Introduction
In an effort to enhance performance, athletes increase their training volume and intensity at strategic times during their competitive season. During these periods of intensified training (an increase in training volume, training intensity, or both), athletes may be at risk for developing overtraining syndrome. Overtraining has been defined as an accumulation of training and/or nontraining stress resulting in long-term decrement in performance capacity with or without related physiological and psychological signs and symptoms of overtraining in which restoration of performance capacity may take from several weeks to months (19). By comparison overreaching results in short-term decrement of performance taking only several days to weeks to recover (19). More recently, further clarification, detail, and consistency has been made to these definitions with the publication of a consensus statement (25). Briefly, overtraining is used as a verb to describe the process of intensified training with many possible outcomes (17,35). These outcomes may be (a) functional overreaching in which supercompensation may occur after an acute decline in performance consistent with the normal training response, (b) nonfunctional overreaching in which performance may decline or fail to increase but will recover after a period of several weeks or months, and (c) overtraining syndrome in which the decrease in performance may take months to recover. Importantly, the diagnosis of overtraining syndrome requires exclusion of other pathological etiology (25). These definitions suggest that performance is the criterion measure for overtraining syndrome and/or overreaching despite many other proposed physiological and psychological measures. However, the mechanisms, criteria, and symptoms for overtraining are poorly understood despite the importance of identifying early indicators that may lead to the performance decrements seen with overtraining and overreaching.
Past literature has suggested a wide range of physiological markers that may serve as early identifiers or potential markers of overtraining. A common practice for athletes is to measure morning resting heart rate (HR). Popular press suggests that a 10% increase in resting HR may be indicative of overtraining (4,15). However, investigations on resting HR as a marker of overtraining are not in agreement. Although some papers have reported increased resting HR as a sign of overtraining (9,31), others have not (23,30,34). Submaximal exercise HRs have also been reported to increase during a state of overtraining (14,20). Other common markers that have received debate in the literature include measures of immunosuppression and mood disturbance. Because immunosuppression has been associated with long-duration, high-intensity exercise (29), markers of immune system function such as secretory IgA may be useful in diagnosis. Mackinnon has reported lower salivary IgA concentrations in athletes who showed signs of overtraining when compared to athletes who were trained but did not show signs of overtraining (24). Overtraining paradigms have demonstrated negative mood disturbances in athletes (27,34) despite physically active individuals having more positive mental health than persons who are less physically active (26). Deterioration of mood state often precedes a drop in performance (27,34), indicating that this approach may be useful in the early detection of overtraining. The profile of mood states questionnaire (POMS) has been shown to detect differences between a nonfunctionally overreached individual and a control subject (28). Additionally, blood-borne markers have been associated with training stress and overtraining. The testosterone:cortisol ratio has been used as a measure of anabolic and catabolic balance (33), with a decrease of 30% being suggestive of overtraining (1). However, others have argued that overtraining cannot be monitored using this ratio during high-intensity exercise (12) and is better used to monitor exercise stress and recovery (13,14). Inconsistency in many of these proposed markers suggest the complexity of overtraining and the different states and severities of overtraining. It is difficult to discern in these studies which subject samples were overreached, overtrained, or simply trained.
Although previous literature has focused on the identification of markers of overtraining, the purpose of the present investigation was to impose a period of quantifiable intensified training to determine if commonly used diagnostic markers of overtraining parallel changes in physical performance and thus overreaching and overtraining status. Furthermore, we aimed to differentiate individuals with and without symptoms of overtraining using physiological and psychological symptoms that have been previously reported.
