Introduction
Jump landing followed by a sudden deceleration is considered to be a mechanism for lower limb injuries (2,24), and the risk of sustaining injuries increases with fatigue (5) in the later stages of exhausting activity (12,27). Kinetics and kinematics of the lower limbs might be altered when landing after fatigue: peak ground reaction forces (GRF), joint angles (26), and joint moments (34) seem to change, and stabilization (ST) times were found to be longer (4). Furthermore, performance in intense intermittent exercise and in sprints decreases (14).
The risk of sustaining an injury might also be higher in unplanned movements: Prelanding muscle response latencies have been found to be modulated during self-initiated drops as compared with unexpected drops (10).
The influence of fatigue on dynamic postural control after running remains unclear: tested by means of the star excursion balance test, treadmill running did not show adverse effects on dynamic postural control (42). However, static postural control was impaired in the same subjects. Therefore, those authors concluded that it would be helpful to compare fatigue-related effects on sports-specific sensorimotor control by using different measures of dynamic postural control (42).
Limitations of some previous studies include controlling for fatigue levels and evaluating a subject's effort to be able to compare athletes of different levels. Running (28,30), push-ups/sit-ups/step-ups (41), jumps (7,18), squats step-up (25), and stepping and bounding (20) were used in these studies to induce fatigue. Although previous studies investigated recovery of static postural control after fatiguing exercises (9,16), there is still a lack of knowledge concerning short-term recovery of dynamic postural control under these conditions. For practical purposes, it is important to know whether athletes of different levels are well prepared for situations when they have reached a certain fatigue level or whether they would need supplementary training to prevent adverse effects of fatigue. Indeed, ball sports athletes should be specifically trained for such situations to prevent injuries because frequent jump landings can already trigger lower limb injuries before fatigue sets in, and even more so under fatigued conditions.
However, it is not known whether high-level ball sports training would include enough elements that enhance resistance to the effects of fatigue on dynamic postural control. Under nonfatigued conditions, the rate of jump landing errors did not differ among varsity, club, and intramural athletes (Landing Error Scoring System), but their fitness levels did vary (37). None of the previous studies compared high-performance ball sports athletes with recreationally active subjects (RAS) in terms of the effects of fatigue on jump landing with an unknown subsequent motor task and recovery.
Our main hypothesis was that fatigue negatively affects dynamic postural control in jump landing and ST. Furthermore, we postulated that dynamic postural control would be less affected in high-performance athletes (HPA) than in RAS.
Methods
Experimental Approach to the Problem
To determine the influence of fatigue on dynamic postural control in athletes of different levels, we developed the following test protocol. It is meant to approximate a risk situation within a reasonable degree, while standardizing the fatigue level by using the individual anaerobic threshold (IAT). An instrumented ball triggers lamps, creating an unanticipated motor task during a jump landing.
Two test sessions were conducted: the incremental treadmill test, to determine the IAT, and the jump test (JT), performed at least 5 days and no more than 30 days later. The fatigue level was monitored according to the Borg Scale (3) and by measuring heart rate (HR) and blood lactate levels. Dynamic postural control was determined before and after a treadmill run at the IAT. The ST force integral index, the dependent variable, was calculated, representing the dynamic postural control for landing and ST. The independent variables were time points (before and until 20 minutes after the run at 5-minute intervals) and group (HPA/RAS). The hypothesis was tested by comparing the ST force integral index before and after the treadmill run and during the recovery time and between athletes of different levels. This procedure made it possible to address the question of whether athletes of both levels, HPA and RAS, are prepared to resist fatigue effects, and if so, to what degree. If important deficits in postural control were found under fatigued conditions, coaches and trainers should develop specific programs that are adapted to each level of training to improve ability in these situations.
Subjects
Eighteen HPA (women, age: 20.5 [5.1] years, mean [SD], range: 16–31 years) and 24 RAS (16 women, 22.4 [2.8] years, 20–28 years, 8 men, 23.9 [2.8] years, 20–28 years) participated. Competitive level sport was required for HPA: 8 athletes were from the top National Volleyball League and National Junior Team, and 10 from the top National Handball League and Regional League. Inclusion criterion for RAS was participation in sport for 0.5–4 hours per week. General exclusion criteria were current history of a lower extremity injury requiring training cessation on the day of testing, neurological diseases, vestibular or visual disturbances, cardiovascular diseases, or medication that could affect balance.
