*Article* **Effect of 12 Weeks Core Training on Core Muscle Performance in Rhythmic Gymnastics**

**Paula Esteban-García 1,\* , José Fernando Jiménez-Díaz <sup>1</sup> , Javier Abián-Vicén 1 , Alfredo Bravo-Sánchez <sup>1</sup> and Jacobo Á. Rubio-Arias <sup>2</sup>**


**Simple Summary:** The aim of this study was to analyze the effect of 12 weeks of core muscle training on core muscle performance in rhythmic gymnasts. Core strength training leads to improvements in body composition, as well as improvements in trunk strength and increases in muscle electromyographic activity. These improvements could therefore improve performance during competitive rhythmic gymnastics exercises.

**Abstract:** Background: Rhythmic gymnastics performance is characterized by technical elements involving flexibility, aerobic capacity and strength. Increased core strength in rhythmic gymnastics could lead to improved sporting performance. Objective: The aim of this study was to analyze the effect of 12 weeks of core muscle training on core muscle performance in rhythmic gymnasts. Methods: A randomized controlled study involving 24 rhythmic gymnastics was conducted. Participants were randomly assigned to a control group (CG; *n* = 12; age 13.50 ± 3.17 years) or a training group (TG; *n* = 12; age 14.41 ± 2.35 years). Body composition, isometric strength of trunk, core endurance and core muscle electromyographic activity were measured (EMG) after 12 weeks of core training. Independent sample t-tests were carried out to compare baseline values between groups. A two-way repeated-measures analysis of variance (ANOVA) (time × group) was applied. Results: The TG improved body composition, trunk lean mass (mean differences MD = −0.31; *p* = 0.040), lean mass (MD = 0.43; *p* = 0.037) and bone mass (MD = −0.06; *p* < 0.001) after training. Core training increased isometric strength of trunk, flexion test (MD = −21.53; *p* = 0.019) and extension test (MD = 22.7; *p* = 0.049), as well as the prone bridge core endurance test (MD = −11.27; *p* = 0.040). The EMG values also increased in the TG in prone bridge for front trunk (MD = −58.58; *p* = 0.026). Conclusions: Core strength training leads to improvements in body composition, as well as improvements in trunk strength and increases in muscle electromyographic activity. These improvements could therefore improve performance during competitive rhythmic gymnastics exercises.

**Keywords:** strength; muscular activity; electromyography; core endurance test; muscular performance

### **1. Introduction**

Rhythmic gymnastics started as a sport in the 1940s and debuted as an Olympic sport at the 1984 Olympic Games [1]. Aesthetic movements, flexibility, artistic and competitive components are distinct characteristics of rhythmic gymnasts [2]. Bobo-Arce and Méndez-Rial (2013) suggested that rhythmic gymnastics is a sport with a particular training process, very young athletes, earlier specialization, a large volume of training, lots of repetition and high levels of physical and psychological stress in competition. Elements of physical fitness such as flexibility, strength and aerobic capacity have been shown to be determinants of performance in rhythmic gymnastics [3,4]. Thus, physical, technical and psychological

**Citation:** Esteban-García, P.; Jiménez-Díaz, J.F.; Abián-Vicén, J.; Bravo-Sánchez, A.; Rubio-Arias, J.Á. Effect of 12 Weeks Core Training on Core Muscle Performance in Rhythmic Gymnastics. *Biology* **2021**, *10*, 1210. https://doi.org/10.3390/ biology10111210

Academic Editors: Filipe Manuel Clemente, Georgian Badicu, Eugenia Murawska-Ciałowicz and Johannes Vogel

Received: 3 November 2021 Accepted: 18 November 2021 Published: 19 November 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

skills, and motor control and harmony of movement are key factors in the performance of gymnasts [2].

For appropriate control and harmony of movements, gymnasts need adequate strength development, which allows them to maintain technical elements of great amplitude. In gymnastic disciplines, to perform a maximum number of strength elements in a competition routine, a high level of specific strength endurance is required [5]. Relative strength is considered to be a more important determinant of gymnastics performance than absolute strength [6], which is why many training systems use the gymnasts' own body weight to prepare them [7]. In this respect, an example of strength training with body weight is the training of the central trunk muscles (core). It is suggested that having a strong core allows for the complete transfer of forces developed with the lower extremities through the trunk to the upper extremities [7]. Many gymnastic movements are generated in the lower body, with the flexion-extension of the legs giving rise to positions held by the whole body for a few seconds, which require isometric and stabilizing strength of the central musculature, mainly. Therefore, an adequate development of the core in rhythmic gymnasts could evoke an increase in sporting performance [1], helping the execution and maintenance of technical movements. Furthermore, a link has been established between trunk stability and lower limb injuries or low back pain [8], so that specific trunk training could reduce this risk [9].

In order to be able to assess the force generated by gymnasts or athletes, there are quantitative measurements of maximal voluntary strength that can be performed with isometric testing on isokinetic dynamometers [9]. In these tests, maximum voluntary contraction (MVC) can be performed in both flexion and extension to quantify trunk strength [8]. On the other hand, for the measurement of endurance strength in athletes, trunk tests such as the McGill test are often used to assess endurance capacity and core stability [10]. Muscle activation assessment tests, such as surface electromyography (sEMG), can also be considered useful tools for assessing muscle activation [8]. In sport, the positive relationship between muscle activation and performance can be established [11].

On the other side, the study of anthropometric variables associated with sports performance is interesting because some studies associate variables such as weight, height, body mass index and lean mass with strength [12,13]. In gymnasts, a negative relationship has been established between fat mass values and improvements in strength and performance [14]; this makes it interesting to assess the gymnasts' body composition and its possible relation to training.

In some sports, improving trunk strength and endurance can increase the ability to generate and maintain strength [15]. Demand for athletic performance responses by the muscles of the whole body and core acts as a bridge between the upper and lower extremities and provides a stable base to transfer force to the extremities [16]. Strength and endurance training of the core musculature could increase trunk stability in gymnasts, facilitating the transmission of forces generated between the upper and lower limbs [16,17]. Furthermore, it has been shown that the improvement in trunk strength is positively related to the extensor strength of this musculature, allowing gymnasts to achieve greater technical performance in all their back trunk extension movements [18].

Several studies suggest that athletes should perform trunk strength training to improve their athletic performance [10,12], demonstrating the effect of trunk training on athletes' performance. However, there are few studies that analyze the effect of specific trunk training in rhythmic gymnasts on trunk muscle performance. Considering that specific trunk training, in addition to rhythmic gymnastics training, could improve trunk strength and stability and thus indirectly improve performance, the aim of this study was to analyze the effect of 12 weeks of core training in gymnasts who were still training in rhythmic gymnastics on body composition, isometric trunk strength, trunk endurance and electromyographic activity of trunk muscles.

