Anabolic/Catabolic Hormone Imbalance but Still Jumping Further? Negative Association of Free Testosterone With Jumping Performance in Elite Handball Players Following a Preparatory Period

ABSTRACT

Purpose: The present study investigated the effects of a 10-week preparatory training period on biomarkers and jumping performance and associations of changes in biomarkers, load, and jumping performance from the beginning (PRE) to the end of the preparatory period (POST) in elite handball players. Methods: Seventeen elite handball players competing in the first Slovenian men’s League were recruited. Training, competition and academic loads were reported weekly, while biomarkers and jumping performance were assessed at PRE and POST. Results: At POST, decreased levels of free testosterone (large effect size [ES] = -1.69, p < .001) and free testosterone to cortisol ratio [FTCR] (large ES = −.95, p = .004) were observed; whereas, better performance on the single leg lateral hop test [SLLH] (large ES = .85, p = .007) and single leg triple hop test [SLTH] (large ES = 1.05, p = .002) were observed compared to PRE. Furthermore, changes in FTCR correlated with changes in cortisol (high r = -.751, p = .001), SLLH (moderate r = -.603, p = .022), and SLTH (moderate r = -.643, p = .013), while changes in free testosterone correlated with SLTH (moderate r = -.645, p = .013). Conclusions: High intensity trainings with a saturated competition schedule can result in disturbed anabolic/catabolic hormone ratio observed through FTCR decrease, which could indicate either an optimal state or early exhaustiveness. It seems that SLLH and SLTH are more sensitive to changes in biomarkers than a single leg hop test. Sport professionals may use the results for individualized monitoring of an athlete’s health and performance, specifically, as an aid for adjusting training loads accordingly to prevent performance declines and potential injury/illness events.

KEYWORDS:

• Athlete
• biomarkers
• free testosterone to cortisol ratio
• single leg hop test

Handball is a contact team sport, characterized by high intensity movement patterns, such as sprinting, accelerating, decelerating and jumping, all of which place great physiological strain on players. The handball playing season in elite sport usually lasts between 44 and 46 weeks (from July/August until June) and consists of two preparatory and competition periods with a short transition period in between, which is considered a “double periodization.”

Training periodization has traditionally been considered as a systemic planning of short-term and long-term training programs from the physical preparation aspect (Inigo Mujika et al., 2018). Recently, a new term—“integrated periodization”—has been introduced in the sport-science community. Integrated periodization includes multiple components, such as strength and conditioning training, skill acquisition, recovery, nutrition, and psychological skill into an athlete’s training, all with the goal of enhancing the player’s game-specific performance. One of the ever-emerging challenges for sport professionals is to plan and execute a training program with an optimal load to maximize the performance at the desired peak point (major competition) while minimizing the risk of nonoptimal adaptation (so-called overreaching) and potential injury/illness (Kuipers, 1996; Schwellnus et al., 2016). To achieve peak performance, coaches usually manipulate training load and training intensity, while alternating between phases of increased and reduced training loads. Typically those include the phases of high training volume and/or high training intensity and progression from training variation toward training specificity (Kiely, 2012; Matveyev, 1981). The phases of intensive training can result in acute physiological effects that might momentarily limit performance capacity but can later lead to performance enhancement throughout supercompensation phenomenon (Inigo Mujika et al., 2018). On the other hand, if the load is exceeding the athlete’s capacity to adapt, or if it’s applied through a longer period, it can have detrimental effects on the athlete’s performance. Handball athletes are required to perform consistently through several months of league competitions (Clemente et al., 2019) and on top, to peak for major national or international tournaments; therefore, proper periodization is challenging.

