In recent years, exercise-induced changes in the anabolic-catabolic hormonal balance and circulating inflammatory cytokines can be used by adolescent athletes and their coaches to optimize training (4). Interestingly, exercise may lead to a simultaneous increase of antagonistic mediators, and stimulate both anabolic components of the growth hormone (GH) → insulin-like growth factor-I (IGF-I) axis (5,9), and catabolic proinflammatory cytokines such as Interlukin-6 (IL-6), IL-1, and tumor necrosis factor-α (11,13,14). The very fine balance between the exercise-associated anabolic and inflammatory/catabolic response will dictate training effectiveness and the health implications of exercise. Dominance of the anabolic response will probably lead ultimately to increased muscle mass and improved fitness. In contrast, prolonged catabolic response dominance, in particularly if combined with inadequate nutrition, may lead to overtraining.
The hormonal response to a single exercise bout was previously determined (6,16). However, whether prolonged training changes the anabolic/catabolic response to a single practice in adolescent athletes is unknown. This has important implication for training of young athletes because puberty itself is characterized by rapid linear and muscle mass growth, and by spontaneous spurt of anabolic hormones. Therefore, the aim of this study was to examine the effect of prolonged training on hormonal and inflammatory response to a single volleyball practice in elite female adolescent players. We hypothesized that training will increase anabolic and reduce catabolic/inflammatory response to a single practice.
Experimental Approach to the Problem
We determined the effect of prolonged training on hormonal and inflammatory responses to a single typical volleyball practice. Thirteen healthy, female members of the Israeli National Academy for Gifted Athletes and the Israeli national female junior volleyball team participated in the study. We chose adolescent female athletes because the anabolic/inflammatory response to exercise is much less studied among this population. Volleyball was chosen because it is a very popular team sport for both genders and involves both power and aerobic and anaerobic properties.
The participants trained 18–22 h·wk−1. Training involved tactic and technical drills emphasizing volleyball skills and team strategies (∼20% of the time), power, and speed drills with and without the ball (∼25% of the time), and interval sessions (∼25% of the time). About 15% of the time consisted of endurance-type training (i.e., long-distance running). The additional 15% of the time consisted of resistance training using mainly circuit training with free weights at 65–75% of 1RM. To achieve greater training responses, the study was performed during the early phase (first 7 weeks) of the volleyball season.
Before and after the 7 weeks of training, each participant performed a typical 1-hour morning (i.e., 7–8 AM, after 8 hours of sleep) volleyball practice at fasting state (water was given ad libitum during practice to avoid dehydration). Training consisted of 20 minutes dynamic warm-up that included jogging, stretching, and running drills at submaximal speed (up to 80% of maximal speed), and additional 20 minutes of volleyball drills. The main part of the practice included 7 repetitions of 7 consecutive sprints from the back of the volleyball court to the net, maximal jump, and a hit of the volleyball over the net in the end of each sprint. Each repetition lasted about 1.5 minutes with 1 minute of rest to collect the balls between repetitions. To ensure similar practice intensity, before and after training, we used the exact same training protocol, monitored heart rate, and measured lactate levels. The participants did not train during the day before the study.
Fitness improvement was determined by the evaluation of power (vertical jump), anaerobic properties (the Wingate Anaerobic Test [WAnT]) and predicted V[Combining Dot Above]O2max (by the 20-m shuttle run) at the beginning and the end of the training intervention.
Blood samples were collected before and immediately after the volleyball practice, before, and after the training intervention. Assessment of anabolic hormones included GH, IGF-I, and IGF-binding protein-3 (IGFBP-3) measurements. Catabolic and inflammatory assessment included cortisol and IL-6 measurements. In addition, we determined lactate levels, commonly used markers of training intensity.
Thirteen healthy, female, elite, national team level, Israeli junior volleyball players (age 16.0 ± 1.4 years, Tanner stage for pubic hair 4–5) participated and completed the study. All the participants played in the Israeli premier junior volleyball league and were members of the Israeli National Academy for Gifted Athletes and the Israeli national junior volleyball team. All the participants lived in the academy dormitories during the intervention. The athletes were exposed to the same training and sleep regimens (i.e., 8 sleeping hours per night) and were all exposed to similar nutritional conditions (i.e., all meals were served at the Wingate institute dining room). All the participants completed their training program and the preintervention and postintervention evaluation. The study was approved by the Institutional Review Board and all parents and participants signed an inform consent prior to participation.
The study was performed during the early phase (first 7 weeks) of the volleyball season. The participants trained 18–22 h·wk−1. A typical, 1 hour, morning volleyball practice was performed before and after the training intervention (for a more detailed description of the training regimen during the study and the single volleyball practice, see the Experimental Approach to the Problem section).