#### **2. Materials and Methods**

#### *2.1. Study Design*

This study used a randomized, controlled single-blind design. A quasi-experimental intra- and inter-subject design with pre- and post-test, and with a control group, was used to identify the effects of 12 weeks of core training on the performance of the core muscles. Subjects were randomized into two groups: a control group (CG) or a training group (TG).

#### *2.2. Participants*

A total of 24 national women rhythmic gymnasts (*n* = 24; age 13.95 ± 2.77 years; height 151.39 ± 12.34 cm; weight 43.00 ± 12.82 Kg) were randomly divided into two groups: CG (*n* = 12; age 13.50 ± 3.17 years; height 147.87 ± 11.63 cm; weight 38.76 ± 11.91 Kg) and TG (*n* = 12; age 14.41 ± 2.35 years; height 154.91 ± 12.50 cm; weight 47.25 ± 12.74 Kg). The gymnasts of both groups continued their rhythmic gymnastics training on a regular basis, and core training was only applied to the gymnasts of the TG group. All participating gymnasts followed the same training, both gymnastic and core specific. The training protocols (gymnastics and core) were designed by the study researchers and subsequently applied by the trainers, previous familiarization and an informative session. In order to ensure the process, the study's principal investigator monitored the training sessions. The inclusion criteria were that they had training experience of 2 years, competed in the national category and trained ≥9 h per week. All the gymnasts and their parents received written and verbal information regarding the nature of this investigation and provided written informed consent before the beginning of the study. Ethical approval was obtained from the Clinical Research Ethics Committee of the Toledo Healthcare Area (number 112/2015). This study complied with the ethical principles of the Declaration of Helsinki.

#### *2.3. Procedures*

The week before the start of the measurements, the gymnasts performed a 90 s warmup and then were familiarized with the isometric and core endurance tests at moderate intensity, and in addition, signed the informed consent documents. On the day of data collection all the measurements were taken by the authors and the instruments were calibrated prior to use. First of all, stature and body mass were measured on a portable scale with a stadiometer (model 700, Seca, Hamburg, Germany) and body composition and densitometry were recorded. Then the rhythmic gymnasts completed a 10 min warm-up on a bicycle ergometer, using self-chosen resistance at 40–60 rpm (20–30 watts), followed by 5 min of stretching exercises for the trunk and lower extremities, the isometric test, and McGill's core endurance test. Surface electromyography (sEMG) of the core was recorded during the isometric and McGill's core endurance tests (Table 1).

**Table 1.** Study protocol.


Body composition and densitometry measurements were taken following the standardized techniques of the International Society for the Advancement of Kinanthropometry (ISAK), fat mass (FM, in Kg) (ICC: 0.99–0.98; CV: 2.6%), total lean mass (LM, in Kg) (ICC: 0.99–0.99; CV: 0.8%), bone mass (BM, in Kg) (ICC: 0.99–0.99; CV: 0.6%) fat tissue percentage (FT%) (ICC: 0.99–0.99; CV: 2.7%) and trunk lean mass (TLM, in Kg) (ICC: 0.99–0.98; CV: 1.6%) were assessed using dual-energy X-ray absorptiometry (DXA) (Lunar iDXA, General Electric Healthcare, Fairfield, CT, USA) [19].

The isometric tests for maximum strength of trunk were performed with a Biodex isokinetic dynamometer (Biodex System 3; Biodex Medical Systems, Inc., Shirley, NY, USA). Maximum voluntary contraction (MVC) exerted in isometric contraction for trunk

flexion and extension was evaluated in terms of peak torque (PT, in N·m) (ICC: 0.87–0.92; CV: 10.5%). Isometric strength measurements were made following the protocols described by Waldhelm and Li (2012) [20] (Figure 1). Trunk flexion and extension were performed while standing, with trunk straight, looking straight ahead, pelvis stabilized, and without upper extremity support. The average of three peak torque with 2 min rest in between was taken for later analysis. The gymnasts held each contraction for 5 s with 30 s rest between trials [19]. *Biology* **2021**, *10*, x FOR PEER REVIEW 4 of 13 between was taken for later analysis. The gymnasts held each contraction for 5 s with 30 s rest between trials [19].

**Figure 1.** Core muscular training exercise. **Figure 1.** Isometric strength measurements.

Core endurance was measured for the same person with the McGill test [10]. The core endurance tests were the extensor endurance test or Biering-Sorensen test (Sorensen) and the prone bridge test (prone bridge). Gymnasts maintained these positions as long as possible, and the time was measured in each test in s. Both tests were considered failures when the gymnast lost the horizontal with respect to the floor. The Sorensen test began with lying prone, with the lower body manually fixed, hips extended over the edge of the test surface, and hands on the opposite shoulders. The prone bridge test was performed on the ground. The gymnasts had to maintain the prone position supporting themselves on their feet and forearms with shoulders and elbows in 90° flexion. Forearms needed to Core endurance was measured for the same person with the McGill test [10]. The core endurance tests were the extensor endurance test or Biering-Sorensen test (Sorensen) and the prone bridge test (prone bridge). Gymnasts maintained these positions as long as possible, and the time was measured in each test in s. Both tests were considered failures when the gymnast lost the horizontal with respect to the floor. The Sorensen test began with lying prone, with the lower body manually fixed, hips extended over the edge of the test surface, and hands on the opposite shoulders. The prone bridge test was performed on the ground. The gymnasts had to maintain the prone position supporting themselves on their feet and forearms with shoulders and elbows in 90◦ flexion. Forearms needed to remain pronated.

