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Abstract

BACKGROUND:

Basketball players playing for the University of Hawai’i Hilo are subjected to well above normal physiological and psychogenic stressors with their exposure to significant amounts of easterly-bound air travel that include time zone and seasonal changes throughout one season.

OBJECTIVE:

The aim of this study was to investigate the effects of a basketball season on physiological, anthropometrical, biometric markers, strength and power of men’s collegiate basketball team who play their away matches after a relatively long (up to 6 h) eastward flight.

METHODS:

Thirty-six men collegiate basketball players and a control group of thirty-seven university students, were included in this study. Measurements were commenced at the beginning of the season and concluded immediately post-season.

RESULTS:

Post-season, players presented with significant gains for resting levels of salivary cortisol; significant gains in visceral trunk fat, total body fat percent or body weight, in resting heart rate and mean arterial blood pressure; and diminishment in leg muscle isokinetic force, most noticeably in knee flexion strength. Vertical jump height also decreased significantly post-season. These changes were not found in the control group.

CONCLUSION:

A flight-travel-heavy basketball season resulted in broad-spectrum declinations in variables related to overall health and well-being in men collegiate basketball players. It is concluded that the prolonged intermittent stress of such a season resulted in measureable stress such as increased cortisol levels, increased blood pressure and heart rate, and selective increase in visceral trunk fat, total percent body fat thus total body weight.

Keywords

Basketball season body composition chronobiology cortisol waist-to-hip ratio

1. Introduction

It is well known that the university students and student athletes in particular face a unique set of stressors during their college years [1]. Other than the challenges associated with their athletic participation, they also share similar concerns about academic success, financial issues, an active social life, etc. In addition to those concerns, in many cases, they have to deal with worrying about being sidelined (or Red-shirted), resolve possible conflicts with their coaches and peers, adjust both to a new team and a college environment while dedicating most of their time to practice. Gaston and Hu stated six distinctive challenges that the student athletes face during their academic years: 1) Balancing athletic and academic responsibilities, 2) balancing social activities with academic responsibilities, 3) balancing athletic success and failures with emotional stability, 4) balancing physical health and injury with the need to continue competing, 5) balancing the demands of relationships with entities such as coaches, teammates, parents and friends and; 6) addressing the termination of one’s college athletic career [2]. Watson et al. (2005) also stated the possible causes of stress as; issues related to adjustment problems, emotional concerns, and psychological distress as a result of their participation.

Student-athletes also experience numerous stressors throughout the course of an academic year such as academic demands and pressures, family dynamics, financial constraints, and the social pressures of being a young adult in additional to extracurricular stressors influence by their sport [3, 4]. These stressors include subordinate stresses of playing with other athletes, changing of dietary content and habits, training and meeting schedules, affect the team functioning as a whole and each athlete’s own individual functioning, and importantly, sleep pattern disruption due to travel schedule and overt time zone changes which disrupt circadian rhythms [5].

Regardless of the physical condition, personality or character, there is no doubt that the effects of stress and especially chronic stress experienced by student athletes adversely affects their physiology, mental state and emotions to some degree [4]. One of the major factors that contributes to stress imparted on college athletes is due to airplane travel. It has been argued that airplane travel affects athletic performance in several different aspects [6].

1.1 Travel and stress response

Travelling at altitude for 3 or more hours regardless of direction has been shown to affect the body in a way that results in a decline in oxygen saturation, an increase in glucocorticoid levels and short term significant decline in aerobic performance [7, 8]. Regulatory agencies have set guidelines for airline cabin pressurization to meet a maximum altitude of 2440 m (8000 ft) and average cabin pressures are usually set at 1520–1828 m, which is equivalent to an inspired oxygen pressure (PO2) of about 130 mm Hg (as compared to 159 mm Hg at sea level). Clark et al. showed that oxygen saturation measured by pulse oximetry in elite athletes, significantly decreased after 3 h flight time, and that these decreases in oxygen saturation levels reflect the acute exposure to hypoxia at altitude (2007). Relatively lower levels of oxygen in the cabin producing hypoxic effect and traveling to different time zones, changing circadian rhythm were largely accepted as the main factors that might affect athletic performance [9]. Additionally, not being able to move and sitting for prolonged times during the flight was theorized to cause lethargy [6]. Therefore, time spent on long flights might be considered as a factor for the overall stress response to the season.