A standard calibrated scale and stadiometer were used to determine the height and body mass. Skinfold measurements at 2 sites (triceps and subscapular) were used to calculate the percent body fat using standard equations (18). Each measurement was performed in triplicate, and the average was taken for the analysis.
All fitness measurements were performed before and at the end of the intervention. Because volleyball training includes power, strength, and anaerobic and aerobic fitness characteristics, all these components were assessed in this study.
Vertical Jump Test
Vertical jump height was measured by maximal vertical jump using a free countermovement jump technique (FCMJ). The participants began in the erect standing position, moved into a semisquat position (90° at the knee joint) before jumping, and touched the wall with their erected arm when they reached maximal height. Three trials were completed with a 1-minute rest between trials, with the participants using a vigorous double-arm swing as they jumped vertically. The highest FCMJ height achieved was recorded.
The Wingate Anaerobic Test
Anaerobic work responses were obtained using a Monark 834k cycle ergometer (Monark, Stockholm, Sweden). Seat height was adjusted to each participant's satisfaction, and toe clips with straps were used to prevent the feet from slipping off the pedals. During the warm-up, the participants pedaled at a constant pace of 60 rpm for 5 minutes against a light load of 1 kg. This was followed with 2 run-up practices of 3 seconds, during which the actual test load was imposed to accustom the participants to the resistance. For the actual test, each participant cycled as fast as possible for 30 seconds against constant resistance of 0.075 kg per each participant's kilogram of body weight. Before the test, the participants were instructed to pedal as fast as possible throughout the 30-second test period. The participants were also verbally encouraged during the test to maintain their maximum pedal rate.
The WAnT measured the peak power (PP) output, the mean power (MP) output, and the fatigue index (FI). All power output measurements were based on 5-second averages calculated by the WAnT computer software, and reported in watts per kilogram. The PP output was calculated from the highest 5-second work output. The MP output was calculated as the MP output throughout the 30 seconds of the test. The FI was calculated as the percentage of power output drop throughout the test from the maximal power output (1).
Aerobic Power Test
Twenty-Meter Shuttle Run Test
The 20-m shuttle run test is a field test that predicts aerobic fitness (V[Combining Dot Above]O2 max) and has been shown to be a reliable and valid indicator (2) of aerobic power in various populations (19). The test consisted of shuttle running at increasing speeds between 2 markers placed 20 m apart. A portable compact disc (Sony CFD-V7, Tokyo, Japan) dictated the pace of the test by emitting tones at appropriate intervals. The participants were required to be at one of the ends of the 20-m course at the signal. A start speed of 8.5 km·h−1 was maintained for 1 minute, and thereafter, the speed was increased by 0.5 km·h−1 every minute. The test score achieved was the number of 20-m laps completed before the subject either withdrew voluntarily from the test or failed to arrive within 3 m of the end line on 2 consecutive tones. The V[Combining Dot Above]O2 was derived by the formula: Y = 6.0X − 24.4, where y equals the predicted V[Combining Dot Above]O2 max and x equals the maximum speed achieved.
Blood Sampling and Analysis
Fasting, early morning, prepractice, and postpractice blood samples were collected before and at the end of the intervention. Water was given ad libitum during practice to avoid dehydration. Blood samples were immediately spun at 3,000 rpm, at 4° C for 20 minutes. Serum was separated and stored at −80° C. All preexercise and postexercise specimens from each individual were analyzed in the same batch by an experienced technician who was blinded to the order of samples (pretraining vs. posttraining program, prepractice vs. postpractice).
The GH serum concentrations were determined by an enzyme-linked immunosorbent assay (ELISA) with the use of the DSL-10-1900 Active kit (Diagnostic System Laboratories, Webster, TX, USA). Intraassay coefficient of variation (CV) was 3.3–4.5%, interassay CV was 5.5–12.9%, and the sensitivity was 0.03 ng·ml−1.
Insulin-Like Growth Factor-I
The IGF-I was extracted from IGFBPs using the acid-ethanol extraction method. Serum IGF-I concentrations were determined by a 2-site immunoradiometric assay using the DSL-5600 Active kit (Diagnostic System Laboratories). IGF-I intraassay CV was 1.5–3.4%, and the interassay CV was 3.7–8.2%. Assay sensitivity was 0.8 ng·ml−1.