remain pronated. sEMG was measured during McGill's core endurance and isometric tests. An 8-channel sEMG ME 6000TE (Mega Electronics, Kuopio, Finland) was used for data collection. sEMG signals from the flexor muscles of the front trunk were analyzed as a group, as were the extensor muscles of the back trunk. The average value of muscle activation (EMG root mean square (rms), EMGrms in µV) (ICC: 0.87–0.94; CV: 12.8%) was measured during the middle 3 s of the 5 s of contraction**.** Each gymnast's skin was prepared for sEMG evaluation according to guidelines of the SENIAM organisation [21], including scrubbing and cleaning with alcohol. Electrodes were placed bilaterally on the front trunk muscles (rectus abdominis, external oblique abdominis) and back trunk muscles (erector spinae). Two 10 mm diameter Ag-AgCl surface electrodes were used on each muscle for data collection. The sampling rate was set at 1000 Hz per channel. The signals were filtered at 500 Hz, and further filtered. The raw data were stored and subsequently processed. The sEMG data were fully rectified and smoothed and the rms was normalized to the signal recorded with sEMG was measured during McGill's core endurance and isometric tests. An 8-channel sEMG ME 6000TE (Mega Electronics, Kuopio, Finland) was used for data collection. sEMG signals from the flexor muscles of the front trunk were analyzed as a group, as were the extensor muscles of the back trunk. The average value of muscle activation (EMG root mean square (rms), EMGrms in µV) (ICC: 0.87–0.94; CV: 12.8%) was measured during the middle 3 s of the 5 s of contraction. Each gymnast's skin was prepared for sEMG evaluation according to guidelines of the SENIAM organisation [21], including scrubbing and cleaning with alcohol. Electrodes were placed bilaterally on the front trunk muscles (rectus abdominis, external oblique abdominis) and back trunk muscles (erector spinae). Two 10 mm diameter Ag-AgCl surface electrodes were used on each muscle for data collection. The sampling rate was set at 1000 Hz per channel. The signals were filtered at 500 Hz, and further filtered. The raw data were stored and subsequently processed. The sEMG data were fully rectified and smoothed and the rms was normalized to the signal recorded with peak maximum value [22].

peak maximum value [22].

### *2.4. Intervention*

Core muscular training was performed in two alternative sessions per week for 12 weeks, supplementary to gymnastic training, included three progressions of difficulty, periods 1, 2, and 3 (Table 2) and each period lasted for 4 weeks. The core program was based on core training by McGill, (2010), increasing the number of series and not the maintenance time of the isometry, due to the commitment to the level of tissue oxygenation in this type of prolonged contraction [23]. The core exercises were performed at the end of the rhythmic gymnastics' session. The core program comprised eight exercises, that is, hollowing (A), bracing (A), dissociation of shoulder girdle and pelvic girdle (B), Cat-Camel (C), quadrupedal stance (D), front bridge (E), side bridge (both sides) (F) and supine bridge (G) (Figure 2). *Biology* **2021**, *10*, x FOR PEER REVIEW 6 of 13

**Figure 2.** Core muscular training exercise. (**A**) Hollowing; (**B**) Bracing; (**C**) Dissociation; (**D**) Cat-Camel; (**D**) Quadrupedal; (**E**) Front Bridge; (**F**) Side Bridge; (**G**) Supine Bridge. **Figure 2.** Core muscular training exercise. (**A**) Hollowing; (**B**) Bracing; (**C**) Dissociation; (**D**) Cat-Camel; (**D**) Quadrupedal; (**E**) Front Bridge; (**F**) Side Bridge; (**G**) Supine Bridge.

Cat-Camel 10 sets 10 sets Supine Bridge 2 × 5 sets × 20 s (15 s rest)

Front Bridge Front Bridge 2 × 5 sets (both sides)

Hollowing 10 sets 10 sets Bracing 10 sets 10 sets Dissociation 5 sets 5 sets

(15 s rest)

2 × 7 sets of 20 s (15 s rest)

Quadrupedal 8 sets of 20 s

**Volume Volume Progress Volume** 

Quadrupedal Birddog exercise 2 × 5 sets

Front Bridge destabilisation 2 × 5 sets × 20 s) (15 s rest)

(both legs)

**Table 2.** The Core program.


#### **Table 2.** The Core program.

#### *2.5. Data Analysis*

Statistical analysis of data was performed with the Statistical Package for the Social Sciences (IBM Corp. IBM SPSS Statistics for Windows, Version 24.0. Armonk, NY, USA: IBM Corp.). Descriptive statistics were calculated using the mean and standard deviation and the mean difference using confidence intervals. The Shapiro–Wilk test was used to analyze data distribution, getting a normal distribution. Subsequently, independent sample *t*-tests were carried out to compare baseline values between groups. In addition, a two-way repeated-measures analysis of variance (ANOVA) (time × group) was applied to analyze the effect of the intervention on outcomes. Eta squared (η 2 ) effect sizes for the time × group interaction effects were calculated. An effect of η <sup>2</sup> <sup>≥</sup> 0.01 indicates a small, ≥0.059 a medium, and ≥0.138 a large effect. For those variables that showed significant main effects, post-hoc tests (Bonferroni) were performed. The effect size (d) was calculated following the guidelines of Cohen [24]. The d was considered large (>0.80), moderate (0.5) and small (<0.2). An effect was considered statistically significant when *p* ≤ 0.05.

#### **3. Results**

All participants completed the intervention and were included in the data analysis. No difference was observed between groups at baseline. Maximum growth velocity (MGA) was measured as a widely used indicator to assess biological maturation [25]. The age and height of the subjects were used to determine their biological maturation [26]. No significant differences in biological maturation were found between pre- and post-training in CG (*p* = 0.349), TG (*p* = 0.339) and between CG and TG in pre-training (*p* = 0.351).

#### *3.1. Body Composition and Densitometry*

Results for body composition are presented in Table 3. We observed no differences between the two groups for either of the two time-line measurements (*p* > 0.05). Withingroup analysis showed an increase in the TG between pre- and post-core training in TLM (*p* = 0.040, d = −0.7; 95% confidence interval [CI] of the mean differences [MD] of the score = 0.03 Kg, 1.29 Kg), in LM (*p* = 0.037, d = −0.7; 95% CI of MD = 0.04 Kg, 1.30 Kg), and in BM (*p* < 0.001, d = −1.3; 95% CI of MD = 0.52 Kg, 2.09 Kg), and the CG showed an

increase in BM (*p* = 0.003, d = −1.1; 95% CI of MD = 0.35 Kg, 1.79 Kg) and a decrease in the FT% (*p* = 0.044, d = 0.5; 95% CI of MD = −1.12%, −0.09 Kg).


FM: fat mass; LM: lean mass; BM: bone mass; %FT: average fat tissue; TLM: trunk lean mass; SD: standard deviation; *p* ≤ 0.005.

#### *3.2. Isometric Tests in Isokinetic Dynamometer and Electromyography Analysis*

Results for the PT and EMGrms in the isometric tests are presented in Table 4. We observed no differences between the two groups for either of the two measurements (*p* > 0.05). Within-group analysis of the TG showed increases (*p* < 0.05) between preand post-core training in PT in the flexion isometric test (*p* = 0.019, d = 0.6; 95% CI of MD = 0.03 N·m, 1.20 N·m) and the extension isometric test (*p* = 0.049, d = 0.5; 95% CI of MD = 0.07 N·m, 1.15 N·m). In addition, the CG showed decreases of EMGrms in front trunk in the flexion isometric test (*p* = 0.03, d = 0.6; 95% CI of MD = −1.19 µV, −0.04 µV) and the TG decreases of EMGrms in the back trunk in the extension isometric test (*p* = 0.04, d = 0.7; 95% CI of MD = −1.326 µV, −0.054 µV).

