American football is a physiologically demanding sport with strength, power, and speed key determinants of success and primary goals of any strength and conditioning program for American football (1,5,8,9,11). However, concomitant to these goals are the needs for injury prevention including sudden death (2,3). Although a student-athlete may be exposed to potential traumatic injury including concussion, muscle is the most common tissue damaged from high-velocity eccentric loading, rapid acceleration and deceleration forces, and blunt force trauma resulting in elevations of creatine kinase (CK) (3,7,12,13). Prior research on CK concentrations the day after a competitive National Collegiate Athletic Association (NCAA) games has been shown to be 330.5 U·L−1 24 hours after a Division I game (12) and about 250 U·L−1 immediately after a Division III game (7), respectively. To date, only one study at the Division III level has examined muscle damage and endocrine changes during the entire football season with significant increases observed in CK 10 days after the preseason training camp along with significantly lower cortisol concentrations (6). In that study, they showed that CK then stabilized because it was drawn in the middle of the week with at least 15 hours from the prior practice. The concept of “contact adaptation” was coined from these early studies on CK in which one did not see the same elevations in CK, which was thought to be because of an accommodation of soft tissues to the practice and games-associated physical contact and blunt force trauma. However, how CK changes over a season of practice and game competition for Division I American football players is still unclear.
Cortisol reflects both the physical and psychological stress associated with one's environment and is considered to be a strong indicator of catabolic metabolism (15). Cortisol responses immediately after a Division III game were shown to be higher in starters than in nonstarters (7). However 24 and 48 hours after a game in Division I, no differences were observed before or after the game or between in starters or nonstarters (12). Thus, the typical values and time course of the cortisol response to American football requires additional research to be further elucidated.
To date, response patterns of clinical chemistries over a season remain unknown. An improved understanding of muscle tissue damage associated with practice and game demands in American football played at the Division I level can provide further insights into the demands of the game, which can benefit sport medicine and strength and conditioning professionals. Additionally, understanding what types of programs were used in relationship to these changes can address, in part, an evidence-based approach to conditioning for the sport. Therefore, the purpose of this study was to examine CK and serum cortisol in addition to standard clinical chemistry markers to observe their progression over time. Furthermore, observing the types of conditioning programs used allowed some context for their management.
Experimental Approach to the Problem
This study consisted was a prospective, longitudinal, single group study design. Our approach was to examine a muscle tissue damage marker (CK), a commonly assessed stress hormone (cortisol), and a panel of typical clinical chemistries. Additionally, we were able to document the strength and conditioning program to add some dimension to the study. Each of the players had participated in the year around strength and conditioning program, and proximate to this, study players had participated in the supervised summer strength and conditioning program. Resting blood samples were obtained after an 8-hour overnight fast on 6 different occasions throughout the season. All the blood samples for each individual were obtained at the same time of the day (within 1 hour) to account for diurnal variations. Resting blood samples were obtained just before the start of preseason summer practice (T-1), 2 weeks later (T-2) and the day 17–18 hours after game 2 (T-3), game 4 (T-4), game 6 (T-5), and game 9 (T-6) of a 12-game season.
Twenty-two NCAA Division I football players at the University of Connecticut volunteered to participate in this study. After a detailed description of the testing procedures and associated benefits and risks, each participant signed a written informed consent form approved by the University's Institutional Review Board for use of human subjects in research. Descriptive data of the subjects were as follows: age: 20.4 ± 1.1 years, height: 188.27 ± 8.3 cm, weight: 115.8 ± 29.7 kg. All the subjects had passed their physical examinations by the medical team and were cleared for practice and games. All the players in this study were of class ranks of sophomore or higher and had experience in both the weight room and on the football field.
Players consisted of both offensive and defensive starters and nonstarters that may have also played special teams (e.g., kickoff and kickoff returns and punt and punt returns). A play was defined as a specific start to finish involvement in one offensive, defensive, or special teams action from the start of putting the ball into play until the finishing whistle to end the play in a competitive game. The breakdown of players included the following: starters n = 7 starters and n = 4 nonstarters on offense; starters n = 7 starters and n =4 nonstarters on defense. Offensive starters include 3 backfield players (one quarterback), 3 linemen, and 1 wide receiver, whereas nonstarters included 1 backfield player, 1 linemen, 1 wide receiver, and 1 tight end. Defensive starters included 3 linemen, 2 linebackers, and 2 defensive backs, whereas nonstarters included 2 linemen, 1 linebackers, and 1 defensive back. All the players participated in each game including both offensive and defensive unit plays and special team plays. Additionally, we did not document other behavioral aspects of the players’ lives from nutritional to sleep patterns. Each player was able to eat at the training table and had a registered dietician assisting with the nutritional supplementation overview according to NCAA rules and regulations. All the players passed each NCAA drug test and educational programs on each element of the sports medicine program instituted. Future studies need to examine the specifics as to each element of the program. Thus, this study focused on the indirect marker of muscle tissue damage, cortisol, and clinical markers along with the strength and conditioning practices used.