The recent activity level was monitored by questionnaire: hours of training/sports on the day before the testing (JT) were for HPA 2.42 hours ±1.93 and for RAS 0.63 hours ±0.70 and on the day of testing 0.28 hours ±0.67 (HPA) and 0.04 hours ±0.14 (RAS), respectively.
Appropriate written informed consent pursuant to law has been obtained by all subjects, and in case of minor subjects, by their parents. The procedures and the test protocol were approved by the Ethics Committee of the Medical Department of the University of Heidelberg (No. 407-05) and followed the tenets of the Helsinki Declaration.
Procedures
The 2 test sessions, the incremental treadmill run and the JT session, were performed in the afternoon (in similar time slots) for all participants. A maximum of 2 athletes were present in the laboratory at the same time.
Incremental Treadmill Test
The runs were conducted on a treadmill (Woodway, Weil am Rhein, Germany, 1.5% uphill inclination, 1-minute warm-up).
Beginning with 6 km·h−1 (RAS) or 8 km·h−1 (HPA), the speed was increased by 2 km·h−1 every 3 minutes until volitional exhaustion was reached. Before the test, during the last 20 seconds of each exercise step, as well as 1, 3, 5, and 10 minutes after cessation of exercise, 20 μl of capillary blood was drawn from the fingertip to measure lactate levels by using an automated system (EBIO plus; Eppendorf, Hamburg, Germany) to determine the IAT (36). Heart rate was continuously registered by electrocardiogram and recorded during the last 15 seconds of each exercise step (EK 53; Hellige, Freiburg, Germany).
Jump Test
The JT was performed with bare feet on a multicomponent force plate (Type 9287; Kistler, Winterthur, Switzerland), 60 × 90 × 10 cm, fixed to the floor. The ball switch was custom made, constituting a foam volleyball on the rod of an electrical switch (Part. Nr. GLAC01E7B; Honeywell, Offenbach, Germany). Indicator lamps (14.5 × 7.5 cm) were placed on each side, 1 m in front of the center of the force plate. Figure 1 shows the set up. The ball switch was raised above the extended arm by a distance corresponding to 50% of the subject's maximum vertical jump (33,40). The subject started on a line 70 cm from the center of the plate (40) and was required to jump off forward to hit the ball overhead (Figure 1A). If no light illuminated during the jump, the subject was required to land on the dominant foot on the force plate (Figure 1B) and stabilize in a single-leg stance for 3 seconds, fixating on a red square on the opposite wall (ST; Figure 1C). If one of the lights on either side illuminated, the subject was required to perform a second jump (SJ) from the force plate 90° to that side. The lamp activation circuit was triggered by the ball switch. The order of the lamp selection was determined before each test session by drawing lots, with each task being performed 3 times per set (=9 jumps).
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Figure 1: High-performance athlete (volleyball) during a stabilization trial: jumping off with both legs, hitting the ball switch overhead (A), landing on 1 leg (B), and stabilizing on the landing leg, fixating on a red square on the opposite wall (C).
The subjects practiced each possibility (ST, SJ to the right and to the left) 5 times before testing. Three sets were performed before and 5 after the 30-minute treadmill run, at minutes 1, 5, 10, 15, and 20. Between these sets, subjects rested on a chair. The last set before the run served as baseline for the analysis of fatigue effects on dynamic postural control. The ST was repeated at another time point of the set if the subject lost balance and touched the floor with the other foot or if an additional hop occurred on landing. If the wrong movement task was performed, that trial was discarded and had to be repeated. In both cases, these trials were documented as “failed trials.”
Thirty-Minute Exercise Load on the Treadmill
The 30-minute treadmill run during the JT session was performed in running shoes at a constant speed at the respective IAT. Heart rate was recorded during the last minute of every 10-minute interval using a HR monitor (Electro BG750; Polar, Kempele, Finland). Subjects were asked to indicate their rate of perceived exertion (Borg Scale) every 10 minutes (3). After 30 minutes of running, the speed was reduced to 6 km·h−1 until a capillary blood specimen for measuring lactate was taken from the fingertip. One minute after the end of the exercise, the subject started the JT again. During the entire JT, HR and Borg Scale were examined immediately before each trial set.