**Table 4.** Performance in isometric test and electromyography values.


PT: peak torque; EMGrms: average electromyography activity; SD: standard deviation; *p* ≤ 0.005.

### *3.3. Endurance Test and Electromyography Analysis*

Results for the core endurance test are presented in Table 5. We observed no differences between the two groups for either of the two endurance core tests (*p* > 0.05). Within-group analysis of the TG showed an increase between pre- and post-training in prone bridge (*p* = 0.044, d = −0.5; 95% CI of MD = 0.083 s, 1.131 s). For EMG in the endurance test, we observed no differences between the two groups for either of the two tests (*p* > 0.05). However, within-group analysis of the TG showed an increase between pre- and postcore training in EMGrms front trunk in prone bridge (*p* = 0.030, d = −0.5; 95% CI of MD = 0.035 µV, 1.197 µV) (Figure 3).


SD: standard deviation; *p* ≤ 0.005.

**Table 5.** Performance in McGill test.

**Figure 3.** Significant difference EMGrms front in prone bridge endurance test/TG. **Figure 3.** Significant difference EMGrms front in prone bridge endurance test/TG.

#### **4. Discussion 4. Discussion**

The aim of this study was to analyze the effect of 12 weeks of core training in gymnasts who were still training in rhythmic gymnastics on body composition, isometric and endurance strength core and core muscle electromyographic activity. The main findings were that the core training evoked an increase in trunk lean mass, lean mass and bone mass, and moreover the values of isometric strength and endurance strength and EMG in The aim of this study was to analyze the effect of 12 weeks of core training in gymnasts who were still training in rhythmic gymnastics on body composition, isometric and endurance strength core and core muscle electromyographic activity. The main findings were that the core training evoked an increase in trunk lean mass, lean mass and bone mass, and moreover the values of isometric strength and endurance strength and EMG in the core during the endurance test improved.

the core during the endurance test improved. Regarding body composition, the TG showed higher values of TLM, LM and BM after core muscular training and the CG in the BM and lower values in the FT%. To our knowledge, there are no studies on the effect of core training on the body composition of gymnasts. However, it is possible to find similarities with our results in the study by Skrypnik et al. [27] , where different types of interventions, resistance training and endurance strength training were compared on body composition. Only the resistance strength training group obtained a significant increase in total lean body mass (<0.001) and total fat-free body mass (<0.001). In this respect, therefore, the gains in lean mass with resistance training, used in core muscle training, would be justified. Similarly, Piacentini et al. [28], evaluated the effects of two different strength training protocols on resting metabolic rate, body composition, running economy and strength parameters, in young elite endurance athletes. Both training protocols included core muscle strength, and both also showed a decrease in body fat percentage and fat mass that reflected a significant increase in fatfree mass in the young athletes. On the evidence of these results, it can be said that the changes in body composition produced by core training in gymnasts may be due to the influence that strength training has on these parameters. In addition, the CG showed Regarding body composition, the TG showed higher values of TLM, LM and BM after core muscular training and the CG in the BM and lower values in the FT%. To our knowledge, there are no studies on the effect of core training on the body composition of gymnasts. However, it is possible to find similarities with our results in the study by Skrypnik et al. [27], where different types of interventions, resistance training and endurance strength training were compared on body composition. Only the resistance strength training group obtained a significant increase in total lean body mass (<0.001) and total fat-free body mass (<0.001). In this respect, therefore, the gains in lean mass with resistance training, used in core muscle training, would be justified. Similarly, Piacentini et al. [28], evaluated the effects of two different strength training protocols on resting metabolic rate, body composition, running economy and strength parameters, in young elite endurance athletes. Both training protocols included core muscle strength, and both also showed a decrease in body fat percentage and fat mass that reflected a significant increase in fat-free mass in the young athletes. On the evidence of these results, it can be said that the changes in body composition produced by core training in gymnasts may be due to the influence that strength training has on these parameters. In addition, the CG showed

lower fat mass values after the intervention period, which can be explained by higher

tic training, the effect of rhythmic gymnastics training cannot be ruled out. The effect that gymnastic training has on athletes in increasing bone mass has been demonstrated in comparison to other sports or control subjects [29,30]. This is related to the fact that both training groups in our research showed significant increases in BM. This is because the subjects were 13.95 ± 2.77 years old and in puberty, when bone mass mineral accrual increases substantially during the growing years [31]. Puberty is an opportune time for bone strengthening [32], when the mechanical loading of athletic training is a positive factor for

lower fat mass values after the intervention period, which can be explained by higher initial fat mass values from this group and by the CG continued with their usual gymnastic training, the effect of rhythmic gymnastics training cannot be ruled out. The effect that gymnastic training has on athletes in increasing bone mass has been demonstrated in comparison to other sports or control subjects [29,30]. This is related to the fact that both training groups in our research showed significant increases in BM. This is because the subjects were 13.95 ± 2.77 years old and in puberty, when bone mass mineral accrual increases substantially during the growing years [31]. Puberty is an opportune time for bone strengthening [32], when the mechanical loading of athletic training is a positive factor for skeletal strength, for maximizing bone mineral gain and reducing the risk of osteoporosis in later life [33,34]. Gruodyte-Raciene et al. [35], and Gruodyté et al. [30], consider that gymnastic training is especially osteogenic for bone development in children and adolescents. Therefore, although gymnastic training may already have a positive effect on the body composition of gymnasts, added core training could have greater benefits for the body composition of female athletes. A relationship is established between gymnasts' body composition and performance, with low values of fat mass being a determinant of performance [14,36].

In relation to isometric strength in the isometric test on the dynamometer, significant effects were found between pre- and post-core training in the TG. There are no studies on rhythmic gymnastics or other sports about the effect of core training on isometric trunk strength. Improvements in isometric trunk strength, both in flexion and extension, of gymnasts after training benefit these athletes, because they need upper body endurance strength and trunk muscle function to be successful in competition. Improving trunk strength and endurance would allow gymnasts to increase their ability to generate and maintain force throughout their routine. Core stability might contribute to the gymnast's performance as it would facilitate the transmission of forces generated by the lower to the upper body during technical elements and it would enhance balance control [15]. The positive data on the gymnasts' isometric strength after core training could reflect the positive effect of core training as a complementary training to gymnastic training. On the other hand, the results obtained in muscle activation, during the isometric test on the dynamometer, reflect a decrease in both study groups. This may be due to other types of neural adaptations that are not evaluated with the amplitude of the sEMG signal, such as inhibition of the antagonistic muscles, greater activation of the synergistic muscles or better inter-muscular coordination [37].