Insulin-Like Growth Factor-I–Binding Protein-3
The IGFBP-3 serum concentrations were determined by an ELISA with the use of the DSL-10-6600 Active kit (Diagnostic System Laboratories). The intraassay CV was 7.3–9.6%, interassay CV was 8.2–11.4%, and the sensitivity was 0.04 ng·ml−1.
Serum lactate was measured spectrophotometrically (YSI 1500, Yellow Springs, OH, USA). Intraassay CV was 2.8%, interassay CV was 3.5%, and the sensitivity was 0.2 mmol·L−1.
Serum cortisol levels were determined by a commercial radioimmunoassay (Diagnostic Products Corporation, Los Angeles, CA, USA). The intraassay and interassay CV for this assay were 3.2 and 6.8%, respectively.
Inflammatory mediators were analyzed by means of the ELISA, using the R&D system Quantikine High Sensitivity commercial kits (R&D system; Minneapolis, MN, USA). Interleukin-6: Intraassay CV was 3.8–11.1%, interassay CV was 7.1–29.5%, and the sensitivity was 0.009 pg·ml−1. Interleukin-1 receptor antagonist: Intraassay CV was 3.1–6.2%, interassay CV was 4.4–6.7%, and the sensitivity was 22 pg·ml−1.
Sample size calculation for this study was based on our previously reported changes in the hormonal response to exercise (6). When using the change in IL-6, with a 2-sided, 0.05 significance level (α = 0.05), a sample size of 7 participants was needed to detect a significant difference at a 90% power. Because of the complexity of measurements before and after a training intervention, and a possibility of dropout, 13 participants were included in the study. A 2-way repeated measure analysis of variance (with Bonferroni post hoc test) was used to compare the effect of training on exercise practice associated changes. Statistical significance was set at p ≤ 0.05. Data presented as mean ± SD.
Anthropometric and fitness characteristics of the study participants at the beginning and the end of the training program are summarized in Table 1. Training led to a significant improvement in the vertical jump, anaerobic properties (mean and peak anaerobic power), and predicted V[Combining Dot Above]O2max (Table 1).
The anabolic/catabolic hormonal and inflammatory mediator's response to the single volleyball practice at the beginning and at the end of the training program is summarized in Table 2 and Figure 1. Volleyball practice, both before and after the training intervention, was associated with a significant increase of serum lactate, GH, and IL-6 levels. The cortisol and the IL-6 responses to the same relative intensity volleyball practice were significantly reduced after, compared with before, the training intervention (Table 2, Figure 1).
We studied the effect of training on hormonal and inflammatory response to a single volleyball practice in elite, adolescent, female volleyball players. Training during the initial phases of the volleyball training season was associated with a significant improvement of both vertical jump, anaerobic capacity (i.e., peak and mean anaerobic power), and aerobic properties (i.e., predicted V[Combining Dot Above]O2 max based on the 20-m shuttle run test). Before the training intervention, a single, typical, volleyball practice was associated with a significant increase of lactate, the anabolic hormone GH, and the proinflammatory marker IL-6. Training led to a significantly reduced cortisol and IL-6 response to the same relative intensity volleyball practice, suggesting that training reduces the catabolic response to a single volleyball practice.
The effect of a single exercise and exercise training on anabolic/catabolic hormones and inflammatory cytokines was studied mainly in adult athletes and in individualized endurance-type sports. Therefore, we studied adolescent athletes participating in team sports, and focused on elite volleyball players, because volleyball is a very popular team sport for both genders during adolescence and it involves both power and anaerobic and aerobic properties. In addition, we studied female volleyball players because the anabolic and inflammatory response to exercise is much less studied among this population. We were encouraged that power and anaerobic and aerobic fitness characteristics were significantly improved by training.
When assessing the effect of training on hormonal and inflammatory response to a single practice, it is important to assure that any difference would not be attributed to a lesser magnitude of exercise intensity because of improved fitness. This is important because when exercise is performed above the lactic anaerobic threshold, relatively small changes in the exercise input may lead to a significantly greater response of hormones such as GH and inflammatory mediators (7). The similar peak exercise heart rate (180.5 ± 10.3 vs. 182.6 ± 8.8 before and after the training intervention, respectively), and the similar exercise-associated changes in serum lactate (reaching lactate levels that are commonly seen in a typical volleyball practice), indicate that we achieved similar metabolic and cardiovascular responses and relative intensity in the volleyball practice before and after training. Moreover, to avoid any influence of diurnal variation, hydration, nutrition, and sleep patterns on hormonal status, we collected early morning blood samples prepractice and postpractice, before and after the training intervention, after overnight fast (water was given ad libitum during practice to avoid dehydration), and after 8 hours of sleep.