Physical performance can be measured objectively with the use of different laboratory and field tests (Thorpe et al., 2017). However, those tests are lacking sensitivity to indicate the performance decline that is yet to happen. One potential indicator of performance levels could be biomarkers; however, the literature on this is inconclusive. In the realm of athletic performance, the anabolic and catabolic hormones play a crucial role in shaping an athlete’s physiological response to training stimuli. Cortisol, often referred to as the “stress hormone,” is associated with catabolic effects, promoting tissue breakdown and potentially impairing muscle function when elevated chronically. Conversely, testosterone is recognized as a key anabolic hormone (Lac & Maso, 2004), which fosters muscle growth, strength development, and overall athletic performance. Research suggests testosterone as an indicator of acute and chronic changes in neuromuscular capacity for explosive performance (Crewther et al., 2011); therefore, its values could explain the variation in physical performance. Free or total testosterone, together with cortisol, a well-known marker of stress, forms a (free) testosterone to cortisol ratio. The ratio was proposed as an anabolic/catabolic index (Hoogeveen & Zonderland, 1996), denoting tapering off when slightly decreased and overtraining when dropped by more than 30% from baseline values (Adlercreutz et al., 1986; Vervoorn et al., 1991). The aforementioned ratio was proposed to positively correlate with fatigue (Andrzejewski et al., 2021) and performance measures (Häkkinen et al., 1985; Mujika et al., 1996); however, the evidence is conflicting (Filaire et al., 2001; Foretic et al., 2020; Hooper et al., 1999).

Understanding the complex relationship between these hormonal changes and athletic performance is particularly relevant in sports characterized by explosive movements and rapid changes of direction, such as handball. Handball demands a combination of strength, power, speed, agility, and endurance, making it imperative for athletes to optimize their lower body capabilities, including jumping performance, which represents a cornerstone for success (Karcher & Buchheit, 2014; Mohoric et al., 2022; Wagner et al., 2014). Single-legged forward and lateral jumps are vital in handball training due to their direct relevance to the sport’s biomechanical demands (Karcher & Buchheit, 2014; Wagner et al., 2018). These exercises replicate the dynamic movements of a handball game, requiring athletes to generate explosive power from a single leg while moving forward, upward or laterally, both in defensive and offensive actions.

Exploring the relationship between anabolic and catabolic hormones and jump performance has significant implications for tailoring training strategies to meet the specific needs of handball players. By understanding the connection between hormones and jump performance, coaches and sport scientists can utilize either one or both methods for assessing athlete’s abilities, injury risk, and performance and to subsequently apply interventions.

The purpose of the present study was to investigate (a) the cumulative effects of a 10-week preparatory training period on free testosterone, cortisol, free testosterone to cortisol ratio, and jumping performance of elite handball players; (b) the associations between changes in free testosterone, cortisol, free testosterone to cortisol ratio, and jumping performance from the beginning of the preparatory period (PRE) to the end of the preparatory period (POST); (c) associations between cumulative loads and changes in biomarkers and jumping performance from PRE to POST.

Materials and methods

Experimental approach to the problem

A prospective observational study was conducted to investigate the changes in selected biomarkers and jumping performance measures due to accumulated load during a 10-week preparatory period between July and September 2022 in elite male handball players. Load-related variables were determined for different domains: (a) training load, (b) competition load, (c) academic load (lectures, exams, practical courses, and study hours), and (d) cumulative load (sum of training, competition, and academic load) reported weekly by the assistant coach and the athletes. This period was chosen due to its highest accumulated load in professional handball team, encompassing two mesocycles wherein general and specific handball conditioning were addressed. A detailed description of the preseason’s training plan is provided below in the section titled “Training description.” Blood biomarkers and jumping performance were assessed at PRE and POST to investigate the effect of this period on athlete’s readiness to perform, accumulated fatigue, and health in general.

Subjects

Seventeen elite male handball players (age: 22.9 ± 3.4 years, body height: 192.9 ± 7.6 cm, body mass 96.7 ± 13.7 kg, body mass index: 25.9 ± 2.4 kg/m²) from a single club, competing in the First Slovenian Handball League (NLB) and the European Handball Federation (EHF) Champions League in the 2022/23 season. Players have on average 12.6 ± 2.8 years playing experience in the elite competitions. Athletes were asked to abstain from alcohol and/or caffeine-based beverage consumption and to avoid strenuous workouts for at least 48 hours before testing days. Before the actual study begun, an introductory meeting was held to familiarize all participants with the study protocol and testing procedures. All subjects were informed about the benefits and potential risks of the study and gave written informed consent to participate in the investigation. All the procedures were carried out in accordance with the ethical standards of the 1964 Declaration of Helsinki and were approved by the Slovenian National Medical Ethics Committee, Ministry of Health (Ljubljana, Slovenia; number: 0120–109/2022/3). The experimental protocol was registered on ClinicalTrials.gov, Identifier: NCT05471297.