Similarly, the results obtained in the McGill endurance test and muscle activation in these tests, reflected significant effects between pre- and post-core training. The TG rhythmic gymnasts increased the maintenance time in prone bridge, as well as the muscle activation in the front trunk. In accordance with these results, previous studies have demonstrated that core training increases the maintenance time in the endurance test, and so increases trunk strength and stability strength in women collegiate gymnasts [38], dance students [39] or competitive collegiate dancers [40]. In this sense, the added and positive effect that core training could have on the gymnasts is again reflected.

Several considerations and limitations should be acknowledged. The evaluation of performance in rhythmic gymnastics was not carried out, so it cannot be confirmed that improvements in the training group had a direct influence on performance in competition. There was no control of the external activities that the participants of the sample did outside of the training. The sample size of the study can be considered small. However, the study has the strength to be considered the first to evaluate the effect of core training on national level rhythmic gymnasts. This core training program considered that the improvements found in the gymnasts are due more to core training combined with gymnastic training than to rhythmic gymnastics training alone because some improvements only occurred in the group that performed core training. Therefore, possible lines of research could analyze the effect of this type of core training on gymnastic performance, on the execution of technical gestures or on the judges' evaluation.

#### **5. Conclusions**

Our results suggest that combining a traditional rhythmic gymnastics program with a core training program could lead to increased strength and improved body composition. Additionally, core strength training produces improvements in trunk strength values in gymnasts, in addition to increasing muscle activation values.

#### **6. Practical Applications**

The proposed training is considered a useful tool for the training of gymnasts by their coaches. The improvements observed in the group that carried out a core program in addition to their traditional training presented improvements in strength and muscle activation capacity and this could have a positive transfer to competition. However, more studies analyzing the transference effect towards competition are needed.

The gains in strength and stability achieved will help coaches improve the physical preparation of gymnasts, and thus increase the technical level.

In addition, core muscle strength training may be of interest to another type of population, such as older adults, since ageing is associated with a variety of biological changes that can contribute to the decline of skeletal muscle mass, strength, and function [41].

**Author Contributions:** Conception: P.E.-G. and J.F.J.-D.; Performance of work: P.E.-G. and A.B.-S.; Interpretation or analysis of data: P.E.-G. and J.Á.R.-A.; Preparation of the manuscript: P.E.-G. and A.B.-S.; Revision for important intellectual content: J.F.J.-D., J.A.-V. and J.Á.R.-A.; Supervision: J.F.J.-D., J.A.-V. and J.Á.R.-A. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Ethical approval was obtained from the Clinical Research Ethics Committee of the Toledo Healthcare Area (number 112/2015). This study complied with the ethical principles of the Declaration of Helsinki.

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

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**Cristian Marín-Pagán 1,\*, Stéphane Dufour 2,3, Tomás T. Freitas 1,4,5 and Pedro E. Alcaraz <sup>1</sup>**


**Simple Summary:** Overall, adolescence brings upon many bodily changes that modify physical capacities. To better understand these physiological changes and the characteristics of each stage of adolescent development in youth cycling, it is necessary to describe and compare cyclists that pertain to lower categories. Parameters such as maximum oxygen uptake, fat oxidation capacity, functional power threshold, and ventilatory thresholds are decisive predictors of performance in future stages. The aim of this study was to evaluate and compare the physiological profile of different road cyclist age categories (Youth, Junior, and Under-23) to obtain the performance requirements. The results suggest major differences, with the Youth group showing clear changes in all metabolic zones except in fat oxidation. The Youth group physiological profile is clearly different from the other age categories. The present results suggest that the Juniors' qualities are closer to adult performance, however, little is known about sports performance indicators in adolescent cyclists.

**Abstract:** Endurance profile assessment is of major interest to evaluate the cyclist's performance potential. In this regard, maximal oxygen uptake and functional threshold power are useful functional parameters to determine metabolic training zones (ventilatory threshold). The aim of this study was to evaluate and compare the physiological profile of different road cyclist age categories (Youth, Junior, and Under-23) to obtain the performance requirements. Sixty-one competitive road cyclists (15–22 years) performed a maximal incremental test on a bike in order to determine functional parameters (maximal fat oxidation zone, ventilatory thresholds, maximal oxygen uptake, and functional threshold power) and metabolic training zones. The results suggest major differences, with the Youth group showing clear changes in all metabolic zones except in fat oxidation. The main differences between Under-23 vs. Junior groups were observed in maximal relative power output (Under-23: 6.70 W·Kg−<sup>1</sup> ; Junior: 6.17 W·Kg−<sup>1</sup> ) and relative functional threshold power (Under-23: 4.91 W·Kg−<sup>1</sup> ; Junior: 4.48 W·Kg−<sup>1</sup> ). The Youth group physiological profile is clearly different to the other age categories. Some parameters normalized to body weight (maximal oxygen consumption, load and functional threshold power) could be interesting to predict a sporting career during the Junior and Under-23 stages.

**Keywords:** cycling; endurance; oxygen uptake; FTP; threshold; power

### **1. Introduction**

Cycling is considered one of the most stressful and physically demanding sports, with the road stage races being its most popular modality. In professional road cyclists, values for maximal oxygen uptake (VO2max) higher than 70–80 mL·Kg−<sup>1</sup> ·min−<sup>1</sup> have repeatedly been observed [1,2]. Although very high, such VO2max values appear more as a prerequisite to achieve professional level rather than good performance predictor [3]. As

**Citation:** Marín-Pagán, C.; Dufour, S.; Freitas, T.T.; Alcaraz, P.E. Performance Profile among Age Categories in Young Cyclists. *Biology* **2021**, *10*, 1196. https://doi.org/ 10.3390/biology10111196

Academic Editors: Filipe Manuel Clemente, Georgian Badicu and Eugenia Murawska-Ciałowicz

Received: 11 October 2021 Accepted: 16 November 2021 Published: 17 November 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

such, maximal power output during an incremental test might be a better predictor than VO2max for short efforts in flat stages, with elite cyclists achieving values between 400 and 500 W (6.0–7.5 W·Kg−<sup>1</sup> ), finding slight differences depending on the test characteristics [4,5]. Additionally, lactate threshold position seems to be more predictive than VO2max for endurance cycle performance, especially in professional climber cyclists [5] where lactate thresholds (LT2) at ~90% of VO2max have been found.