Methods
Experimental Approach to the Problem
The period of intensified training was organized as a 21-day bicycle tour through the mountains of western USA. Participants cycled at a self-selected work rate for the bulk of the training time (except for scheduled performance trials). Training consisted of cycling approximately 169 ± 4 km·d−1 on each of the 21 days except days 10 and 20 (rest days), for a total of 3,211 km. This represented a 418 ± 142% increase in training time compared to the 60 days before the study. Participants completed the training on identical (size adjusted) racing bicycles (Orbea USA, North Little Rock, AR, USA) equipped with a power tap power meter integrated into the rear wheel (Saris Cycling, Madison, WI, USA). Ad libitum energy was provided in the form of a hot breakfast and dinner from a catering service that specialized in bicycling tours. During the time spent cycling, participants were provided with as much commercially available supplemental foods as desired (energy bars and sport drinks, Gatorade, Chicago, IL, USA). Subjects slept in tents at prearranged sites during the study.
Subjects
Ten male participants were recruited from the local triathlon and cycling community. The data from 2 individuals are not included in the current data set because of technical issues with equipment. Therefore, the data represented in this paper are for 8 participants (n = 8). Descriptive data are presented in Table 1. Participants completed the protocols in August, which is nearing the end of the road cycling and triathlon seasons in the northwest USA. According to the criteria for classification of a world class cyclist put forth by Jeukendrup et al., these subjects would be classified as trained to well-trained cyclists (18). Subjects were informed of the experimental procedures and signed informed consent statements. All procedures were approved by the University of Montana institutional reviewboard before any data collection.
;)
Table 1: Descriptive data at the onset of training.
Procedures
Performance Trials
On days 1, 4, 7, 11, 14, 17, and 21, a 1-hour performance time trial was conducted on open roads. On these days, participants rode 5-10 km as a warm-up before starting the performance trial. Time trials were started at 2-minute intervals, and riders were instructed to ride as hard as possible during the 1-hour period. Power output may be dependent upon the terrain that the performance trial occurs but less so than speed and hence distance (10). Therefore, average watts produced during this 1-hour time trial was recorded as performance capacity. Altitude may also influence cycling capacity (5). Therefore, days 1 and 21 (which were conducted on the identical course) were analyzed independently of the other trials in an effort to eliminate the impact of variable terrain and altitude. Distance and speed were not used as the performance measure because the terrain varied by day (except days 1 and 21, which were on an identical course).
Profile of Mood States
The Profile of Mood States Brief QuikScore forms (MHS, North Tonawanda, NY, USA) were used to track mood state during the intensified training period. These forms allow for measurement of total mood disturbance, tension, depression, anger, vigor, fatigue, and confusion. This 30-question form was administered to participants in the morning before any activity on days 1, 4, 7, 11, 14, 17, and 21. This version of the POMS is comparable to that of the original POMS (8).
Heart Rate
Morning resting HR, submaximal stepping HR, and HR after 30 seconds of seated recovery were measured on days 1, 4, 7, 11, 14, 17, and 21 before any other activity. Resting HR was measured immediately upon waking for 5 minutes in a seated position. Participants then stepped up and down on a 20.32-cm step to a metronome (88 b·min−1) yielding a cadence of 22 steps per minute for 1 minute. Participants then immediately sat down, and recovery HR was recorded at 30 seconds postexercise. The postexercise recovery HR was then converted to percent recovery of resting HR.
Saliva Collection
Saliva samples were collected by the passive drool technique on the morning and immediately after cycle training on days 1, 4, 7, 11, 14, 17, and 21. Salivary flow rate was calculated by recording the time each individual took to fill a collection vial to 3 ml. The samples were weighed to verify the volume and then immediately frozen on dry ice until they were transferred to an −80°C freezer and stored for later analysis of testosterone, cortisol, and secretory IgA.
Testosterone, Cortisol, and Secretory IgA
Salivary testosterone, cortisol, and secretory IgA were measured in duplicate in the saliva samples using a competitive immunoassay on a plate reader (Model 680 XR, BioRad, Hercules, CA, USA) at 450 nm in accordance with the manufacture's protocol (Salimetrics, State College, PA, USA). Absolute secretory IgA was then corrected for salivary flow rate. If the coefficient of variation for duplicate samples was greater than 10% then samples were reanalyzed. The values reported in this manuscript are similar to others (11). Salivary measures of IgA, cortisol, and testosterone were measured due to the noninvasive collection method. The salivary markers change similarly in response to stimuli as serum measures and may be more responsive to exercise (3,7,32).
