sets of each exercise were performed with a 60-second rest in-between. These exercises were performed twice weekly (Monday and Wednesday). All cyclists were supervised by an investigator at all workouts during the first 2 weeks and thereafter at least once every second week throughout the intervention period. Over the entire training period, two sessions were not performed due to illness.

2.7. Statistical Analyses

Data are described as mean (standard deviation) [range]. Baseline differences between the three groups were assessed by univariate analyses of variance (ANOVA). To compare the effectiveness of each intervention, a one-way between-groups analysis of covariance (ANCOVA) was conducted. The base analysis model was built with group allocation as the independent variable and the absolute change (Δ = post-pre) as the dependent variable, with the corresponding baseline scores as covariates. Prior to the analysis, the assumptions of linearity, homogeneity of regression slopes, normality of residuals, homogeneity of variances and absence of outlier values were inspected and, accordingly, the following decisions were made: 5-min RPO violated slope homogeneity and was heteroscedastic and, consequently, its modeling included an interaction term with group-by-baseline data and the White-Huber heteroscedasticity correction; and 60-sec RPO had baseline differences and, consequently, its modeling included an interaction term with group-by-baseline data. Post-hoc pairwise comparisons were based on model estimated marginal means and reported as estimated means and/or mean changes (Δ) and their 95% confidence interval (CI). Effect sizes for ANCOVA terms were reported as partial eta 2 (η2P), and for pairwise comparisons as Cohen’s d, in both cases with their respective 95% CI. Analyses were performed using R version 4.2.2 (R Core Team) and statistical significance was assumed when p < 0.05.

3. Results

3.1. Anthropometric Data

At baseline, all groups had similar Body Mass (F(2, 33) = 0.06, p = 0.94), Fat Mass (F(2, 33) = 3.07, p = 0.06), Body Mass Index (F(2, 33) = 1.21, p = 0.31), and VO2max (F(2, 33) = 1.11, p = 0.34). Changes after training were also comparable among groups in Body Mass (F(2, 32) = 0.12, p = 0.89), Fat Mass (F(2, 30) = 0.94, p = 0.402), and Body Mass Index (F(2, 32) = 0.026, p = 0.97). By contrast, VO2max improvements were different among groups (F(2, 32) = 6.84, p = 0.003; η2P = 0.30, 95% CI [0.08, 1.00]), being higher in the Cycling & Strength group (Δ = 2.14 ml/min/kg, Δ 95% CI [1.4, 2.47] ml/min/kg) compared with the Cycling-only (Δ = 0.35 ml/min/kg, Δ 95% CI [-0.27, 1.21] ml/min/kg, t(32) = 3.22, p = 0.008, d = 1.14, d 95% CI [0.38, 1.88]) and the Cycling & Core group (Δ = 0.36 ml/min/kg, Δ 95% CI [-0.2, 1.25] ml/min/kg, t(32) = 3.2, p = 0.008, d = 1.13, d 95% CI [0.38, 1.87]).

3.2. Main Relative Power Output Differences

Individual relative power output (RPO) data has been plotted in Figure 1) There were no group differences in basal 5-sec RPO (F(2, 33) = 1.39, p = 0.263), 5-min RPO (F(2, 33) = 1.11, p = 0.34), and 20-min RPO (F(2, 33) = 0.27, p = 0.763), but a statistically significant and large main effect of group in 60-sec RPO (F(2, 33) = 4.16, p = 0.024; η2P = 0.20, 95% CI [0.02, 1.00]). Adjusted by basal data, RPO improvements after the intervention were different among groups in all tests: 5-sec RPO (F(2, 32) = 14.09, p < .001; η2P = 0.47, 95% CI [0.24, 1.00]), 60-sec RPO (F(2, 30) = 11.96, p < .001; η2P = 0.44, 95% CI [0.20, 1.00]), 5-min RPO (F(2, 32) = 5.77, p = 0.008, η2P = 0.28, 95% CI [0.06, 1.00]), and 20-min RPO (F(2, 32) = 11.72, p < .001; η2P = 0.42, 95% CI [0.19, 1.00]).