In recent years, the evaluation of cycling performance and the monitoring of cycling training load through the so-called functional threshold power (FTP) has also been of increasing scientific interest [6–8]. FTP consists of the maximum power output developed during a 1 h trial, and can be evaluated by contemplating the power developed during 20 min with the application of a correction factor of 0.95 [9]. FTP values are estimated to be around 5.0–6.0 W·Kg−<sup>1</sup> and 3–5 W·Kg−<sup>1</sup> for professional and trained amateur cyclists, respectively [9]. The FTP has become a supplementary parameter to the assessment of performance profile due to its applicability to the field in a non-invasive way and without the need for sophisticated equipment.

Achieving professional and world-class level in road cycling is a long-term process taking several years of regular, high volume, and high intensity training, most of the time from Youth, through to the Junior and Under-23 (U-23) categories. Therefore, important differences in physiological profile exist between competition levels and age categories in cycling [10]. For example, professional road cyclists complete approximately 30,000 to 35,000 km per season [4] while amateur competitive cyclists complete around 13,500 km [11]. Important changes in total volume progression have also been observed when comparing consecutive seasons from the Junior stages to World class level [12]. Similarly, higher VO2max values have been reported in elite cyclists (~74 mL·Kg−<sup>1</sup> ·min−<sup>1</sup> ) when compared to amateurs (~65 mL·Kg−<sup>1</sup> ·min−<sup>1</sup> ) [13,14]. Another critical factor that has been suggested to differentiate cyclists of superior performance levels [5,13,15] is the ability to develop power, both as peak values in incremental tests or during critical power [16] tests as a FTP [9]. Due to mentioned discrepancies between cyclists, De Pauw et al. [13] proposed a five level cycling classification according to physiological demands and training loads. Nevertheless, it is worth noting that amateur cyclists are progressively showing higher performance levels, to the extent that similarities with professionals can be found, particularly in cycling economy and efficiency [17].

Regarding age categories, previous studies have reported differences in anthropometric parameters, with athletes displaying greater left–right leg length asymmetries as they progress through to older categories [18]. This unbalance could be related to an increased training duration in more experienced cyclists to meet the demands of the competition. The characteristics of Youth and Junior races are different and very stressful for the metabolic system [19] and some countries have limited the maximal number of competitions per season during the Youth categories. As the distances are usually shorter in these categories, the average race intensity is higher. For this reason, due to the progression in training volume [12] and competition characteristics [19] the recovery time necessary after an endurance exercise increases with age [20].

On a related topic, during prolonged training and competitive efforts (>4 h), an increased fatty acid contribution to total energy turnover is observed and fat oxidation capacity could be considered as a desirable adaptation for road cycling performance [21,22]. Accordingly, assessing and training to improve this capacity are important aspects of the training process in cycling [22]. Different authors have reported that the maximal fat oxidation zone (Fatmax) is achieved at approximately 45–60% of VO2max [23,24] and that this concept is closely related to cycling economy and efficiency. The issue with the former variables is that they are somehow easy to improve in amateurs, but very difficult when it comes to professional cyclists. Thus, in highly trained cyclists, it is common to observe that endurance training is not sufficient to improve cycling economy and efficiency, which makes it necessary to rely to alternative training strategies such as resistance training to

achieve this objective [25,26], with heavy strength training being recommended to achieve improvements in aerobic performance [26,27].

From the above-mentioned, it appears that endurance performance parameters are likely different among the Youth categories, but the extent of these differences remain presently unclear. Dissimilarities in some cardiorespiratory and metabolic parameters between professionals and amateur cyclists [13,14] as well as between age categories [14] can be found in the literature. However, the differences in physiological and performance profile of three different age categories (Youth, Junior, and U-23) in the pre-season phase as well as the value of FTP in these three age categories have never been documented to date. Such knowledge might have important practical applications not only for better performance evaluation (i.e., talent identification) but also to optimize training prescription and training load management in young cyclists. Currently, there are no studies that compare the physiological profile in these categories, in order to establish differences or similarities that could help determine future performance. It is also unknown which are, in these lower categories, the most important physiological characteristics to be studied and controlled. Therefore, the aim of this study was to assess the physiological parameters and performance profile that can influence cycling performance and to compare them amongst three different age categories, from Youth to U-23.

#### **2. Materials and Methods**

### *2.1. Participants*

Sixty-one young male amateur cyclists from three distinct age categories, but with similar competitive level, participated in the study (Table 1): Youth (15–16 years); Junior (17–18 years), and U-23 (19–22 years), according to the classification of the *Union Cycliste Internacionale* (UCI). All cyclists were members of an official team, did not present any injury in the three months before the investigation and performed regular training of more than 6 h per week. Participants had at least three years of cycling training experience, were enrolled in the cycling team since "school" categories, and had previous experience in laboratory testing. Prior to study enrollment, all cyclists or the parents (of those under 18 years old) signed the consent to participate in the study (approved by the University Ethical Committee; CE022105) and obtained medical approval to participate in this study. Just before testing, weight and height were measured using a SECA 780 device (Seca, Hamburg, Germany). All tests were completed between 10 h and 14 h 2 h after breakfast intake (bread, milk or yogurt and juice). Participants did not train in the 24 h prior to testing to avoid fatigue and the test was separated from high intensity training or preseason competitions by at least 72 h.


**Table 1.** General characteristics of the participants.

UCI = Union Cycliste Internationale; SD = standard deviation (±); BMI = body mass index.

#### *2.2. Assessments*

All tests were carried out in the laboratory during pre-season (December–February). For the cardiorespiratory evaluation, a metabolic cart (Cortex Metalyzer, Leipzig, Germany) and the Cyclus2 ergometer (Cyclus, Leipzig, Germany) were used. The cyclists utilized their own bikes in all assessments. The protocol used consisted of a combined test with an initial step phase followed by final ramp. The test started at 35 W with increments of 35 W

every 2 min. Then, when the respiratory exchange ratio (RER) was ≥1.05, the final ramp of 35 W per minute (~1 W each 0.583 s) was initiated. This combined protocol was applied to determine the ventilatory thresholds (VT1 = aerobic; VT2 = anaerobic) during steady states (step phase) and continued until exhaustion to assess VO2max and maximal load (Pmax, final ramp) [28–30]. The recommended pedaling cadence was 85 to 95 rpm and the test was stopped when the participants were unable to sustain a cadence greater than 60 rpm, with permanent chainset (52–53/12 teeth). To determine blood lactate concentration, blood samples were collected from the finger at 1.5 min after exhaustion. The first blood drop was dismissed and the second was analyzed with a Lactate Pro2 (Arkray, Tokyo, Japan).