Studies have also shown that not only crossing the time zones but also direction of the travel is important for athletic performance as eastward travel was shown to be detrimental for performance [10]. Continuous easterly trans-Pacific travel with little or no recovery time is shown to misalign circadian rhythms, to cause loss of appetite, to disrupt concentration, and deprives the athletes of much needed sleep and reduced-stress rest [11]. It has also been demonstrated that such psychogenic stressors can result in cardiovascular diseases, body fat deposition changes, a decrease in physical and mental performance, as well as future metabolic dysfunctions [12, 13].

Athletes who compete for the University of Hawai’i Hilo, and the men’s basketball in this particular study, are subjected to well above normal physiological and psychogenic stressors with their exposure to significant amounts of easterly-bound air travel that include time zone and seasonal changes throughout one season. Though data is difficult to decipher, it may be that men’s basketball players of UHH travel farther than any other athletes who participate in any other collegiate program in the country. It is hypothesized that the prolonged intermittent stressors that these athletes face through the duration of one season has resulted in negative physiological adaptations.

Therefore, the aim of this study is to assess the physiological, anthropometrical and biometric markers of men’s basketball team who plays most of their away matches after several hours of eastward flight.

2. Methods

2.1 Participants

During this study, each season averaged 112.7 days with 24.4 of those days in which the teams spent in travel. The athletes were exposed to an estimated 16,115 miles of air travel through the course of the season, with 15,195 miles flying east to the mainland United States from Hawai’i, and 924 miles were inter-island travel from the Big Island.

The amount of short-flight (216 miles) and over-seas flight (the shortest flight being 2,556 miles to Los Angeles) that these athletes must travel exposes them to a larger amount of air travel, especially easterly, than any other university that competes in the same division.

Thirty-six Division II travel-team university men basketball players (MBB) (age $=$ 21.32 y $\pm$ 1.7 y; body weight 98.99 kg $\pm$ 16.15, total body fat $=$ 16.81%, and a control group of 37 age-matched men full-time university students (CT) who were not participants in collegiate athletics, (age $=$ 22.67 y $\pm$ 1.2 y; body weight $=$ 79.51 kg $\pm$ 17.1, total body fat $=$ 20.37% $\pm$ 6.1 were included in the present study. The CT subjects were recruited from the same academic departments as the MBB, and the same courses that the MBB were enrolled, whenever possible. Subjects were informed of the study protocol and signed an informed consent before initial measurements were commenced. The Institutional Review Board of the University of Hawai’i system approved this study over five years.

2.2 Experimental design

The MBB and CT subjects were examined immediately before the men’s basketball team competed in their first seasonal game. Though circumstances negated controlled testing times, a majority of the subjects were measured between 10 AM HST and 12 PM HST, and each subject was re-measured immediately post-basketball-season (T2) at the same time of day that he was measured at T1, and was asked to replicate the same pre-testing sleeping and eating patterns exhibited pre-T1.

2.3 Anthropometric measurements

Height and weight were measured for T1 and T2 using digital scale and stadiometer (Seca 769, Hamburg, Germany). Circumference measurements were performed with a Seca 200 tape measure in front of a mirror and with two technicians present to assure accuracy. Thigh circumference on the dominant side non-weight-bearing appendage was obtained at the mid-point between the superior patella and the greater trochanter. Waist circumference was obtained at the mid-point between the superior iliac crest and the inferior point of the costal cartilage, measured horizontally upon expiration. Hip circumference was obtained at the level of the greater trochanters with modulations made to include the largest horizontal circumference.

2.4 Body composition and bone density measurements

Body composition analyses and bone mineral density measurements were obtained via a GE Prodigy Lunar dual energy X-ray absorptiometry unit (DXA-GE Medical Systems Luna, Madison) with enCORE software (v. 16.2). The scanner was calibrated before each data collection trial. Each participant completed a whole-body DXA scan that provided a three-component analysis of body composition (Kendler et al., 2013). Total and regional bone mineral densities and lean and fat mass depositions were assessed, providing measurements of percent body fat and lean mass for total body and regional segments of arms, legs, and trunk. Participants wore light clothing (shorts or tights and t-shirt; the similar pieces clothing was worn by participants for T1 and T2), without any metallic objects, and were positioned in a supine position with hands by the sides in prone position.