3.3. Post-Hoc Group Contrasts by Variable

Adjusted by baseline, the mean 5-sec RPO improvements were higher in Cycling & Strength group (Δ = 1.25 W/kg, Δ 95% CI [0.86, 1.64] W/kg) compared to the Cycling-only (Δ = -0.17 W/kg, Δ 95% CI [-0.55, 0.21] W/kg, t(32) = 5.3, p < 0.001, d = 1.88, d 95% CI [1.04, 2.7]) and Cycling & Core (Δ = 0.47 W/kg, Δ 95% CI [0.09, 0.85] W/kg, t(32) = 2.86, p = 0.02, d = 1.01, d 95% CI [0.27, 1.74]). Additionally, 5-min RPO was higher too in the Cycling & Core compared to Cycling-only (t(32) = 2.46, p = 0.049, d = 0.87, d 95% CI [1.14, 1.59]).
Improvements in 60-sec RPO were higher too in the Cycling & Strength group (Δ = 0.51 W/kg, Δ 95% CI [0.34, 0.67] W/kg) compared to the Cycling-only (Δ = 0.02 W/kg, Δ 95% CI [-0.21, 0.24] W/kg, t(30) = 3.58, p = 0.003, d = 1.31, d 95% CI [0.51, 2.09]) and Cycling & Core (Δ = 0.13 W/kg, Δ 95% CI [-0.04, 0.3] W/kg, t(30) = 3.22, p = 0.008, d = 1.18, d 95% CI [0.39, 1.94]).
RPO in 5-min also improved more in the Cycling & Strength group (Δ = 0.22 W/kg, Δ 95% CI [0.14, 0.32] W/kg) compared to the Cycling-only (Δ = 0.05 W/kg, Δ 95% CI [-0.04, 0.14] W/kg, t(30) = 2.9, p = 0.018, d = 1.06, d 95% CI [0.29, 1.82]) and Cycling & Core (Δ = 0.06 W/kg, Δ 95% CI [-0.02, 0.14] W/kg, t(30) = 2.8, p = 0.023, d = 1.02, d 95% CI [0.26, 1.78]).
Finally, the mean 20-min RPO improvement was greater in the Cycling & Strength group (Δ = 0.22 W/kg, Δ 95% CI [0.17, 0.28] W/kg) compared to the Cycling-only (Δ = 0.07 W/kg, Δ 95% CI [0.02, 0.13] W/kg, t(32) = 3.98, p = 0.001, d = 1.41, d 95% CI [0.62, 2.17]) and Cycling & Core (Δ = 0.06 W/kg, Δ 95% CI [0.00, 0.11] W/kg, t(32) = 4.37, p < 0.001, d = 1.54, d 95% CI [0.75, 2.32]).

4. Discussion

The objective of the current study was to compare the effects of conventional strength training, core training and no strength training in trained road cyclists. The main findings were as follows: a) Conventional strength training was superior to core training and no training for the improvement of 5-second, 60-second, 5-minute and 20-minute power outputs; b) Core training was superior to no training for the improvement of 5-second power outputs only and c) There were no differences in body composition changes across the three groups although the VO2max increase was larger in the conventional strength training group.
To the best of the author´s knowledge, this is the first study to compare conventional strength versus core training for the improvement of road cycling performance. The results support previous evidence that suggested the general utility of conventional strength exercises when contextualized into a concurrent strength and endurance training program [16]. This was not the case for core exercises, a lack of effect that suggests that these types of interventions do not benefit road cyclists. Several theorical benefits have been suggested for core stability and strength training: increases in joint range and muscle extensibility; improvements in joint stability, enhanced muscle performance and optimized movement function are among the most reported [6]. Some of these possible benefits could be of interest for road cyclists given that most of them translate into better exercise economy [1,21]. Given that an improvement in exercise economy may not necessarily translate into an increase in mean maximal power outputs, the current study could have overlooked this hypothetical benefit, which should be explored in the future [7]. Despite this possibility, most cyclists have limited time to train and need to limit cycling time in order to incorporate some kind of strength training into their routine. Accordingly, the results of the current study suggest most cyclists would make a better use of their time by performing conventional strength exercises rather than core training.
Core training resulted in an increase in 5-second RPO when compared to no strength training. This finding should be further contextualized as the no strength training group actually decreased its sprinting power after the 12-week intervention period. This could be related to the fact that no sprints were performed during the study. Although the improvement (or better said, maintenance) of sprinting power during the preparatory period of the annual training cycle could be of interest, it is normally not the main objective of this phase of the season and given the time and effort required to perform the core training sessions, the potential benefit could not result as attractive in this case [10,13]. Theoretically, an improvement in core strength and stability could result in an optimized movement pattern during sprinting, which would result in an increase in power output during this race moment [10]. However, as of today, it is impossible to know whether an improvement in core strength and stability is the cause of this effect: there is lack of a gold standard method for measuring core stability and strength during sporting movements. Further, few studies have observed any performance enhancement in sporting activities despite observing improvements in core stability and core strength following a core training program [6]. Finally, there are no official guidelines nor scientific evidence regarding the best intensity, volume and distribution of core training sessions for the improvement of sporting performance. Accordingly, the intervention used in the current study, although based on previous research with cyclists, may have produced an insufficient stimulus to produce any measurable change in performance [22]. Given all the above, the results of the current study do not support core training as a time-efficient strategy to improve road cycling performance.
The three groups assessed in this study presented a similar anthropometric evolution after 12 weeks of intervention. This finding is interesting given that previous research has reported increases in muscle mass, changes in fiber type and alterations of body mass after conventional strength training performed with heavy weights [1,12,16]. As the main interest of the present study was to assess the relative power output after the intervention period, changes in body mass and fat mass but not muscle mass were tracked. Therefore, the evolution of the specific components of body composition cannot be discussed in this case. Given the lack of difference in the evolution of body mass and the clear increase in VO2max in the conventional strength training group, this change can be attributed to the increase in absolute power output observed in this group [20]. Improvements in either fractional or maximal oxygen utilization have been reported in previous research and are probably related to postponed activation of less efficient type II muscle fibers, conversion of type IIX fibers into more fatigue-resistant IIa fibers, and increased muscle mass and rate of force development [12,22]. Given these results, conventional strength training is an interesting addition to cycling training in order to improve VO2max.