Training description

The preparatory period lasted 10 weeks and was divided into two parts. For the first four weeks, individualized strength and conditioning training plans were provided to players based on their needs. The emphasis of the programs was on maximal strength, muscle mass, and general aerobic endurance development. Within this period, the players performed on average 24 exercise sessions in the strength/endurance ratio 70/30. The main part of the preparation period lasted for 6 weeks and was divided on two 3-week long mesocycles. During the first mesocycle, the main emphasis was on maximal strength, power, speed, and specific aerobic-anaerobic endurance development. The second mesocycle was dedicated to the development of playing position specific maximal strength, power, speed, and specific aerobic-anaerobic endurance. In the second part of the preparation period, the team in total performed 26 handball exercise sessions (17 technical-tactical exercise sessions and nine handball-specific conditioning exercise sessions) and 25 strength and conditioning exercise sessions (maximal strength/power/speed: 13 exercise sessions; specific aerobic-anaerobic endurance: 6 exercise sessions; recovery and injury prevention: 6 exercise sessions) and played nine preparation/non-official matches.

Procedures

Jumping performance testing

The single leg hop test for distance was performed as follows: The tested leg was fully extended with the great toe on the specified starting line. The alternate leg was flexed at the hip and knee joints to 90 degrees. The subjects were then directed to make a countermovement to a self-selected depth, to jump as far forward as they could, and to land on the tested leg without losing the balance. On the single leg triple hop test, athletes performed three consecutive maximal hops forward on the same leg. And finally, for the single leg lateral hop test, athletes were instructed to jump to the side of the standing leg as far as possible. An experienced researcher instructed the participants to try again after a minute of rest, if the jump did not follow these guidelines. All the jumps at both measurement points were performed in the same training hall on a handball parquet floor. The researcher measured the distance from the starting line to the point where the heel touched the ground upon completing the successful jump. All participants were allowed one to two practice trials and then completed up to three correct test trials with the dominant leg. The jump with the longest distance hopped was selected for further analysis.

Blood sample collection

Blood samples were collected at PRE and POST between 07:00 and 08:00 in the morning in the quiet room with optimal environmental temperature at the handball club facility. Athletes were instructed to report to club facility in a euhydrated condition, after they refrained from strenuous exercise on the previous day. Two blood samples were obtained (antecubital fossa, BD Vacutainer® SST™ II Advance Tubes) from the antecubital vein in the arm by an experienced medical nurse while the subjects were seated. Following collection, blood was centrifuged for 10 minutes at 1,500 × g rates per minute (Tehtnica, Centric 160). The samples were stored in special containers designed to maintain optimal temperature and transferred to a processing facility (Clinical Institute for Clinical Chemistry and Biochemistry, University Clinical Centre Ljubljana) for analysis. Biomarkers analyzed included free testosterone and cortisol. Cortisol in serum was measured by electrochemiluminescence assay (Cobas e411 analyzer, Roche Diagnostics, Mannheim, Germany); the limit of detection was 0.5 nmol/L. Free testosterone was calculated from testosterone, SHBG, and albumin using the Vermeulen equation (Vermeulen et al., 1999). For the measurement of serum testosterone and SHBG, an electrochemiluminescence assay was used (Cobas e411 analyzer, Roche Diagnostics, Mannheim, Germany); the limit of detection was 0.09 nmol/L and 0.35 nmol/L, respectively. Albumin in serum samples was measured spectrophotometricaly using bromcresol green (Alinity analyzer, Abbott Laboratories, Illinois, USA); the limit of detection was 10 g/L.

Statistical analysis

All statistical analyses were conducted with SPSS statistical software (version 27.0, IBM Inc., Chicago, USA). Data are presented as mean ± SD. Descriptive statistics were used to summarize the demographic characteristics of the subjects and outcomes of interest. Normality of the data distribution was confirmed by using the Shapiro-Wilk test. To investigate the changes from PRE to POST for all dependent variables a paired-samples t-test was used (Mishra et al., 2019). Additionally, Cohens’ d (ES) was used to assess the magnitude of change from PRE to POST and was interpreted as trivial: <0.20; small: 0.20–0.50; moderate: 0.50–0.80; or large: >0.80 (Cohen, 1988).