2.5 Heart rate and hemostatic measurements

Blood pressure and heart rate measurements were obtained via the following protocol: subjects and controls rested in supine position for 10 min before first measurement. Blood pressure and heart rate were measured with a fully automatic monitor (OMRON M4-1 IntelliSense) after the initial rest period, with repeated measures made after 3 min. Measurements of DBP, SBP and HR within 5% difference were averaged; measurements outside of 5% required a re-measure after another 3 min rest period. On several occasions it was necessary to repeat the resting period multiple times to obtain final measurements.

2.6 Countermovement vertical jump

Countermovement vertical jump, using a Vertec device (JumpUSA, Sunnyvale, CA, USA) was performed to measure vertical jump capabilities. Subjects stood with feet hip width apart directly under the stratified Vertec ${}^{\@setsize{\scriptsize}{8pt}{\viipt}{\@viipt}\textregistered}$ vanes and performed a rapid countermovement jump, reaching the highest possible vane with the dominant hand. A two-minute rest was taken between attempts and the highest vertical jump was registered.

2.7 Isokinetic knee extension and knee flexion maximum strength

Maximum voluntary dominant leg isokinetic knee extension and knee flexion strengths were determined concentrically using a Cybex Humac Norm Isokinetic Dynamometer. Settings for the instrument were 120 degrees range of motion, at 30 ${}^{\circ}$ /s. The subjects were instructed to perform several sub-maximal knee extensions followed by knee flexions on the two-way isokinetic dynamometer for familiarization and warm-up. After three minutes’ rest, the subjects perform three consecutive maximum voluntary concentric knee extensions and flexions. Again, the subjects rested for three minutes followed by a repeat testing bout of three concentric extensions and flexions. The maximum flexions and extensions, measured in Newton/meters, were determined from the first and second trials, and if there was an increase in any measurement from the first to the second trials, a third trial was performed. Maximum concentric knee extension and flexion measurements were recorded for data analysis.

Table 1
Men’s basketball team (MBB) descriptive characteristics ( $n=$ 36)

Variable	T1	T2
Age (years)	21.32 yr $\pm$ 1.7	21.32 $\pm$ 1.7
Height (cm)	191.43 cm $\pm$ 9.02	191.47 cm $\pm$ 9.03
Body weight (kg)	98.99 kg $\pm$ 16.15	94.65 kg* $\pm$ 14.77
Total body fat (%)	16.45% $\pm$ 4.43	18.60%* $\pm$ 5.17
Visceral trunk fat (%)	17.61% $\pm$ 4.17	20.23%** $\pm$ 5.73

T1 $=$ pre-season; T2 $=$ post-season; means and SDs presented; *significant difference at $p\leqslant$ 0.05; **significant difference at $p\leqslant$ 0.01.

Table 2

Student controls (CT) descriptive characteristics ( $n=$ 37)

Variable	T1	T2
Age (years)	22.67 yr $\pm$ 1.2	22.67 yr $\pm$ 1.2
Height (cm)	175.95 cm $\pm$ 7.22	176.11 cm $\pm$ 7.22
Body weight (kg)	79.51 kg $\pm$ 17.1	79.35 kg $\pm$ 18.2
Total body fat (%)	20.37% $\pm$ 6.1	19.62% $\pm$ 5.7
Visceral trunk fat (%)	22.36% $\pm$ 6.4	21.31% $\pm$ 6.3

T1 $=$ pre-season; T2 $=$ post-season; means and SDs presented; *significant difference at $p\leqslant$ 0.05.

2.8 Cortisol

Saliva cortisol levels were obtained by saliva collections using the drool-spit method. The subjects were instructed to refrain from eating, drinking, or oral hygiene procedures for at least 1 hour prior to the collection. Each subject was instructed to spit whole saliva (WS) into a 50 ml sterile Falcon ${}^{\@setsize{\scriptsize}{8pt}{\viipt}{\@viipt}\textregistered}$ tube, with at least 10 ml received from each subject, and was analyzed for cortisol levels at T1 and T2 testing sessions. Saliva samples were stored at $-$ 80 ${}^{\circ}$ C until assayed using commercially available cortisol EIA kits (Salimetrics, State College, PA, USA). The CV% for both assays was $<$ 7%.