Fasted resting blood samples were collected from an antecubital arm vein using a 20-gauge disposable needle equipped with a Vacutainer tube holder (Becton Dickinson, Franklin Lakes, NJ, USA) with the participants in a seated position. Approximately, 20 ml of blood was withdrawn and placed in two 10-ml serum tubes. Whole blood was allowed to clot at room temperature, before being centrifuged at 3,000 rpm at 4° C for 15 minutes. The resultant serum was divided into appropriate aliquots and stored at 80° C until subsequent analyses.
Creatine kinase was measured in duplicate using assay procedures from Genzyme Diagnostics (Charlottetown, PE, Canada). A BioMate spectrophotomer from Thermo Scientific (Waltham, MA, USA) was used to determine the appropriate absorbance values used in calculations. The CK analyses yielded a coefficient of variation was <2.6% for all samples. Serum cortisol was measured in duplicate according to procedures outlined in the assay protocol by (DSL-10–2,000) Diagnostic Systems Laboratory, Webster, TX. In brief, unknown samples 25 μl were incubated with a solution of cortisol conjugated to horseradish peroxidase and rabbit anticortisol serum in a protein-based buffer in microtitration wells that were coated with goat antirabbit gamma globulin serum. The unlabeled and enzyme-labeled antigens then competed for a limited number of anticortisol binding sites. The unbound cortisol was then washed away, and this was followed by incubation with substrate tetramethylbenzidine Chromogen solution. A reagent was then used to stop the reaction, and the absorbance was determined at 450 nm. The amount of enzyme-labeled antigen bound to the antibody was inversely proportional to the concentration of the unlabeled antigen present. The sensitivity of this assay was 0.1 μg·dl−1, and the coefficient of variance in this assay was 10.0%. Clinical chemistries, which included a comprehensive metabolic screening profile, were performed including serum glucose, albumin, total protein, minerals (sodium, potassium, chloride, calcium), renal function (blood urea nitrogen, creatinine), and liver function (alkaline phosphatase, bilirubin, alanine amino transferase, aspartate amino transferase) and analyzed by our reference laboratory (Quest Diagnostics, Storrs, CT, USA).
The typical days during preseason summer camp consisted of an NCAA-approved practice and workout schedule in accordance with the current rules and requirements at the time of the study. Each structured preseason summer camp day was composed of camp meetings, film study, team stretches, conditioning, and practices. After familiarization, strength testing was performed in the first 2 days of the preseason summer camp, with the participants having just completed a supervised summer strength and conditioning program with the strength and conditioning staff. Seven 1-a-day practices were followed by five 2-a-day practices leading up to the start of school and the first game of the season.
Strength and Conditioning
A modified nonlinear periodized resistance training program was followed by the subjects throughout the duration of the study (Table 1). The resistance training program was structured upon the weekly manipulation of relative training volume, which can be seen in Figure 1. Alterations in relative training volume in turn dictated the selection of exercises, sets, repetitions, and loads for each week. Relative training volume was calculated by the combination of the products of the load (in percentage of 1 repetition maximum [1RM]) and the number of repetitions performed of each set performed within that week of training. Fluctuations in relative training volume reflected the variation of the competitive schedule and the objectives of the training program itself for each football player. Strength was maintained in the major lifts from 92 to 94% over the entire 12-game season.
Loads for the core exercises (Olympic lifts, back squat, and bench press) were based on 1RM tests performed during the spring training using the Nebraska formula (1RM = [1 + (0.0333 × repetitions performed)] × load lifted). The initial load of auxiliary exercises was left to the discretion of the subjects. If the subject was able to complete all the target repetitions for each set of a particular exercise, the load would be increased the following week by a predetermined weight based upon the nature of the exercise (generally 5–10 lbs). Because variations in competition schedule, minor injuries, and fatigue during the in-season mesocycle, the subjects were given the ability to adjust loads to their own preference to accommodate the quality of the workouts and allow recovery when needed.