Ventilatory thresholds (VT1 and VT2) were calculated with the ventilatory equivalent method described by Wasserman [31] and using the data averaged every 20 s. The VO2max was assumed as the maximum value of the last four data of 20 s averages. To guarantee that the VO2max was achieved, at least three of the following criteria had to be obtained: (I) plateau in the final VO<sup>2</sup> values (increase <sup>≤</sup>2.0 mL·kg−<sup>1</sup> ·min−<sup>1</sup> in the two last loads); (II) maximal theoretical HR (220–age) × 0.95) for a cycling test suggested by Millet et al. [32]; (III) RER ≥1.15; and (IV) a lactate value ≥8.0 mmol·l −1 [33]. Pmax was calculated as the maximal power achieved during the final ramp in the incremental test. Maximal oxygen uptake and load were expressed in absolute units or normalized to body weight (VO2R and Load/BW, respectively). To determine the percentage of VO2max at which Fatmax was achieved, the values of VO<sup>2</sup> corresponding to maximal fat oxidation (MFO) and normalized to VO2max were selected.

Functional threshold power (FTP) was estimated using the equation described by Denham [34] using the maximal power output during VO2max test.

#### *2.3. Statistical Analysis*

All descriptive statistics were presented as mean ± standard deviation (SD) and the statistical analysis was performed using the Statistical Package for Social Sciences (SPSS 27.0, IBM, Chicago, IL, USA). A Shapiro–Wilk test was performed to assess the normality of the variables. The between-group differences were investigated using independent *t*-tests and the statistical significance was set for a *p* < 0.05. The U-23 group was established as the "reference group" for the comparative analysis, given that it was the highest competitive level. Effect sizes (ES) were calculated utilizing Cohen's equations [35]. Threshold values for ES statistics were: >0.2 small, >0.6 moderate, and >1.2 large, >2.0, very large; and >4.0, nearly perfect [36].

#### **3. Results**

*Ventilatory Threshold 1*. Significant differences were obtained between the Youth and Junior groups for VO<sup>2</sup> (*p* = 0.001; ES = 0.98), Load (*p* < 0.001; ES = 1.21) and Load/BW (*p* = 0.037; ES = 0.62). For Youth vs. U-23 group, significant differences were obtained in HR (*p* = 0.018; ES = 0.80), %VO2max (*p* = 0.005; ES = 0.97), Load (*p* < 0.001; ES = 1.32), and Load/BW (*p* = 0.002; ES = 1.06). For Junior vs. U-23, differences were only found in HR (*p* = 0.027; ES = 0.77). In this metabolic zone, the U-23 group showed the lowest percentage with respect to VO2max, and the Youth group displayed the best results (Table 2).

**Table 2.** Performance assessments data.



**Table 2.** *Cont.*

SD = standard deviation (±); VT1 = ventilatory threshold 1; VT2 = ventilatory threshold 2; HR = heart rate; VO<sup>2</sup> = oxygen uptake; VO2R = oxygen uptake normalized to body weight; VO2max = maximal oxygen uptake; BW = body weight; \* = Significant differences with the Youth group; † = Significant differences with the Junior group.

*Ventilatory Threshold 2*. For the Youth vs. Junior group comparison, significant differences were found in VO<sup>2</sup> (*p* < 0.001; ES = 1.47), VO2R (*p* = 0.020; ES = 0.70), Load (*p* < 0.001; ES = 1.51) and Load/BW (*p* = 0.011; ES = 0.77). There were also significant differences between the Youth and U-23 groups in VO<sup>2</sup> (*p* = 0.001; ES = 1.22), VO2R (*p* = 0.007; ES = 0.92), Load (*p* < 0.001; ES = 1.80), and Load/BW (*p* < 0.001; ES = 1.40). As for VT1, significant differences were found only in HR (*p* = 0.035; ES = 0.86) when comparing the Junior and U-23 groups (Table 2).

*Maximal Zone*. Significant differences were obtained between the Youth and Junior groups (Table 3 and Figure 1) for VO<sup>2</sup> (*p* < 0.001; ES = 1.42), VO2R (*p* = 0.003; ES = 0.92), Load (*p* < 0.001; ES = 1.51), Load/BW (*p* = 0.003; ES = 0.89), time to exhaustion (*p* < 0.001; ES = 1.67), and blood lactate concentration (*p* = 0.007; ES = 0.86). Similar results were obtained for Youth vs. U-23 for VO<sup>2</sup> (*p* < 0.001; ES = 1.18), VO2R (*p* = 0.002; ES = 1.08), Load (*p* < 0.001; ES = 1.95), Load/BW (*p* < 0.001; ES = 1.88), and time to exhaustion (*p* < 0.001; ES = 1.70) but not for blood lactate (*p* = 0.059; ES = 0.77), in which only a trend toward statistical significance was found. Finally, for Junior vs. U-23, significant differences were found for HR (*p* = 0.013; ES = 1.24) and Load/BW (*p* = 0.015; ES = 0.86).

**Table 3.** Maximal values in the VO2max test.



**Table 3.** *Cont.*

SD = standard deviation (±); MAX = maximal value; HR = heart rate; VO<sup>2</sup> = oxygen uptake; VO2R = oxygen uptake normalized to body weight; VO2max = maximal oxygen uptake; BW = body weight; RER = respiratory exchange ratio; \* = Significant differences with Youth group; † = Significant differences with Junior group.

**Figure 1.** Maximal oxygen uptake (**A**) and Load/BW (**B**) values. Load/BW (**A**) = work load normalized to body weight; VO2max (**B**) = maximal oxygen uptake; \* = Significant differences with Youth group; † = Significant differences with Junior group.

*Fatmax zone*. Significant between-group differences were found in this metabolic zone (Table 4) only in VO<sup>2</sup> (*p* = 0.007; ES = 0.86) and Load (*p* = 0.011; ES = 1.00) for Youth vs. U-23.


**Table 4.** Values in the maximal fat oxidation zone.

SD = standard deviation (±); HR = heart rate; VO<sup>2</sup> = oxygen uptake; VO2R = oxygen uptake normalized to body weight; VO2max = maximal oxygen uptake; BW = body weight; RER = respiratory exchange ratio; MFO = maximal fat oxidation; \* = Significant differences with the Youth group.

*Estimated functional threshold power*. For the estimated FTP, significant differences were found (Table 5) between the Youth and the other two groups (Junior and U-23, *p* < 0.001; ES = 1.50 and 2.66, respectively). Additionally, for Junior vs. U-23, a significant difference was obtained in FTP/BW (*p* = 0.014; ES = 0.85).

**Table 5.** Estimated functional threshold power.


SD = standard deviation (±); FTP = functional threshold power; BW = body weight; Pmax = Maximal power output; \* = Significant differences with Youth group; † = Significant differences with the Junior group.