2.9 Statistical analyses

MBB and CT descriptive statistics are presented in the form of means and standard deviations for T1 and T2 immediate pre-season and immediate post-season values in the form of means and standard deviations (Tables 1–4). Individual independent $t$ -tests were used to evaluate differences between T1 and T2 results for further anthropometric data, heart rate, blood pressure, and salivary cortisol data performance tests (Tables 5–8), and bone mineral densities (Tables 9 and 10). Statistical significance was set at $p\leqslant$ 0.05, and $p\leqslant$ 0.01 is noted when applicable. All data were reported as means $\pm$ SD.

Table 3
Men’s basketball team (MBB) descriptive characteristics ( $n=$ 36)

Variable	T1	T2
Thigh circumference (cm)	58.04 cm $\pm$ 8.01	57.5 cm $\pm$ 3.11
Hip circumference (cm)	98.2 cm $\pm$ 9.93	96.89 cm $\pm$ 11.43
Waist circumference (cm)	86.89 cm $\pm$ 6.72	89.45 cm* $\pm$ 4.73
Waist/hip ratio (%)	87.6% $\pm$ 4.54	92.32%** $\pm$ 4.78

T1 $=$ pre-season; T2 $=$ post-season; means and SDs presented; *significant difference at $p\leqslant$ 0.05; **significant difference at $p\leqslant$ 0.01.

Table 4

Student controls (CT) descriptive characteristics ( $n=$ 37)

Variable	T1	T2
Thigh circumference (cm)	55.71 cm $\pm$ 4.7	55.96 cm $\pm$ 5.1
Hip circumference (cm)	93.06 cm $\pm$ 7.9	92.67 cm $\pm$ 7.7
Waist circumference (cm)	84.87 cm $\pm$ 8.3	83.77 cm $\pm$ 8.1
Waist/hip ratio (%)	91.19% $\pm$ 3.3	90.41% $\pm$ 3.3

T1 $=$ pre-season; T2 $=$ post-season; means and SDs presented; *significant difference at $p\leqslant$ 0.05.

Table 5

Men’s basketball team (MBB) BP, HR, cortisol ( $n=$ 36)

Variable	T1	T2
Systolic blood pressure (mm/Hg)	123.97 mg/Hg $\pm$ 3.31	126.87 mm/Hg* $\pm$ 4.47
Diastolic blood pressure (mm/Hg)	66.68 mg/Hg $\pm$ 4.64	71.86 mm/Hg** $\pm$ 5.19
Mean arterial pressure (mm/Hg)	85.77 mg/Hg $\pm$ 4.84	90.21 mm/Hg** $\pm$ 4.78
Resting heart rate (bpm)	53.25 bpm $\pm$ 4.81	57.04 bpm* $\pm$ 4.93
Cortisol (nmol/L)	5.7 nmol/l $\pm$ 2.2	13.2 nmol/l** $\pm$ 6.7

T1 $=$ pre-season; T2 $=$ post-season; means and SDs presented; *significant difference at $p\leqslant$ 0.05; **significant difference at $p\leqslant$ 0.01.

Table 6

Student controls (CT) BP, HR, cortisol ( $n=$ 37)

Variable	T1	T2
Systolic blood pressure (mm/Hg)	122.92 mm/hg $\pm$ 7.7	120.21 mm/hg $\pm$ 6.8
Diastolic blood pressure (mm/Hg)	67.85 mm/hg $\pm$ 5.4	65.12 mm/hg $\pm$ 5.2
Mean arterial pressure (mm/Hg)	86.19 mm/hg $\pm$ 5.7	83.47 mm/hg* $\pm$ 4.3
Resting heart rate (bpm)	62.88 bpm $\pm$ 7.5	63.07 bpm $\pm$ 7.2
Cortisol (nmol/L)	8.5 nmol/l $\pm$ 2.7	10.7 nmol/l $\pm$ 2ta.9

T1 $=$ pre-season; T2 $=$ post-season; means and SDs presented; *significant difference at $p\leqslant$ 0.05.

Table 7

Men’s basketball team (MBB) isokinetic strength and vertical jump ( $n=$ 36)

Variable	T1	T2
Right knee extension (Nm)	209.83 Nm $\pm$ 61.79	201.36 Nm $\pm$ 59.63
Right knee flexion (Nm)	141.97 Nm $\pm$ 40.91	133.39 Nm* $\pm$ 44.52
Right knee flexion/extension(%)	67.65% $\pm$ 12.37	66.19% $\pm$ 11.31
Left knee extension (Nm)	188.69 Nm $\pm$ 63.11	185.17 Nm $\pm$ 50.01
Left knee flexion (Nm)	142.19 Nm $\pm$ 47.67	133.33 Nm* $\pm$ 27.74
Left knee flexion/extension (%)	75.35% $\pm$ 13.53	72.00%** $\pm$ 6.82
Vertical jump (cm)	75.69 cm $\pm$ 6.87	71.21* $\pm$ 7.22

T1 $=$ pre-season; T2 $=$ post-season; means and SDs presented; *significant difference at $p\leqslant$ 0.05; **significant difference at $p\leqslant$ 0.01.