Maximal Exercise Capacity
Maximum oxygen consumption (V̇O2max) and workload associated with V̇O2max were measured for each subject before and after the intensified training using a graded exercise protocol. Briefly, the protocol started at 95 W, with an increase of 35 W every 3 minutes on an electronically braked cycle trainer ergometer (Computrainer, RacerMate Inc., Seattle, WA, USA). Participants rode to volitional fatigue. Maximum workload was calculated as the highest completed stage (in watts) + the proportion of time in the next stage multiplied by the 35-W stage increment. Expired gases were collected during the test using a calibrated metabolic cart (Parvomedics, Inc., Salt Lake City, UT, USA) and recorded at 15-second intervals.
Individual Responses
To determine the response of each individual, participants were classified by 4 markers of overtraining: (a) >5% reduction in time trial performance, (b) Increase in resting HR by >10% (4,15), (c) increased submaximal exercise HR by more than the day-to-day variation of 8 b·min−1 (21), and (d) >30% decrease in testosterone:cortisol ratio (1). These 4 markers were selected based on the ability to determine an individual critical value for each marker that if reached may imply a symptom of overtraining in that individual, as described in the previous literature (1,4,15,21). Individuals with 2 or fewer symptoms throughout the training period were classified as asymptomatic, whereas individuals with >2 symptoms were classified as symptomatic. Characteristics of these groups were then compared to determine if these groups differed.
Statistical Analyses
Differences in performance and overtraining parameters over 21 training days were compared using 1-way repeated-measures analyses of variance (ANOVAs). Additionally, a paired t-test was used to further analyze performance on day 1 vs. day 21, when testing conditions were controlled for terrain and altitude. Salivary testosterone, cortisol, and testosterone:cortisol ratio were compared over training days and by time of day (pre vs. postacute exercise) using 2-way repeated-measures ANOVAs. In the event of a significant F ratio the false detection rate method (2) was applied to locate differences and correct for multiple comparisons. All ANOVAs were performed using SPSS for windows Version 9 (Chicago, IL, USA). A probability of type 1 error <5% was considered significant (p ≤ 0.05). All data are reported as means ± SE.
Results
Training
During 21 days of intensified training, the participants cycled 3,211 km (169 ± 4 km·d−1 + 2 rest days) over varied terrain. See Figure 1 for the route profile. The time spent riding represented a 418 ± 142% increase in training time per day compared to the 60 days before this investigation. The riders averaged 167 ± 4 W (47 ± 1% of pretraining max watts) during the training. See Figure 2 for a detailed breakdown of riding intensity.
Figure 1: Route profile (elevation and distance) for the entire 21-day period of intensified training.
Figure 2: Cycling power distribution (power zones) as a percent of initial max power and percent of total ride time. Data are mean ± SE.
Performance
Average power output (in watts) during the 1-hour time trials was no different (p > 0.05) on day 4 (+2 ± 2%), day 7 (+2 ± 2%), day 11 (−6 ± 3%), day 14 (+5 ± 3%), day 17 (+3 ± 2%), or day 21 (+4 ± 4%) than it was on day 1 (Figure 3). Furthermore, a separate analysis of day 1 vs. day 21 in which the 1-hour performance trials were conducted on the identical course revealed no statistical difference (p > 0.05) as a result of the intensified training.
Figure 3: One-hour time trial performance throughout the 21-day period of intensified training. Data are mean ± SE.
Heart Rate
There was no change (p > 0.05) at any time point in resting HR (49 ± 1), step test exercise HR (92 ± 1), or percent HR recovery 30 seconds postexercise (64 ± 1%) from day-1 values (Figure 4).