In addition, associations between changes in biomarkers and jumping performance and between cumulative loads from PRE to POST were examined using Pearson’s correlation coefficient. The following thresholds of the correlation coefficient were used to assess the magnitude of the associations analyzed: weak: ≤0.35; moderate: 0.36–0.67; and high: ≥0.68 (Taylor, 1990). Statistical significance was accepted at p ≤ .05 for all analysis.

Results

Initially, 17 athletes were enrolled in the study (PRE); of these, one athlete transferred to another club and two athletes could not attend the final measurements due to an injury. Consequently, 14 athletes were assessed at both periods (PRE and POST) and evaluated based on per protocol analysis.

During the preparatory period, athletes had on average 10 hours of training load per week. Athletes started with preparation matches in Week 4, resulting in their competition load of approximately 0.6 hours per week. Within a team of 17 athletes, five were pursuing a dual career, therefore, their average academic load was 0.5 hours per week.

Results shown in Table 1 indicate that the cumulative effects of 10 weeks’ preparatory training period had small to large effects on biomarkers and jumping performance of elite handball players. Decreased levels of free testosterone (large ES = −1.69, p < .001) (Figure 1a), free testosterone to cortisol ratio (large ES = −0.95, p = .004) and cortisol (small ES = −0.18, p = .503) concentrations; whereas, better performance on the single leg lateral hop test (large ES = 0.85, p = .007) and single leg triple hop test (large ES = 1.05, p = .002) (Figure 1b) were observed after 10 weeks of preparatory training period.

Figure 1. Graphical illustration of changes from the beginning of (PRE) to after (POST) the preparatory period in (a) free testosterone level (pmol/L) and (b) single leg triple hop test.

Table 1. Comparisons of biomarkers and jumping performance of elite handball players at the beginning of (PRE) and after (POST) the 10-week preparatory training period.

	PRE		POST
Blood derived biomarkers	Mean	SD	Mean	SD	Δ (%)	t test	p value		ES (95% CI)
Cortisol (nmol/L)	516.51	±96.70	496.25	±107.78	−3.92	0.684	0.506	small	−0.18	−0.35	0.71
Free testosterone (pmol/L)	51.60	±14.06	35.39	±12.64	−31.42	6.307	p < .001	large	−1.69	0.85	2.50
Free testosterone: cortisol ratio	0.1000	±0.0232	0.0721	±0.0236	−27.95	3.553	0.004	large	−0.95	0.30	1.57
Jumping performance
Single leg hop test (cm)	205.57	±13.89	208.07	±12.60	1.22	−2.110	0.055	moderate	0.56	−1.12	0.01
Single leg lateral hop test (cm)	209.29	±13.89	212.07	±13.22	1.33	−3.172	0.007	large	0.85	−1.45	−0.22
Single leg triple hop test (cm)	667.50	±64.17	680.07	±65.65	1.88	−3.935	0.002	large	1.05	−1.70	−0.38

Notes. Bold values = significant difference.

Considering associations between different measures of interest, the results showed that changes in free testosterone to cortisol ratio correlated with cortisol (high r = −0.751, p = .001), the single leg lateral hop test (moderate r = −0.603, p = .022), and the single leg triple hop test (moderate r = −0.643, p = .013), while changes in free testosterone correlated with the single leg triple hop test (moderate r = −0.645, p = .013). Changes in the single leg lateral hop test positively correlated with total training load (high r = 0.783, p = .001 (Table 2).

Table 2. Pearson’s product-moment correlation coefficient (r) between changes in biomarkers, jumping performance, and different type of loads of elite handball players from the beginning of (PRE) and after (POST) the 10-week preparatory training period.