Table 8

Student controls (CT) isokinetic strength and vertical jump ( $n=$ 37)

Variable	T1	T2
Right knee extension (Nm)	196.97nm $\pm$ 24.7	208.83 nm $\pm$ 27.7
Right knee flexion (Nm)	112.13nm $\pm$ 19.7	116.47 nm $\pm$ 20.9
Right knee flexion/extension (%)	56.92% $\pm$ 2.9	55.77% $\pm$ 2.9
Left knee extension (Nm)	183.41nm $\pm$ 22.3	180.23 nm $\pm$ 25.8
Left knee flexion (Nm)	112.53nm $\pm$ 16.9	108.63 nm $\pm$ 17.7
Left knee flexion/extension (%)	61.35% $\pm$ 3.2	60.27% $\pm$ 2.7
Vertical jump (cm)	55.77 cm $\pm$ 9.7	57.15 cm $\pm$ 10.1

T1 $=$ pre-season; T2 $=$ post-season; means and SDs presented; *significant difference at $p\leqslant$ 0.05; **significant difference at $p\leqslant$ 0.01.

3. Results

Measures of body composition indicated that throughout the basketball season, the total percent body fat, visceral fat increased significantly despite the significant decrease in body weight for MBB but not for the CT group (Tables 1 and 2, $p\leqslant$ 0.05).

Isokinetic strength measurements for this investigation are presented in Tables 7 and 8. Most notable changes were shown in the decrease in both right knee flexion and left knee flexion data in MBB ( $p\leqslant$ 0.01). These significant diminishments, in turn, significantly reduced both right knee and left knee flexion/extension ratios (Table 7) despite the insignificant changes for left and right knee extensor force; 59.4% to 63.8% and 77.47% to 71.96%, respectively (Table 7). Vertical jump performance for also decreased significantly for MBB and not for CT. Though CT’s VJ measurements increased from 55.7 cm to 57.15 cm, this increment was deemed not statistically significant (Table 7).

MBB also exhibited significant gains in waist circumference, and waist/hip ratio (WHR) ( $p\leqslant$ 0.01), while the CT exhibited no changes in either measures (Tables 3 and 4).

For the MBB, significant gains in resting heart rate, systolic and diastolic blood pressures, and mean arterial blood pressure (85.7 to 90.2 mmHg, $p\leqslant$ 0.01) (Table 5) were detected, while no such changes were detected for the CT (Table 6).

MBB resting salivary cortisol measures rose significantly (5.7 to 13.2 nmol/l, Table 5), while CT cortisol measures did not change significantly (Table 6).

For both MBB and CT groups, bone mineral density measurements of total body, lower body, trunk, and pelvis, did not change, remaining remarkably identical for each measurement for each group from T1 to T2 (Tables 9 and 10).

Table 9
Men’s basketball team (WBB) bone density ( $n=$ 36)

Variable	T1	T2
Total body bone density (g/cm ${}^{2}$ )	1.442 $\pm$ 0.15	1.468 $\pm$ 0.11
Lower body bone density (g/cm ${}^{2}$ )	1.760 $\pm$ 0.09	1.790 $\pm$ 0.10
Trunk bone density (g/cm ${}^{2}$ )	1.199 $\pm$ 0.08	1.232 $\pm$ 0.08
Pelvis bone density (g/cm ${}^{2}$ )	1.565 $\pm$ 0.09	1.596 $\pm$ 0.08

T1 $=$ pre-season; T2 $=$ post-season; means and SDs presented.