Figure 4: Morning resting heart rate (HR), submaximal stepping exercise HR, and percent recovery from submaximal exercise in 30 seconds throughout the 21-day period of intensified training. Data are mean ± SE.
Salivary Markers
There was no change in salivary secretory IgA in absolute terms (μg·mL−1) or relative to salivary flow rate (μg·min−1, Figure 5) from day 1. Salivary testosterone and salivary cortisol both decreased from pre-daily exercise to post-daily exercise (p < 0.05) with no change over the 21 days of intensified training (Figures 6A, B). The testosterone:cortisol ratio increased (p < 0.05) from pre-daily exercise to post-daily exercise but did not change over the 21 days (Figure 6C).
Figure 5: Morning resting salivary secretory IgA throughout the 21-day period of intensified training. Data are mean ± SE.
Figure 6: A) Salivary cortisol pre-daily exercise and post-daily exercise throughout the 21-day period of intensified training. B) Salivary testosterone pre-daily exercise and post-daily exercise throughout the 21-day period of intensified training. C) Salivary testosterone:cortisol ratio (pmol·L−1 testosterone: nmol·L−1 cortisol) pre-daily exercise and post-daily exercise throughout the 21-day period of intensified training. Data are means ± SE. *p < 0.05 main effect for pre to postexercise.
Maximum Exercise Capacity
Maximum exercise capacity did not change over the course of 21 days of intensified training in terms of peak oxygen consumption (4.49 ± 0.11 L·min−1 pre, 4.57 ± 0.23 L·min−1 post, p > 0.05) or peak workload (355 ± 14 W pre, 365 ± 17 W post, p > 0.05).
Profile of Mood States
There was no change in total mood disturbance, tension, depression, anger, fatigue, or confusion over 21 days of intensified training. Vigor decreased from days 1 to 4 (p < 0.05) and remained lower throughout the 21-day training cycle (Figure 7).
Figure 7: Profile of mood states (POMS) score for total mood disturbance and vigor throughout the 21-day period of intensified training. Data are mean ± SE. *p < 0.05 for vigor from day 1.
Individual Response
The presence or absence of overtraining symptoms for each participant is indicated in Table 2. Four individuals developed 2 or fewer symptoms (asymptomatic group) and 4 individuals developed >2 symptoms (symptomatic group). The symptomatic group had a lower absolute V̇O2max (p < 0.05), a trend for a lower max workload (p = 0.09), and lower performance during the 1-hour time trial (p < 0.05, Table 3) than the asymptomatic group. There was no statistical difference between groups for other select variables (see Table 3).
Table 2: Individual subject daily overtraining symptoms.
Table 3: Descriptive data at the onset of training for participants who had <2 symptoms of overtraining/overreaching (asymptomatic) and those who had 2 or more symptoms (symptomatic).
Discussion
One of the novel aspects of this study is the method in which the data were collected. This investigation took place during a 3-week period of intensified training in the field, not in a laboratory setting. The use of a power meter incorporated into each participant's bicycle allowed us to quantify the work that was being completed over the entire 3,211-km route during the 21-day period. Although the average work rate remained low (47.2 ± 1.1% of pretraining watts max), the daily mean time spent at an intensity greater than 70% of max watts was on average 71 minutes, of which 21 minutes was spent above 90%, during each day of riding. Furthermore, participants completed a 1-hour time trial on 7 separate occasions. This design allowed us to aggressively stress the participants with both exercise volume (418 ± 142% increase in volume) and intensity while concurrently evaluating changes in their performance. A goal of this project was to induce a period of intensified training to put participants into a state of overreaching (functional or nonfunctional). By definition, a decrement in performance must occur for the diagnosis of overtraining or overreaching to be made (19). The performance of the current subjects did not significantly change but did show a nonsignificant, yet practical, increase (p > 0.05) by an average of 4.3%. Therefore, despite the large increase in training volume, we were unable to create a training stimulus that had a negative impact on performance in these participants as a whole. Moreover, the only marker of overtraining used in this investigation that did show a significant change was a decrease in the POMS category of vigor. However, without an observed measurable change in performance singular markers of overreaching and/or training may have limited diagnostic value.