A 1-way repeated measures analysis of variance (time) was used to analyze the data. Data sets met all the assumptions for linear statistics. When a significant F score occurred, a Fisher's least significant difference post hoc test was used to determine pairwise differences. Additionally, an analysis of covariance was used to determine if playing time explained a given dependent variable. Statistical significance was set at p ≤ 0.05.
All the players participated in each game including both offensive and defensive unit plays and special team plays. Percentage of plays each player averaged ranged from 40 to 100% for offense and defense plays for each position, both starter and nonstarter. Additional special team plays resulted in additional plays for players with nonstarters playing a larger percentage of them. The mean number of plays for starters and nonstarters in total was 71 ± 20% for the 9-game part of the season studied. The distribution of participation over the season was not significantly different for each player because only the players that made it through the 9 games were used in the analysis of the data. Future studies need to examine the pattern of play for players on an entire team though an entire season, but this was beyond the logistical scope of this investigation.
Resting serum CK concentrations are shown in Table 2. No significant changes in CK concentrations were observed over the season. No differences existed between starters and nonstarters for CK concentrations, although in the last game the number of plays was a significant cofactor in explaining the increase in CK after game 9. As shown in Table 2, a range of CK values were observed over the season yet peak values of each range over the study were ≤1,070.0 IU·L−1 with the largest range was observed at T-6 after game 9 (119–2,834 IU·L−1). This along with the influence of the percentage of plays played in that game both indicate a trend toward an accumulation of soft muscle tissue damage with continued practice and play.
Resting serum cortisol concentrations can be seen in Table 3. No changes in serum cortisol concentrations were observed yet again large variations existed. However, peak values of each time point measured were all in ranges ≤465.0 nmol·L−1.
Changes for metabolic markers are shown in Tables 4–6. Changes observed were small in magnitude and not indicative of any metabolic or organ pathologies or stress. All the changes observed were within normal ranges for each clinical marker for each player and not considered to be clinically relevant.
Although the demands of an NCAA Division I game had been previously examined in the ninth game of a 12-game season, what happened leading up to that game was unknown (12). This study attempted to provide some data on the physiological changes that lead up to a late game in the season and the recovery responses observed the day after each game. Albeit this study had different players and a schedule of different competitive demands, we thought that tracking such changes would provide some novel insights into one of the most popular sports in the USA. In that prior game study, the starters who played the game had significant elevations in CK on Sunday after the game, but the mean values were <350 IU·L−1. Additionally, the nonstarters that did not play did play in the game did not demonstrate any significant increases in CK 18–20 hours after the game (12). Hoffman et al. (7) had shown that after a Division III game CK did not change, but myoglobin saw expected increases in starters. The values in this study represent players who actually played in the game albeit with different percentages of plays for each game. The practice and game stress by the ninth game of the season appeared to make an impact as different from prior games the number of plays now started to be a major influencing factor in the CK 24-hour response. Interestingly, the recovery values were lower than that which has been seen with rhabdomyolysis, yet no definitive value for CK has been shown to be a putative marker (2,3). The range of values observed still demonstrate the important need for individual monitoring of recovery from a game, and from this study, this may seem to be even more important as practice and game stress accumulate over the season.
In this study, we assessed our markers the morning after 17–18 hours after the game to allow for a determination of the acute recovery phenomenon from a game. Interestingly, only a small number of changes were observed in the clinical chemistries with cortisol relatively constant suggesting that both the physical and mental stress of the practices and games were being managed. Prior work by Hoffman et al. (6) had demonstrated that CK was higher and cortisol lower after summer preseason camp in Division III American football players. Our data show a relatively easy accommodation to the preseason summer camp despite the NCAA rules, which at the time were not as rigorous as they are today. Cortisol has been shown to be dramatically involved in immune modulation that when dramatically elevated well above the values seen in this study can inhibit both immune function, which is important for tissue repair and downstream Mammalian target of rapamycin (mTOR) signaling, which contributes to protein synthesis (4,14). Higher cortisol values have been associated with higher CK values after a weight training workout (typically short rest, high volume) (10). The normal modulation of cortisol over a football season could be because of optimal in-season strength and conditioning, and practice schedules along with coaching techniques of which each of these influence stress responses and requires further study.