Table 10

Student controls (CT) bone density ( $n=$ 37)

Variable	T1	T2
Total body bone density (g/cm ${}^{2}$ )	1.296 $\pm$ 0.13	1.295 $\pm$ 0.14
Lower body bone density (g/cm ${}^{2}$ )	1.535 $\pm$ 0.21	1.536 $\pm$ 0.27
Trunk bone density (g/cm ${}^{2}$ )	1.054 $\pm$ 0.21	1.052 $\pm$ 0.20
Pelvis bone density (g/cm ${}^{2}$ )	1.320 $\pm$ 0.24	1.321 $\pm$ 0.24

T1 $=$ pre-season; T2 $=$ post-season; means and SDs presented.

4. Discussion

The present study investigated the effects of a full season on physiological, anthropometrical, biometric markers, strength and power of men’s collegiate basketball team who play their matches after a relatively long (up to 6 h) eastward flight. To our knowledge, this is the first study to attempt to quantify the changes in above-mentioned markers during a Division-II Basketball Season. Studies have shown that lower body strength and power performance should be maintained during a season via proper resistance training (RT) sessions as they are highly correlated with playing time [14, 15]. It was also observed that even without RT, basketball players in earlier studies were able to maintain their strength and speed [14, 16]. Players in this study, on the other hand, despite regularly having RT sessions (2 times/week), had a significant decrease in right and left knee flexors isokinetic strength.

Although the results obtained from this study might not be enough to explain the factors that caused the diminishment of the knee flexor strength, we think that the reason for that might be related to their training programs on top of flight related stress.

Sport of basketball involves activities such as vertical jump, landing and change of direction which are predominantly knee extensor movements [17, 18, 19]. Although RT program designed for basketball players in this study included knee flexor movements such as leg curls and stiff legged deadlifts, in order to improve the performance of movements related to basketball, a higher number of knee extensor exercises such as leg press, barbell Front Squat and forward lunges were performed during the RT sessions. Moreover, plyometric drills such as box jumps and bounding drills that the players performed during the basketball practice sessions also involves a higher activation the Quadriceps. For those reasons, it might have been possible for the players to maintain the isokinetic knee extensor strength but not the knee flexor strength.

Although diminishment in the left extensor strength was not statistically significant (188.69 Nm $\pm$ 63.11 to 185.17 Nm $\pm$ 50.01), the significant decrease in vertical jump height, as a measure of power, might also be attributed to the decreased knee extensor strength post season. No difference was found between pre-post right knee extensor strength.

One of the major findings of this study was that cortisol levels were higher as well as total body and trunk fat % despite the decrease in bodyweight post season. It is possible that an influential reason for higher saliva levels cortisol may be directly linked to eastern multi zonal flights. Cortisol has a very distinct circadian rhythm with acrophase occurring shortly after sunrise with diminishment throughout the day with nadir generally at sunset [20]. Eastward travel through several time zones are argued to cause disruptions to chronobiology of the human body with sunrise and daily activity commencing hours earlier than the home time zone. This, significantly affects the circadian cycle, and may cause an earlier and exaggerated rebound effect [11]. The stress on the Suprachiasmatic nuclei (SCN) of the hypothalamus which are caused by the input changes from retinohypothalamic tract after eastward travel might also contribute to this increase in cortisol levels thus trunk visceral fat levels. Furthermore, interviews with the players revealed that their sleeping patterns were also disturbed after long hours of air travel. In some cases, particularly during night games, players had to perform at a time when they are supposed to be sleeping or resting because of the time zone changes.

In addition to time zone changes, being exposed to hypoxic environment in the cabin, loud flight noise, limited movement capability during flight might have all contributed to sleep disruptions which might have affected athletic performance [21]. DXA trunk fat data, waist circumference data and waist to hip ratio (WHR) data all indicated an increase in central adiposity which also possibly might be a side effect of prolonged high cortisol levels.

It must be also noted that over the 5-year period of this study, MBB program had a record of 66 wins – 66 losses. What is interesting was that home record was 49–28 whereas Road was 17–38. Since the teams MBB play at home and on the road were usually quid per quo basis, MBB’s road schedule was not competitively more daunting than the home schedule.

Systolic, diastolic, mean arterial pressures as well as the resting heart rate were all significantly increased post season. These results might reflect the challenges student athletes encounter during long eastward air travel, competition/academic influences, change in the environment and/or combination of all those factors.

On the other hand, it is also our understanding that Cortisol awakening response (CAR) – a natural metabolic response initiated by negative cognitive-emotional processes that are not necessarily related to athletic competition might also be an additional factor for this increase among the players during a travel heavy season [22]. Repeated losses on the road against teams that MBB, beat intermittently at home, might have caused players to experience a downward spiral of events which might cause mild depression and loss of motivation which can also stimulate glucocorticoid production as well. In other words, lack of winning may have perpetuated a stress response separate from the choronobiological response.