We previously reported increases in GH and IL-6 after a single typical volleyball practice in the elite male adolescent volleyball players (6). We suggested that changes in GH may indicate exercise-related anabolic adaptations, and that increases of IL-6 may indicate its important role in microtraumatic muscle tissue damage repair after the volleyball training. Furthermore, we recommend that changes in the anabolic-catabolic-inflammatory hormonal balance may be used by athletes and their supporting coaching team to gauge training intensity, not only in individualized sports, but also in team sports such as volleyball.
The main contribution of this study is that after 7 weeks of training during the initial phases of the volleyball season, we found a significantly reduced cortisol and IL-6 in response to the same relative intensity volleyball practice. Overall, this suggests that in addition to the training-related improvement in power and anaerobic and aerobic properties in adolescent volleyball players, part of the training adaptation includes a reduced catabolic and inflammatory response to a single practice.
Exercise-induced cortisol increase depends on the duration and the intensity of the physical activity. A significant increase in cortisol levels requires duration of exercise of at least 20 minutes and an intensity of at least 60% of the maximal oxygen consumption (22). Cortisol levels were also found to be increased in fighting sports during competition and were higher among the winners compared with among the losers, reflecting probably greater physiological and psychological stress (8,17). It should be noted that before the training intervention, the volleyball practice was associated with a nonsignificant increase in cortisol levels. This increase occurred despite cortisol's diurnal circadian rhythm, which is associated with a decrease in cortisol level throughout the day, suggesting probably an even higher increase in cortisol level. Only after the training intervention, a decrease in the cortisol level was found after practice, suggesting reduced stressful/catabolic-like response to a similar intensity volleyball practice.
Interestingly, training had no effect on the anabolic GH response to the single volleyball practice. This may be related to the timing of blood sampling. Previous studies indicated that the exercise-induced GH peak occurs 25–35 minutes after the start of exercise irrespective of the exercise duration (3,11). Because blood samples were collected in this study only before and at the end of practice (1 hour), and not 25–30 minutes after the beginning of exercise, it is possible that effects of training on the exercise-related GH peak might have been missed. Thus, in future research, multiple hormonal/inflammatory measurements should be considered.
The volleyball practice, both before and after training, had no significant effect on IGF-I and IGFBP-3 levels. Previous reports suggested that very short supramaximal exercise efforts (e.g., 90 seconds) were associated with increases in IGF-I levels (21), and that intense sprint interval training increased IGFBP-3 levels (10,12). Therefore, it is possible that the present volleyball practice was not intense enough to increase IGF-I levels.
The IL-6 increase after the single practice was significantly reduced after training. The major source for the exercise-related IL-6 increase is the skeletal muscle (15). However, IL-6 increases during both exercises with and without evidence of muscle damage. It is believed that IL-6 plays a key mediatory role in the inflammatory response needed for exercise-associated muscle damage repair (20). It is possible that frequent jumping and ball hitting and digging during a typical volleyball practice were associated with subclinical muscular and soft tissue damage that triggered a significant increase in circulating IL-6 levels. It is also possible that despite the similar practice intensity before and after training, tissue damage was reduced during the single practice after training, resulting in significantly reduced need for IL-6 increase.
Volleyball training during the initial phases of the volleyball season is associated with significant improvement of power, anaerobic and aerobic fitness.
Training-related improvement in fitness was associated also with significantly reduced cortisol and IL-6 responses to a single practice, suggesting that part of the adaptation to training is that a single practice becomes less catabolic and less inflammatory during initial phases of the training season.
Changes in the anabolic-catabolic-inflammatory hormonal balance can be used by athletes and their coaching staff to determine the training intensity also in team sports like volleyball. It is clear that these mediators cannot be used as markers in every practice, unless future techniques will afford instant results (like the current ability to assess lactate levels). However, responses of these hormones can be used occasionally in different team sports, key training sessions, or training camps, or before main tournaments, as an objective, quantitative tool to monitor training load and to better plan training cycles throughout a competitive season.
Whether training will have similar effects during longer training periods, periods of greater training intensity, different phases of the season or during competition periods, needs further research.
1. Bar-Or O. The Wingate anaerobic test. An update on methodology, reliability and validity. Sports Med 4: 381–394, 1987.
2. Castro-Pinero J, Artero EG, Espana-Romero V, Ortega FB, Sjostrom M, Suni J, Ruiz JR. Criterion-related validity of field-based fitness tests in youth: A systematic review. Br J Sports Med 2009.
3. Eliakim A, Nemet D. Exercise
provocation test for growth hormone secretion: Methodologic considerations. Pediatr Exerc Sci 20: 370–378, 2008.