Although not tested experimentally in this study, the implementation of a supervised summer strength and conditioning program appeared to eliminate the elevation in CK observed in the Hoffman et al. (6) study after preseason summer camp in Division III players. The use of a more aggressive “in-season” program in this study may also have contributed to the more stable management of muscle damage and hormonal stress responses as measured in this investigation.
The clinical chemistries shown in Tables 4–6 represent common clinical chemistries used to monitor clinical aspects of electrolytes, metabolism, and liver function. Minor changes were observed over the study duration from preseason summer camp to the ninth game of the season. These data are included for future reference in other studies in sports medicine. However, from a medical perspective, none of the changes were considered clinically relevant to a player’s health of training status because all were within normal values (low effect sizes) and most likely typical modulation of homeostatic concentrations in response to a multivector stressful environment and competition (16). For example, in this study, small changes were observed in total protein concentrations because they significantly decreased at T-2 and T-3. This may well have been because of the need for greater incorporation of amino acids in the repair process, which resulted in maintenance of muscle tissue damage. However, total protein returned to baseline and no significant differences from T-1 were found through T-4–T-6. These changes indicate that net protein balance was negative during the beginning of the season. To maintain a neutral net protein balance and indication of maintaining muscle mass or to have a positive net protein balance, an indication of increasing muscle mass sufficient dietary protein must be ingested. The results of this study indicate that sufficient dietary protein ingestion may be of particular importance at the beginning of the season. Such clinical marker data demonstrate that solid clinical management in sports medicine can maintain a student-athletes health and well-being even in such as competitive contact sport as American football at the Division I level.
In conclusion, the use of long-term strength training with heavy loads appears to provide the prophylactic advantage to mute muscle damage. Contact adaptation because of a progression of from higher CK values never did occur suggesting that the strength and conditioning programs played a larger role in this sample of players. However, a potential for muscle tissue damage accumulation or greater sensitivity over a long season was seen as a trend for this study and in the later game affected by the number of plays that the athlete participated in. The lack of any real changes in cortisol appears to indicate management of both physical and psychological stressors within normal ranges well below that seen in other conditions (e.g., overreaching and overtraining with >800.0 nmol·L−1.). Such data demonstrate that a comprehensive, sports medical approach to the management of student-athletes in the sport of American football can successfully modulate muscle tissue damage, clinical markers, and adrenal cortical stress. Yet concerns still exist for other aspects of the game that have been identified and require our attention, research, and concern (2,3).
The challenges for the safety and care of the student-athlete in American football have been a concern in sports medicine and by governing bodies. From prevention of sudden death in the sport to managing, the improved physical capacity of players to improve performance and prevent injury, multidisciplinary sport medicine teams (e.g., athletic training, sports medicine, nutrition, strength and conditioning, and other specialized medical specialties) are needed for its proper management. From this study, the major practical application is the support for a comprehensive strength training program over the year including summer, preseason, and in-season programs. Of major concern and importance is that because of time laminations, often football coaches do not allocate enough time for the implementation of “effective” strength and conditioning programs. This can be counterproductive to optimizing muscular fitness and performance, and such data as presented in this study support the use of a comprehensive program and the needed time to complete it. Contact adaptation or playing oneself into shape was not needed when an effective practice schedule and strength and conditioning program was implemented because no significant changes were observed in CK and adrenal cortical stress was managed. Nevertheless, individual monitoring of each player in a football program is needed and important to optimizing participation for the student-athlete.
Cristina Cortis is now with the University of Cassino and Southern Lazio, Cassino, Italy. Disa L. Hatfield is now with the University of Rhode Island. Maren S. Fragala is now with the University of Central Florida, Orlando, FL. Duncan French is now with the Northumbria University, Newcastle, United Kingdom. Nicholas Ratamess is now with the The College of New Jersey, Ewing, NJ. Barry A. Spiering is now with the United States Army Research Institute of Environmental Medicine, Natick, MA. Jakob L. Vingren is now with the University of North Texas, Denton, TX.
The investigators want to thank a dedicated group of student-athletes who participated in this investigation. The findings in this study do not reflect any endorsement by the National Strength and Conditioning Association. No conflict of interest exists, and this study was funded by internal funds at the University of Connecticut's Human Performance Laboratory.
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