Although there were minimal statistical changes in the overtraining markers, it is possible that certain individuals may have developed signs of overreaching/overtraining. To further evaluate the individual response, subjects were classified as symptomatic or asymptomatic based on 4 markers of overtraining: (a) >5% reduction in performance, (b) resting HR increase by >10% (4,15), (c) increased submaximal exercise HR by more than a reported day-to-day variation of 8 b·min−1 (21), and (d) >30% decrease in testosterone:cortisol ratio (1). The individuals with 2 or fewer of these symptoms (asymptomatic group) of overtraining had a higher absolute VO2max, a trend toward a higher max workload, and produced more watts during the 1-hour time trial at the start of intensified training. Each of these differences is muscle mass dependent, and thus, the amount of lean muscle mass appears to interact with the measured symptoms of overtraining. Furthermore, the asymptomatic participants increased their 1-hour time trial performance by 9.9%, whereas the symptomatic participants decreased performance by 1.3% during the 21-day period (pre vs. post training, p > 0.05 between groups). Although it is unclear whether or not the markers analyzed here are good at detection of overtraining, they do seem to be indicative of training response.
The intensified training period represented a 606% increase in training volume for the asymptomatic participants and only a 277% increase in training volume for the symptomatic participants. It seems counterintuitive that no symptoms of overtraining were demonstrated in the individuals who had a greater increase in training volume although symptoms of overtraining were demonstrated in the individuals who had a smaller increase in training volume. It is possible that the symptomatic participants were further along their individual overreaching or overtraining continuum, although no symptoms were present at the onset of this study, and that there may be a threshold for training volume that was exceeded during the study period. Additionally, the asymptomatic participants may have a more favorable genetic and physiological profile that helps them adapt to intensified training. These data further support the notion that individual athletes respond differently in terms of susceptibility to symptoms of overtraining (6). Interestingly, symptoms that developed early in the training period did not always persist throughout the 3 weeks despite little time for recovery (Table 1). During the 3 weeks, only 2 days were used as recovery days (days 10 and 20).
Overtraining is thought to result as a function of an imbalance between stress and stress tolerance. Lehman et al. (22) have defined stress as the sum of training and nontraining stress factors. Furthermore, overtraining can occur when an athlete experiences high psychological and social stress but relatively low physiological stress (14). During the current study, removing the participants from their normal living environment minimized many sources of extraneous psychological stresses. The participants did not have to worry about school, jobs, scheduling, meal preparation, etc. Although the training stress was high, other stresses were minimized by having high-quality meals and by eliminating late nights, thereby providing an environment conducive to maximizing recovery. It is unclear how the control of other nontraining stresses may have impacted these results. In a 7-day period of intensified training, another investigation was able to see a decrease in performance when participants continued to live in their normal environment (16). Further investigation is warranted to determine the effectiveness of training camps for athletes when completed in their normal (higher social stress) living environment vs. an isolated training camp completed away from these stresses.
Practical Applications
These data demonstrate that markers of overtraining do not always parallel a decrease in performance and that these markers are unstable. The authors suggest that the markers presented here may simply indicate the presence of a training stress and not specifically overtraining. Others have also suggested that some of these markers of overtraining are characteristic of intense training and not overtraining (6). Anecdotally, many of the participants had their best competitive seasons after the conclusion of this study.
Athletes, coaches, sports scientists, and clinicians must exercise caution when making the diagnosis of overtraining syndrome based on previously reported markers of overtraining. The criterion variables of performance and recovery must be incorporated and as such early detection may be limited. Furthermore, many athletes may be able to tolerate very high training volume and intensity without developing overtraining syndrome, particularly when they can limit their nontraining stresses.