4.1 Limitations

Throughout this study, there were several variables that were beyond the parameters of control, thus limiting interpretation. These limitations included the inability to test various biological markers related to stress. Although the equipment and facilities used during this study allowed for cortisol level testing via saliva collection, information of other stress related markers such as Corticotrophin Releasing Hormone (CRH) and Adrenocorticotropic Hormone (ACTH) could not be collected. CRH is found in the hypothalamus and signals the release of ACTH from the anterior pituitary gland. As ACTH then promotes a rise in the synthesis of glucocorticoids, this would have provided more in depth information on the body’s response to prolonged intermittent stress.

We also suggest the future researchers in their prospective studies to consider the volume of knee extensor exercises vs. knee flexor exercises in players’ training programs and possibly equate the volume or increase number of hamstring exercises in their program as Quadriceps is more active than the hamstring muscle group especially during stretch shortening cycle activities in Basketball such as jumping and changing direction [18]. This could potentially decrease the possibility of hamstring injuries by increasing the Hamstrings/Quadriceps strength ratio and also help to identify the actual reason for the diminishment of knee flexors in this study [23, 24].

Furthermore, during the isokinetic strength measurements, it was assumed that the players were performing at their maximums in this study. It should also be taken into consideration that these performances can be affected by psychological states such as anxiety, motivation and perceived rate of exertion etc. [25, 26]. These states can also be measured and controlled for the future studies by using questionnaires to make sure that the players are in similar psychological states.

Other variables that were beyond the control of the study were travel schedules while the players were on the road. While the mileage accounted for in this study was strictly based on air travel, a team report, conducted post season, found that additional long travel hours by vehicle occurred while away. Other factors while on the road such as the pressure of keeping up with academic course work between games, changes in dietary habits and abnormal sleep schedules were discussed as additional stressors in the team report. Disrupted circadian rhythms may result in an unbalance in hormonal levels, including glucocorticoids. However, because there was a lack of control over and inability to measure these factors, they are considered to be unquantifiable data.

4.2 Practical applications

It is important for coaches and athletic support teams to understand the effects of east-zone travel, jet lag and travel fatigue on the players, thus it might be critical to develop strategies that limit the negative outcomes afforded by these effects. Forbes-Robertson et al. has suggested countermeasures to provide some practically applied methods of implementing a travel management program for athletic teams which include a pre-flight plan. Mimicking the destination’s sleep pattern as much as possible and adopting modified training routines with lower volume and intensity before travel to reduce sleep debt are practical ways to minimize the travel stress [11]. In-flight plan would be modulating the activities during flight that can minimize discomfort and accentuate relaxation. Adjusting all time devices to the destination time zone at boarding, creating a comfortable environment possible by using pillows, eyeshades, ear plugs or noise cancelling listening devices are all practical ways that can aid the athlete. Eating as closely to the destination schedule as possible which may mean having athletes bring aboard their own meals to control eating times and staying hydrated are also very important strategies to be able adjust to the destination’s time zone according to Samuels [9]. Strategic use of sedatives and/or melatonin is also recommended either during or after the flight depending on the time zone change [11].

Footnotes

Conflict of interest

All authors declare no conflict of interest.

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More stress for the eastward travelling student athlete: A preliminary analysis

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

1.1 Travel and stress response

2. Methods

2.1 Participants

2.2 Experimental design

2.3 Anthropometric measurements

2.4 Body composition and bone density measurements

2.5 Heart rate and hemostatic measurements

2.6 Countermovement vertical jump

2.7 Isokinetic knee extension and knee flexion maximum strength

Table 1 Men’s basketball team (MBB) descriptive characteristics ( n = 36)

2.9 Statistical analyses

Table 3 Men’s basketball team (MBB) descriptive characteristics ( n = 36)

Table 9 Men’s basketball team (WBB) bone density ( n = 36)

4.1 Limitations

4.2 Practical applications

Footnotes

Conflict of interest

References

Table 1
Men’s basketball team (MBB) descriptive characteristics ( $n=$ 36)

Table 3
Men’s basketball team (MBB) descriptive characteristics ( $n=$ 36)

Table 9
Men’s basketball team (WBB) bone density ( $n=$ 36)