Data Collection and Analysis
Ground reaction forces data were collected at 200 Hz for 3.3 seconds, triggered by touching the plate (Kistler Bioware software, version 3.2.6, Kistler, Winterthur, Switzerland; amplifier: Model 9865; analogue/digital conversion: 5606A DAQ-system) and filtered with a second-order recursive low-pass Butterworth digital filter, using a cutoff frequency of 10 Hz.
Dynamic postural control in ST was measured as the integrals of the absolute values of the GRF:
integral functions over time, Fx, Fy, and Fz: GRF mediolateral, anteroposterior, and vertical, Fw = gw: body weight, g: gravitational constant, and w: body mass.
The outcome parameter, the ST force integral index, was defined as:
For each trial set, the mean of the 3 ST was used.
Data processing and the results of the SJ to the side have already been presented (15).
Statistical Analyses
Measures of central tendency and dispersion were calculated, and goodness-of-fit to normal distribution was assessed using the Kolmorogov-Smirnov test. As the data were normally distributed, a repeated-measures analysis of variance (ANOVA) was performed, taking time and group as the independent variables; furthermore, 95% confidence intervals (CIs) were determined. The significance level was set at α = 0.05. Reliability of the JT with ST was determined by comparing the mean of the 3 ST trials of the 2 last trial sets before the 30-minute run (IBM SPSS Statistics 21, Armonk, NY, USA). Power analysis was performed with G*Power (3.1.6; Franz Faul, University of Kiel, Kiel, Germany): power (1 − beta error probability) = 0.87.
Results
Dynamic postural control was significantly impaired in the first minute after the run in all participants: the ST force integral index 1 minute after the run was 3.92 m·s−1 (0.58 m·s−1) (mean [SD]) vs. 3.67 m·s−1 (0.38 m·s−1) at baseline (before the run), (p = 0.043, 95% CI of the difference: 0.10–0.40 m·s−1, η2 = 0.031) (ANOVA). High-performance athletes and RAS showed comparable values (Table 1, no significant differences). Over all subjects, the number of failed ST trials was significantly different between time points (Friedman, p = 0.005). Recreationally active subjects failed more trials per person than HPA at the first, fifth, and 20th minute after the run (Figure 2; nonsignificant). The relative change in the force integral compared with baseline (Figure 3) suggests that RAS were affected more by fatigue than HPA (nonsignificant).
Table 1: Mean ± SD of the stabilization force integral index before (baseline) and after the 30-minute treadmill run (m·s−1).*
Figure 2: Ratio of failed stabilization trials (number of failed trials per person, SD). HPA = high-performance athletes; RAS = recreationally active subjects; baseline: directly before the 30-minute treadmill run; Min 1, 5, 10, 15, and 20: at 1, 5, 10, 15, and 20 minutes after the treadmill run.
Figure 3: Relative change in the dynamic postural control in jump landing: the stabilization force integral index compared with the baseline in percent; before the 30-minute run (baseline), and 1, 5, 10, 15, and 20 minutes (Min 1, 5, 10, 15, and 20) after the run. HPA = high-performance athletes; RAS = recreationally active subjects.
In each group, the 30-minute run was at IAT (Tables 2 and 3). The rates of perceived exertion at baseline and during and after the treadmill run were similar in the 2 groups (Figure 4). The reliability of the ST force integral index was determined with intraclass correlation coefficient (ICC): 0.84 (0.70–0.91).
Table 2: Mean ± SD of treadmill speed, heart rate, and lactate at the individual anaerobic threshold, and lactate after the 30-minute run.*
Table 3: Mean ± SD of heart rate per minute before, during and after the 30-minute run.*
Figure 4: Rate of perceived exertion, measured with the Borg scale (mean values, SD), before (BL), during the run (at 10, 20, 30 minutes: m10, m20, and m30), and after the run (at 1, 5, 10, 15, and 20 minutes: MIN 1, 5, 10, 15, and 20); HPA and RAS. BL = baseline; HPA = high-performance athletes; RAS = recreationally active subjects.
Discussion
The aim of the present study was to compare the effects of fatigue on dynamic postural control in jump landing in athletes of different levels. Dynamic postural control was found to be impaired by fatigue in both HPA and RAS. Contrary to our expectations, dynamic postural control was not more impaired in RAS, apart from higher error rates and apparent differences in the relative change (Figure 3). High-performance athletes seemed to have recovered faster than RAS, however (Figure 3).
In the literature, only little information is presently available about the effects of different training levels on the degree of impairment caused by fatigue and the recovery speed.