	CORTISOL	FTCR	SLH	SLLH	SLTH	TTL (hr)	TCL (hr)	TAL (hr)	TOTAL LOAD (hr)
TESTOSTERONE	−0.148	.730^**	−0.503	−0.502	−.645^*	−0.389	0.095	0.217	0.186
FTCR	−.751^**		−0.245	−.603^*	−.643^*	−0.415	−0.003	0.088	0.001
SLH	−0.199			.535^*	0.425	0.503	−0.026	−0.255	−0.118
SLLH	0.382				.700^**	.783^**	−0.169	−0.100	0.198
SLTH	0.287					0.374	−0.363	0.215	0.265
TTL (hrs)	0.262						−0.233	−0.196	0.137
TCL (hrs)	0.134							−.757^**	−.636^*
TAL (hrs)	0.035								.867^**
TOTAL LOAD (hrs)	0.175								1

Notes. FTCR = free testosterone to cortisol ratio; SLH = single leg hop test; SLLH = single leg lateral hop test; SLTH = single leg triple hop test; TTL = total training load; TCL = total competition load; TAL = total academic load; bold values = significant correlation.

Discussion

Our study aimed to identify the link between free testosterone, cortisol, load and jumping performance in elite handball players. During a 10-week period, the team had two peaks of increased training load, followed by a training load decrease when the competition load increased. We found that after the preparatory period, both cortisol and free testosterone levels decreased, which resulted in a decreased free testosterone to cortisol ratio (−27.95%), just below the critical −30% threshold, previously proposed as an indicator of overtraining (Adlercreutz et al., 1986; Vervoorn et al., 1991). Even though several studies have failed to find such a decrease, they have been conducted on athletes competing in individual sports such as triathlon (Coutts et al., 2007), which is characterized by longer preparatory periods and less saturated competition schedules. According to the well-being continuum (Fry et al., 1991), we could suggest the athletes were in the “functional overreaching” zone, wherein the anabolic/catabolic hormone imbalance was observed for a shorter period of time, but the performance was enhancing. If this phase were to continue for too long, nonfunctional overreaching could occur, and performance decrease would be observed, together with hormone imbalance.

Our results showed a moderate negative correlation between free testosterone to cortisol ratio and the single leg lateral hop test/single leg triple hop test, suggesting that a decrease in free testosterone to cortisol ratio was associated with enhancement in the single leg lateral hop test performance. We also found a moderate correlation between free testosterone concentrations and the single leg triple hop test but no correlation with the single leg hop test. Therefore, it seems that the single leg lateral hop test and the single leg triple hop test are more sensitive to changes in free testosterone, cortisol, and free testosterone to cortisol ratio than the single leg hop test. While conventional knowledge might suggest a positive correlation between testosterone levels and athletic performance due to testosterone’s role in promoting muscle growth and strength development, our findings challenge this notion. Interesting results, showing that testosterone levels decreased, while jumping performance improved could be explained through various factors. Although testosterone was identified as a predictor of power-related performance evaluated by a countermovement jump and yo-yo intermittent recovery test in adolescent soccer and American football athletes (Gravina et al., 2008; Martin et al., 2019; Moore & Fry, 2007), a recent study utilizing lower and upper body strength and repeated sprint ability tests failed to confirm this correlation (Hecksteden et al., 2016). The contradictory results observed in the aforementioned studies can be attributed to high methodological heterogeneity due to the different populations studied (e.g., power vs. endurance vs. team sports athletes) and the variety of physical performance tests used. This was supported by several studies that found disrupted hypothalamic pituitary gonadal axis in highly aerobically trained male athletes (Hackney et al., 1988, 1998; MacConnie et al., 1986; Wheeler et al., 1984), resulting in reduced serum total testosterone and free testosterone (Wheeler et al., 1984). Athletes recruited for the current study started the preparatory period with an emphasis on resistance training, while gradually increasing the aerobic training load in the second half of the preparatory period, which probably caused free testosterone levels to decrease. On the other side, a phenomenon of enhanced jumping performance despite a free testosterone to cortisol ratio decrease can be explained with the specifics of a handball game that is predominantly characterized by high-intensity activities consisting of stretch and shortening cycle patterns—an essential part of plyometric exercise. The handball-specific conditioning has been shown to be an effective training regime for multifactorial enhancement of physical capabilities including jumping performance (Ramirez-Campillo et al., 2020). Thus, as the players moved from basic physical conditioning in the beginning of the preparatory period to performing more lower body plyometric drills toward the end of the preparatory period, better performance on the jumping tests could be observed. At the same time, free testosterone levels decreased as a part of accumulated training stress—that is, functional overreaching. Research has also showed that in addition to high-volume exercise, several other factors such as sleep deprivation, energy restriction, and psychological stress can contribute to reductions in serum total and free testosterone (Alemany et al., 2008; Opstad, 1992). Our results coincide with previous studies (Moore & Fry, 2007; Stone et al., 2019) in which reductions in testosterone were noted in Division I collegiate American Football players following a preparatory period.