Acknowledgments
The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Air Force Research laboratory or the US government. Sponsored by Air Force Research Laboratory under agreement number FA5650-06-2-6740. The results of the present study do not constitute endorsement of any product by the authors or the National Strength and Conditioning Association.
References
1. Adlercreutz, H, Harkonen, M, Kuoppasalmi, K, Naveri, H, Huhtaniemi, I, Tikkanen, H, Remes, K, Dessypris, A, and Karvonen, J. Effect of training on plasma anabolic and catabolic steroid hormones and their response during physical exercise.
Int J Sports Med 7(Suppl. 1): 27-28, 1986.
2. Benjamini, Y and Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing.
J R Stat Soc Ser B 57: 289-300, 1995.
3. Brandtzaeg, P. Do salivary antibodies reliably reflect both mucosal and systemic immunity?
Ann N Y Acad Sci 1098: 288-311, 2007.
4. Brown, RL and Henderson, J.
Fitness Running. Champaign, IL: Human Kinetics, 1994.
5. Clark, SA, Bourdon, PC, Schmidt, W, Singh, B, Cable, G, Onus, KJ, Woolford, SM, Stanef, T, Gore, CJ, and Aughey, RJ. The effect of acute simulated moderate altitude on power, performance and pacing strategies in well-trained cyclists.
Eur J Appl Physiol 102: 45-55, 2007.
6. Costill, DL, Flynn, MG, Kirwan, JP, Houmard, JA, Mitchell, JB, Thomas, R, and Park, SH. Effects of repeated days of intensified training on muscle glycogen and swimming performance.
Med Sci Sports Exerc 20: 249-254, 1988.
7. Crewther, BT, Lowe, TE, Ingram, J, and Weatherby, RP. Validating the salivary testosterone and cortisol concentration measures in response to short high-intensity exercise.
J Sports Med Phys Fitness 50: 85-92, 2010.
8. Curran, SL, Andrykowski, MA and Studts, JL. Short Form of the Profile of Mood States (POMS-SF): Psychometric information.
Psychol Asses 7: 90-83, 1995.
9. Dressendorfer, RH, Wade, CE, and Schaff, JH. Increased heart rate in runners: A valid sign of overtraining.
Phys Sport Med 13: 77-86, 1985.
10. Ebert, TR, Martin, DT, McDonald, W, Victor, J, Plummer, J, and Withers, RT. Power output during women's World Cup road cycle racing.
Eur J Appl Physiol 95: 529-536, 2005.
11. Elloumi, M, Maso, F, Michaux, O, Robert, A, and Lac, G. Behaviour of saliva cortisol [C], testosterone [T] and the T/C ratio during a rugby match and during the post-competition recovery days.
Eur J Appl Physiol 90: 23-28, 2003.
12. Fry, AC, Kraemer, WJ, and Ramsey, LT. Pituitary-adrenal-gonadal responses to high-intensity resistance exercise overtraining.
J Appl Physiol 85: 2352-2359, 1998.
13. Fry, RW, Morton, AR, Garcia-Webb, P, and Keast, D. Monitoring exercise stress by changes in metabolic and hormonal responses over a 24-h period.
Eur J Appl Physiol Occup Physiol 63: 228-234, 1991.
14. Fry, RW, Morton, AR, and Keast, D. Overtraining in athletes. An update.
Sports Med 12: 32-65, 1991.
15. Galloway, J.
Marathon! Atlanta, GA: Phidippedes Publication, 1996.
16. Halson, SL, Bridge, MW, Meeusen, R, Busschaert, B, Gleeson, M, Jones, DA, and Jeukendrup, AE. Time course of performance changes and fatigue markers during intensified training in trained cyclists.
J Appl Physiol 93: 947-956, 2002.