5. Conclusions

Road cyclists are often limited by their time availability in order to choose the best training plan for maximal performance optimization. The incorporation of strength training sessions into the weekly training routine may reduce the time spent on the bicycle and, accordingly, this decision should not be taken lightly. The present study suggests that 12 weeks of conventional strength training added to cycling during the preparatory phase of the season results in increased power outputs over the entire power curve and improves VO2max. These results were superior to those obtained from core training, which only increased power output during sprints. Given the notable performance gains and great adherence observed in the current study, it is recommended that cyclists include bi-weekly strength training sessions into their preseason. The exercises should target the main muscles activated during the pedal stroke (half squat, leg press with one leg at a time, one-legged hip flexion, and ankle plantar flexion) with intensities of 6RM and three sets per exercise.

Author Contributions

S. S, I. L-L, and R. C-S were involved in conceptualizing and design this study. S.S and I L-L were involved in the data collection and R. C-S carried out the statistics. All authors were involved in manuscript writing (review and editing) and supervised this research study. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study followed the ethical guidelines of the 2013 Declaration of Helsinki and received approval from the Research Ethics Committee of the autonomous region of Aragon, Spain (PI23/131).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Acknowledgments

The authors thank cyclists volunteered to participate in this research work.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Aagaard, P.; Andersen, J.L.; Bennekou, M.; Larsson, B.; Olesen, J.L.; Crameri, R.; Magnusson, S.P.; Kjær, M. Effects of resistance training on endurance capacity and muscle fiber composition in young top-level cyclists. Scand. J. Med. Sci. Sports 2011, 21, e298–e307. [Google Scholar] [CrossRef] [PubMed]
  2. Allen, H.; Coggan, A. Training and racing with a power meter, 3rd ed.; VeloPress: Boulder, CO, 2019. [Google Scholar]
  3. Bell, P.G.; Furber, M.J.W.; VAN Someren, K.A.; Antón-Solanas, A.; Swart, J. The Physiological Profile of a Multiple Tour de France Winning Cyclist. Med. Sci. Sports Exerc. 2017, 49, 115–123. [Google Scholar] [CrossRef] [PubMed]
  4. Castronovo, A.M.; Conforto, S.; Schmid, M.; Bibbo, D.; D’Alessio, T. How to assess performance in cycling: the multivariate nature of influencing factors and related indicators. Front. Physiol. 2013, 4, 116. [Google Scholar] [CrossRef] [PubMed]
  5. Hansen, E.A.; Rønnestad, B.R.; Vegge, G.; Raastad, T. Cyclists’ Improvement of Pedaling Efficacy and Performance After Heavy Strength Training. Int. J. Sports Physiol. Perform. 2012, 7, 313–321. [Google Scholar] [CrossRef] [PubMed]
  6. Hibbs, A.E.; Thompson, K.G.; French, D.; Wrigley, A.; Spears, I. Optimizing Performance by Improving Core Stability and Core Strength. Sports Med. 2008, 38, 995–1008. [Google Scholar] [CrossRef] [PubMed]
  7. Leo, P.; Spragg, J.; Podlogar, T.; Lawley, J.S.; Mujika, I. Power profiling and the power-duration relationship in cycling: a narrative review. Eur. J. Appl. Physiol. 2021, 122, 301–316. [Google Scholar] [CrossRef] [PubMed]
  8. Levin, G.T.; Mcguigan, M.R.; Laursen, P.B. Effect of Concurrent Resistance and Endurance Training on Physiologic and Performance Parameters of Well-Trained Endurance Cyclists. J. Strength Cond. Res. 2009, 23, 2280–2286. [Google Scholar] [CrossRef] [PubMed]
  9. Lucia, A.; Hoyos, J.; Chicharro, J.L. Physiology of Professional Road Cycling. Sports Med. 2001, 31, 325–337. [Google Scholar] [CrossRef]