It is likely that training, competition, and academic load, posing physical and psychological stress to the athletes, resulted in the decreased anabolic hormone concentrations. Moreover, we observed performance enhancement despite a significant decrease in free testosterone to cortisol ratio that coincides with findings in players competing in different team sports (Martin et al., 2019), in soccer players (Filaire et al., 2001) and in cyclists (Hoogeveen & Zonderland, 1996). Our results confirm the proposed hypothesis that a decrease in free testosterone to cortisol ratio could reflect an optimal state of physical functioning, although it could also indicate a future performance decrement and exhaustion. It is possible that the observed decrease in testosterone reflects a transient hormonal adaptation in response to acute training stressors or competition demands. While testosterone may decrease temporarily as a result of increased training load or competition stress, the body’s adaptive response mechanisms could lead to enhanced neuromuscular efficiency, improved motor coordination, or other performance-enhancing adaptations that manifest as improved jumping performance. Therefore, it is important to conduct larger studies with a longer follow-up to clarify this issue.

Limitations

This study has some limitations. The first concerns the frequency of blood biomarker collection, which could be more frequent in order to optimize athletes’ load on a week-to-week basis. However, in elite teams, achieiving increased frequency can be difficult due to dense competition schedule and frequent travels. Nonetheless, we found it sufficient to investigate the primary hypothesis—that is, the effects of the preparatory period on the aforementioned markers and jumping performance. The second limitation is the small sample size owing to the elite athlete sample. Therefore, results cannot be generalized to all athletes, and larger studies are needed to confirm the results on other team sport athletes, considering females as well. Although, this limitation can be seen also as a strength, because it is a sample of elite athletes (first-placed team in Slovenian handball), and sport science often needs to deal with small samples (Hecksteden et al., 2022).

Conclusions

The results of the current study clearly emphasize the relevance of monitoring blood biomarkers during the preparatory training period in elite handball players. The high and multifaceted physiological demands of the handball game during intensive trainings with a saturated competition schedule even in the preparatory period can result in a disturbed anabolic/catabolic hormone ratio and a free testosterone to cortisol ratio decrease, which could indicate either an optimal state or early exhaustiveness. Altogether, this warrants future research with larger samples in order to elucidate the variations of biomarkers throughout the season of professional handball players with a special emphasis on individual playing position. Coaches and other sports professionals working with athletes may use the results for individualized monitoring of an athlete’s health and performance, as an aid for prescribing proper training loads and recovery strategies accordingly to prevent performance declines and potential injury/illness occurrence.

Author contributions

KD, research concept and study design, data collection, analysis and interpretation, writing of the manuscript; AP, research concept, data analysis and reviewing/editing a draft of the manuscript; PP, AJ and AK; data collection and reviewing a draft of the manuscript.

Clinical trial registration

ClinicalTrials.gov (No. NCT0547129)

Data statement

Data will be provided by the corresponding author upon a reasonable request.

Ethics approval statement

This study was approved by the National Medical Ethics Committee of Slovenia (number: 0120–109/2022/3).

Patient consent statement

A signed informed consent was obtained from all participants prior to data collection.

Acknowledgments

The authors wish to thank University Medical Centre Ljubljana, Clinical Institute of Clinical Chemistry and Biochemistry for supporting the blood biomarker analysis.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work is supported by a research fellowship grant [No. 393/2020] received by KD from the Public Research Agency of the Republic of Slovenia (ARRS). The research took place within the KINESIOLOGY OF MONOSTRUCTURAL, POLYSTRUCTURAL AND CONVENTIONAL SPORTS research program, code: P5-0147, financed by the Public Research Agency of the Republic of Slovenia. The funding agency has no impact on data collection, analysis, or interpretation of the study results.