17. Halson, SL and Jeukendrup, AE. Does overtraining exist? An analysis of overreaching and overtraining research.
Sports Med 34: 967-981, 2004.
18. Jeukendrup, AE, Craig, NP, and Hawley, JA. The bioenergetics of World Class Cycling.
J Sci Med Sport 3: 414-433, 2000.
19. Kreider, RFA and O'Toole, M. Overtraining in sport: Terms, definitions, and prevalence. In:
Overtraining is Sport. Kreider, FAR and O'Toole, M, eds. Champaign, IL: Human Kinetics, 1998. pp. vii-ix.
20. Kuipers, H and Keizer, HA. Overtraining in elite athletes. Review and directions for the future.
Sports Med 6: 79-92, 1988.
21. Lamberts, RP, Lemmink, KA, Durandt, JJ, and Lambert, MI. Variation in heart rate during submaximal exercise: Implications for monitoring training.
J Strength Cond Res 18: 641-645, 2004.
22. Lehmann, M, Foster, C, and Keul, J. Overtraining in endurance athletes: A brief review.
Med Sci Sports Exerc 25: 854-862, 1993.
23. Lehmann, M, Gastmann, U, Petersen, KG, Bachl, N, Seidel, A, Khalaf, AN, Fischer, S, and Keul, J. Training-overtraining: Performance, and hormone levels, after a defined increase in training volume versus intensity in experienced middle- and long-distance runners.
Br J Sports Med 26: 233-242, 1992.
24. Mackinnon, LT. Chronic exercise training effects on immune function.
Med Sci Sports Exerc 32 (7 Suppl.): S369-S376, 2000.
25. Meeusen, R, Duclos, M, Gleeson, M, Rietjens, G, Steinacker, J, and Urhausen, A. Prevention, diagnosis and treatment of the overtraining syndrome.
EurJ Sport Sci 6: 1-14, 2006.
26. Morgan, WP. Selected psychological factors limiting performance: A mental health model. In:
Limits of Human Performance. Clark, DH and Eckert, HM, eds. Champaign, IL: Human Kinetics, 1984. pp. 77-80.
27. Morgan, WP, Brown, DR, Raglin, JS, O'Connor, PJ, and Ellickson, KA. Psychological monitoring of overtraining and staleness.
Br J Sports Med 21: 107-114, 1987.
28. Nederhof, E, Zwerver, J, Brink, M, Meeusen, R, and Lemmink, K. Different diagnostic tools in nonfunctional overreaching.
Int J Sports Med 29: 590-597, 2008.
29. Pedersen, BK, Rohde, T, and Zacho, M. Immunity in athletes.
J Sports Med Phys Fitness 36: 236-245, 1996.
30. Snyder, AC, Kuipers, H, Cheng, B, Servais, R, and Fransen, E. Overtraining following intensified training with normal muscle glycogen.
Med Sci Sports Exerc 27: 1063-1070, 1995.
31. Stone, MH, Keith, RE, Kearney, JT, Fleck, SJ, Wilson, GD, and Triplett, NT. Overtraining: A review of the signs, symptoms and possible causes.
J Appl Sport Sci Res 5: 35-50, 1991.
32. Tunn, S, Mollmann, H, Barth, J, Derendorf, H, and Krieg, M. Simultaneous measurement of cortisol in serum and saliva after different forms of cortisol administration.
Clin Chem 38: 1491-1494, 1992.
33. Urhausen, A, Gabriel, H, and Kindermann, W. Blood hormones as markers of training stress and overtraining.
Sports Med 20: 251-276, 1995.
34. Urhausen, A, Gabriel, HH, Weiler, B, and Kindermann, W. Ergometric and psychological findings during overtraining: A long-term follow-up study in endurance athletes.
Int J Sports Med 19: 114-120, 1998.
35. Urhausen, A and Kindermann, W. Diagnosis of overtraining: what tools do we have?
Sports Med 32: 95-102, 2002.