The FTP normalized to BW is a key factor in cycling, which is related to other performance parameters such as VO2max and power output in VO2max. Finally, in FTP/BW, a linear increase was found in relation to the age category (R<sup>2</sup> = 0.995; Figure 2). Additionally, the percentage of FTP with respect to the maximal power output (Pmax) showed a significant difference with the Youth group (Junior and U-23, *p* < 0.001; ES = 1.41 and 1.69, respectively), finding higher values in both groups (4% in Junior and 5% in U-23), but no differences were observed between the Junior and U-23 groups.

**Figure 2.** Estimated functional threshold power normalized to body weight. FTP = functional threshold power; BW = body weight; \* = Significant differences with the Youth group; † = Significant differences with the Junior group.

#### **4. Discussion**

The aim of the present study was to assess and compare the physiological profile of different age categories. Despite cardiorespiratory testing being the most frequent procedure to assess performance in cyclists regardless of the level of competition [37], this study is the first to directly compare the Youth, Junior and U-23 categories. The main findings indicated that, during a maximal test, Junior, and U-23 group obtained values of VO2max were slightly lower than those reported in elite and professional cyclists [1,2,37], but significantly greater than the Youth group. Similar differences were found for all performance variables analyzed in the maximal effort zone with important results in the ES analysis. These results were somehow expected due to the changes in physiological parameters with age and maturation, but could also be influenced by the athlete's training background.

Maximal values of VO2max and Pmax showed important differences with the Youth (VO2max = 8.2–10.2%; Pmax = 13.8–24.8% for Junior and U-23, respectively) and only for Pmax/BW were found differences between the Junior and U-23 (8.6% greater in the U-23 group). The VO2max data obtained by the Junior and U-23 groups were similar to the values reported in professional cyclists [1,2]. However, in recent years, relative power production has proven to be a more sensitive indicator, since in professional categories, this parameter allows for better differentiating performance levels when compared to the VO2max [4,5]. Along these lines, the present results indicated that the U-23 group outperformed the Youth (+19.0%) and the Junior (+8.6%) categories. For this reason, maximum Load/BW could be an important indicator of the competitive level in the U-23 category.

The FTP was at ~70% of Pmax with differences with the Youth group (4% in Junior and 5% in U-23). Interestingly, great differences between groups were found for Load/BW and FTP/BW, with a linear increase from Youth (19% and 14%, respectively, for Junior) to the U-23 category (25% in both for U-23). These parameters (Load/BW and FTP/BW) have been proposed to be very important for cycling performance [6–8,38,39]. Due to the duration of the stages, time under muscle tension is usually large, potentially explaining why power output normalized to BW is crucial for road cyclists. From an applied perspective, FTP/BW could be used at the beginning of the season to determine performance levels and compare them with the reference values of each category. Of note, the FTP assessments

were calculated indirectly in our study using the equation proposed by Denham et al. [34], where there were similar values were obtained with direct assessments by the U-23 group in comparison with previously reported values for professional cyclists [3], which supports the notion that the athletes in the studied sample were of high competitive level. It is likely that the FTP could be the most differentiating variable, showing a large and very large ES favoring the U-23 vs. the Junior and Youth, respectively.

Regarding VT1, similarities were found between the Junior and U-23 cyclists and both groups presented greater values than the Youth (especially for Load variables with ~13% in Junior and ~16% in U-23). According to Lucia et al. [1], it is important to achieve a good "cruising speed" in this metabolic zone, because it is the predominant intensity during flat stages. The differences reported herein could be conceivably explained by the competition characteristics in the Youth categories, which are usually comprised of shorter stages. For this reason, the lower intensity profile could be optimized in Junior and U-23 and, hence, closer to the values found in professional and elite cyclists [1,2].

In the work load at VT2, similar differences to those obtained for VT1 between age categories were found, but the values reported for U-23 were clearly lower than for professional cyclists [3]. Although there were no differences between age categories in the VT2 position with respect to VO2max, the workload developed in this metabolic zone is crucial to determine the aerobic capacity, which characterizes the professional cyclists [3,39]. Therefore, from an applied perspective, developing the aerobic capacity in younger categories should be an important objective.

Finally, when analyzing the Fatmax zone, similar results were displayed by all age groups with only small differences found between the U-23 and Youth groups for VO<sup>2</sup> and Load. Notably, these differences were not found for the same parameters when the values were normalized to BW (VO2R and Load/BW), which is in line with previous findings [23,24] and had not been reported for either differences in economy and efficiency when amateur and professional cyclist were compared [17]. Based on the present results, coaches should be aware that Fatmax does not seem to be a key factor discriminating the performance level in cyclists, although it could be important in long-term modalities as demonstrated in Ironman triathletes [22].

The workload was found to be the main difference in both thresholds (VT1 and VT2) with respect to the Youth group, as displayed by the large ES. Moreover, workload seems to be the main performance determinant in both maximum and submaximal zones with respect to the Youth group. These results are supported by the large ES obtained. However, when comparing the Junior and U-23, these differences were less pronounced and are only manifested in FTP/BW and maximal Load/BW with moderate ES. Practitioners should be aware of these findings when managing workload and monitoring training through power output zones.

The main limitation of the study was the reduced number of participants. Moreover, the fact that no previous investigations have compared, among the same age categories, the physiological parameters analyzed herein limited the discussion of the findings. Future studies with longitudinal research designs comparing the evolution of the same cyclists during their career would be interesting to conduct.

#### **5. Conclusions**

The main findings in this study showed enough differences with the Youth group and minor changes in the Junior vs. U-23 group. These results suggest that the main ladder is from the Youth to Junior age category. Due to the minor differences obtained between the Junior and U-23 categories, it could be intuited that the physiological profile in the Junior stage could be predictors of performance in absolute categories. Additionally, FTP/BW showed clear differences between each age category and testing it could be a good method to determine the cycling potential for cyclists.

**Author Contributions:** Conceptualization, C.M.-P. and S.D.; Methodology, C.M.-P.; Formal analysis, C.M.-P., T.T.F. and P.E.A.; Investigation, C.M.-P.; Resources, C.M.-P. and P.E.A.; Data curation, C.M.-P., S.D., T.T.F. and P.E.A.; Writing—original draft preparation, C.M.-P.; Writing—review and editing, T.T.F., S.D. and P.E.A.; Visualization, C.M.-P.; Supervision, P.E.A.; Project administration, C.M.-P.; Funding acquisition, P.E.A. 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 was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of Catholic University of Murcia (protocol code CE022105, 26 February 2021).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** The original data report is available to reviewers by contacting the corresponding author.

**Acknowledgments:** We wish to thank the cyclists for the availability to carry out this study.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