4. Eliakim A, Nemet D. Exercise
training, physical fitness and the growth hormone-insulin-like growth factor-1 axis and cytokine balance. Med Sport Sci 55: 128–140, 2010.
5. Eliakim A, Nemet D, Cooper DM. Exercise
, training and the GH → IGF-I axis. In: The Endocrine System in Sports and Exercise
. Kraemer W.J., Rogol A.D., eds. Oxford, UK: Wiley-Blackwell, 2005. pp. 165–179.
6. Eliakim A, Portal S, Zadik Z, Rabinowitz J, dler-Portal D, Cooper DM, Zaldivar F, Nemet D. The effect of a volleyball practice on anabolic hormones and inflammatory markers in elite male and female adolescent players. J Strength Cond Res 23: 1553–1559, 2009.
7. Felsing NE, Brasel J, Cooper DM. Effect of low-and high-intensity exercise
on circulating growth hormone in men. J Clin Endocrinol Metab 75: 157–162, 1992.
8. Filaire E, Sagnol M, Ferrand C, Maso F, Lac G. Psychophysiological stress in judo athletes during competitions. J Sports Med Phys Fitness 41: 263–268, 2001.
9. Meckel Y, Eliakim A, Seraev M, Zaldivar F, Cooper DM, Sagiv M, Nemet D. The effect of a brief sprint interval exercise
on growth factors and inflammatory mediators. J Strength Cond Res 23: 225–230, 2009.
10. Meckel Y, Nemet D, Bar-Sela S, Radom-Aizik S, Cooper DM, Sagiv M, Eliakim A. Hormonal and inflammatory responses to different types of sprint interval training. J Strength Cond Res 25: 2161–2169, 2011.
11. Nemet D, Eliakim A. Growth hormone-insulin-like growth factor-1 and inflammatory response to a single exercise
bout in children and adolescents
. Med Sport Sci 55: 141–155, 2010.
12. Nemet D, Meckel Y, Bar-Sela S, Zaldivar F, Cooper DM, Eliakim A. Effect of local cold-pack application on systemic anabolic and inflammatory response to sprint-interval training: A prospective comparative trial. Eur J Appl Physiol 107: 411–417, 2009.
13. Nemet D, Oh Y, Kim HS, Hill M, Cooper DM. Effect of intense exercise
on inflammatory cytokines
and growth mediators in adolescent boys. Pediatrics 110: 681–689, 2002.
14. Nemet D, Rose-Gottron CM, Mills PJ, Cooper DM. Effect of water polo practice on cytokines
, growth mediators, and leukocytes in girls. Med Sci Sports Exerc 35: 356–363, 2003.
15. Pedersen BK, Steensberg A, Fischer C, Keller C, Ostrowski K, Schjerling P. Exercise
with particular focus on muscle-derived IL-6. Exerc Immunol Rev 7: 18–31, 2001.
16. Pilz-Burstein R, Ashkenazi Y, Yaakobovitz Y, Cohen Y, Zigel L, Nemet D, Shamash N, Eliakim A. Hormonal response to Taekwondo fighting simulation in elite adolescent athletes. Eur J Appl Physiol 110: 1283–1290, 2010.
17. Salvadora A, Suay F, Martinez-Sanchis S, Simon VM, Brain PF. Correlating testosterone and fighting in male participants in judo contests. Physiol Behav 68: 205–209, 1999.
18. Slaughter MH, Lohman TG, Boileau RA, Horswill CA, Stillman RJ, Van Loan MD, Bemben DA. Skinfold equations for estimation of body fatness in children and youth. Hum Biol 60: 709–723, 1988.
19. St Clair GA, Broomhead S, Lambert MI, Hawley JA. Prediction of maximal oxygen uptake from a 20-m shuttle run as measured directly in runners and squash players. J Sports Sci 16: 331–335, 1998.
20. Steensberg A, Keller C, Starkie RL, Osada T, Febbraio MA, Pedersen BK. IL-6 and TNF-alpha expression in, and release from, contracting human skeletal muscle. Am J Physiol Endocrinol Metab 283: E1272–E1278, 2002.
21. Stokes K, Nevill M, Frystyk J, Lakomy H, Hall G. Human growth hormone responses to repeated bouts of sprint exercise
with different recovery periods between bouts. J Appl Physiol 99: 1254–1261, 2005.
22. Urhausen A, Kindermann W. The endocrine system in overtraining. In: Sports Endocrinology. Warren M.P., Constantini N.W., eds. New Jersey, NY: Humana Press, 2000. pp. 347–370.