  10. Menaspà, P.; Quod, M.; Martin, D.T.; Peiffer, J.J.; Abbiss, C.R. Physical Demands of Sprinting in Professional Road Cycling. Int. J. Sports Med. 2015, 36, 1058–1062. [Google Scholar] [CrossRef]
  11. Montalvo-Pérez, A.; Alejo, L.B.; Valenzuela, P.L.; Castellanos, M.; Gil-Cabrera, J.; Talavera, E.; Lucia, A.; Barranco-Gil, D. Validity of the Favero Assioma Duo Power Pedal System for Measuring Power Output and Cadence. Sensors 2021, 21, 2277. [Google Scholar] [CrossRef]
  12. Mujika, I.; Rønnestad, B.R.; Martin, D.T. Effects of Increased Muscle Strength and Muscle Mass on Endurance-Cycling Performance. Int. J. Sports Physiol. Perform. 2016, 11, 283–289. [Google Scholar] [CrossRef] [PubMed]
  13. Navalta, J.W.; Hrncir, S.P. Core stabilization exercises enhance lactate clearance following high-intensity exercise. J. Strength Cond. Res. 2007, 21, 1305–1309. [Google Scholar] [CrossRef] [PubMed]
  14. Pallares, J.G.; Hernández-Belmonte, A.; Valenzuela, P.L.; Muriel, X.; Mateo-March, M.; Barranco-Gil, D.; Lucia, A. Field-derived maximal power output in cycling: an accurate indicator of maximal performance capacity? International journal of sports physiology and performance 2022, 17, 1558–1564. [Google Scholar] [CrossRef] [PubMed]
  15. Rønnestad, B.R.; Hansen, E.A.; Raastad, T. Effect of heavy strength training on thigh muscle cross-sectional area, performance determinants, and performance in well-trained cyclists. Eur. J. Appl. Physiol. 2009, 108, 965–975. [Google Scholar] [CrossRef] [PubMed]
  16. Rønnestad, B.R.; Mujika, I. Optimizing strength training for running and cycling endurance performance: A review. Scand. J. Med. Sci. Sports 2014, 24, 603–612. [Google Scholar] [CrossRef] [PubMed]
  17. Sitko, S.; Cirer-Sastre, R.; Corbi, F.; López-Laval, I. Functional Threshold Power as an Alternative to Lactate Thresholds in Road Cycling. J. Strength Cond. Res. 2022, 36, 3179–3183. [Google Scholar] [CrossRef] [PubMed]
  18. Sitko, S.; Cirer-Sastre, R.; Corbi, F.; López-Laval, I. Five-Minute Power-Based Test to Predict Maximal Oxygen Consumption in Road Cycling. Int. J. Sports Physiol. Perform. 2022, 17, 9–15. [Google Scholar] [CrossRef]
  19. Sitko, S.; Cirer-Sastre, R.; Corbi, F.; López-Laval, I. Power Assessment in Road Cycling: A Narrative Review. Sustainability 2020, 12, 5216. [Google Scholar] [CrossRef]
  20. Sunde, A.; Støren, Ø.; Bjerkaas, M.; Larsen, M.H.; Hoff, J.; Helgerud, J. Maximal Strength Training Improves Cycling Economy in Competitive Cyclists. J. Strength Cond. Res. 2010, 24, 2157–2165. [Google Scholar] [CrossRef]
  21. Vikmoen, O.; Ellefsen, S.; Trøen, Ø.; Hollan, I.; Hanestadhaugen, M.; Raastad, T.; Rønnestad, B.R. Strength training improves cycling performance, fractional utilization of VO2max and cycling economy in female cyclists. Scandinavian journal of medicine & science in sports 2016, 26, 384–396. [Google Scholar] [CrossRef]
  22. Warburton, D.E.R.; Jamnik, V.; Bredin, S.S.D.; Shephard, R.J.; Gledhill, N. The 2019 Physical Activity Readiness Questionnaire for Everyone (PAR-Q+) and electronic Physical Activity Readiness Medical Examination (ePARmed-X+): 2019 PAR-Q+. The Health & Fitness Journal of Canada 2018, 11, 80–83. [Google Scholar] [CrossRef]
Figure 1. Individual changes in RPO by test.
Figure 1. Individual changes in RPO by test.
Preprints 94751 g001
Table 1. Summary of participant characteristics.
Table 1. Summary of participant characteristics.
Variable Cycling Cycling & Core Cycling & Strength
Age (years) 30 (4) [22, 36] 29 (5) [21, 37] 28 (4) [22, 36]
Body height (cm) 180 (6) [170, 190] 179 (5) [169, 187] 179 (5) [170, 185]
Body mass (kg) 69 (6) [60, 80] 69 (3) [62, 73] 70 (4) [60, 74]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

Subscribe

© 2024 MDPI (Basel, Switzerland) unless otherwise stated