Central and peripheral adaptations to fatigue include changes in recruiting muscle motor units, in coactivation patterns, and in the neuromuscular junction (11). A decline in performance after exercise may be the result of a change in coordination, in the functional capacity to produce force, or both (31). The increase in the error points (Figure 2) after the exercise shows that fatigued subjects had more difficulties in fulfilling the required, complex task.
The force integral represents the total need of force for landing and stabilizing in a certain time period. Higher values after the run indicate an increased need for neuromuscular control. This result is in line with previous studies, demonstrating that fatigue temporarily decreases the neuromuscular control of postural stability (4,39). However, our parameter produces higher values than the previously developed “dynamic postural stability index” (40). Therefore, it could be helpful in distinguishing between groups.
Our study indicates that fatigue affects athletes independently of their training level. Indeed, the abilities we tested were probably not specifically trained in these ball sports athletes: Both RAS and HPA showed similar ratios of failed trials at the baseline measurement, which confirms recent findings about similar landing errors in athletes of different levels (37).
Santamaria et al. (34) pointed out that most study protocols did not allow the subjects' effective fatigue levels to be monitored properly. The cardiovascular and metabolic parameters of our study subjects clearly indicate a standardized fatigue level (Tables 2 and 3). In addition, the Borg scales show the high subjective effort level in both groups (Figure 4). This parameter was previously found to be appropriate for monitoring both local and general fatigue components (34).
Fatigue in terms of lactate level reached almost that found in female elite soccer players after the first half of a competitive match (14) and it was higher than the level measured at any time in elite volleyball players during a beach volleyball match (19). In handball, higher lactate levels are reached during the matches (6,17). We chose the IAT to achieve a comparable and relatively high fatigue level in all participants. Had we asked the athletes to reach an effort level beyond their IAT, we would probably have had study dropouts. It was important for the study design to allow all athletes to fulfill the entire 20-minute run. The duration of the run was chosen to induce not only physical fatigue but also a certain degree of mental fatigue, just as it would be in a real situation in sports. The effects on postural control might be higher if higher states of fatigue (body and mind) are reached during matches. These data could be extrapolated.
Dynamic postural control in jump landing is impaired directly after a 30-minute run not only in RAS but also in HPA. Therefore, the risk of injury could be higher under fatigued conditions, independently of the training level.
Practical Applications
In volleyball, the lower extremity accounts for more than half of all injuries. Ankle sprains represent 44% of game injuries and almost a third of those sustained during practice. Most injuries occur in the front positions (1), where jump landings are common investigation of neuromuscular fatigue in elite handball players during training and tournaments revealed a significant performance reduction in sprint and JTs (32). There is strong evidence to suggest that neuromuscular training can improve dynamic postural control (8) and lower limb biomechanics in ball sport athletes (23). Proprioceptive training reduced recurrent ankle sprains in soccer players (21) and in other ball sports athletes to the level of not previously injured athletes (38). Furthermore, video and verbal feedback could already improve landing biomechanics in ball sports athletes (29) as could specific jump exercises over a relatively short period of 4 weeks (13). In addition, imagery-based training was found to change landing biomechanics (35).
With the knowledge of the present study, we highly recommend that ball sports athletes participate in neuromuscular training and special jump landing training. This exercise could alternate between periods of high effort and neuromuscular training, as suggested previously (22), to enhance resistance to fatigue effects on dynamic postural control. We would also suggest monitoring individual abilities to maintain postural control under fatigued conditions and adjusting exercise intensity and frequency on an individual basis.
Recovery time was relatively short. Consequently, an appropriate time out during training sessions and during a match would probably prevent injuries by avoiding an accumulation of fatigue effects.
Acknowledgments
The authors thank Prof. Dr. Peter Bärtsch, MD, PhD, Department of Sports Medicine (Internal Medicine VII), Heidelberg University Hospital, for support and Dr. Ulrike Mehnert, MD, Department of Sports Medicine (Internal Medicine VII), Heidelberg University Hospital, for help in data acquisition, the Department of Sports and Sports Science of the University of Heidelberg for providing facilities, Simone Gantz for statistical support, Eva Kalkum for help in formatting the article, and Sherryl Sundell for English language revision. This study was supported by the Federal Institute of Sports Science (Bundesinstitut für Sportwissenschaft), Germany/Europe (project no. IIA1-070122/05-06).
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