Journal of Exercise Physiologyonline

October 2018Volume 21 Number 5

Editor-in-ChiefTommy Boone, PhD, MBAReview BoardTodd Astorino, PhDJulien Baker, PhDSteve Brock, PhDLance Dalleck, PhDEric Goulet, PhDRobert Gotshall, PhDAlexander Hutchison, PhDM. Knight-Maloney, PhDLen Kravitz, PhDJames Laskin, PhDYit Aun Lim, PhDLonnie Lowery, PhDDerek Marks, PhDCristine Mermier, PhDRobert Robergs, PhDChantal Vella, PhDDale Wagner, PhDFrank Wyatt, PhDBen Zhou, PhD

Official Research Journal of the American Society of

Exercise Physiologists

ISSN 1097-9751

Official Research Journal of the American Society of Exercise Physiologists

ISSN 1097-9751

JEPonline

Lipid Peroxidation, Nerve Conduction Velocity and Physical Performance among Male University Athletes

Orachorn Boonla1,2, Piyapong Prasertsri1,2

1Faculty of Allied Health Sciences, Burapha University, Chonburi, Thailand, 2Exercise and Nutrition Sciences and Innovation Research Group, Burapha University, Chonburi, Thailand

ABSTRACT

Boonla O, Prasertsri P. Lipid Peroxidation, Nerve Conduction Velocity and Physical Performance among Male University Athletes. JEPonline 2018;21(5):184-197. The purpose of this study was to determine plasma lipid peroxidation, nerve conduction velocity, and physical performance in male university athletes engaged in different sports classifications. A cross-sectional study was conducted in 41 male athletes at Burapha University aged 18 to 30 yrs. Subjects were divided into 4 groups according to sports classification: low static moderate dynamic (LSMD) group, low static high dynamic (LSHD) group, moderate static moderate dynamic (MSMD) group, and high static low dynamic (HSLD) group. Plasma malondialdehyde (MDA), nerve conduction velocity, and physical performance were determined among groups accordingly. There was no significant difference in plasma MDA concentration between groups. Sensory nerve conduction velocity of the median nerve in the LSMD group was significantly higher than in the HSLD group (P<0.05); whereas, motor nerve conduction velocity did not reach a statistical significance. Flexibility in the MSMD group was significantly higher than in the LSMD, LSHD, and HSLD groups (P<0.05). However, strength, endurance, and balance did not indicate a significant difference between groups. This study suggests that sensory nerve conduction velocity and flexibility differed among male university athletes engaged in different sports classifications, while lipid peroxidation, motor nerve conduction velocity, and other physical performance indicators were similar.

Key Words: Lipid peroxide, Nerve Conduction, Physical Performance, Sports

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INTRODUCTION

Aerobic and anaerobic exercises are terms of activity characterized by muscle metabolism type (28). The terms dynamic and static exercise are other classifications characterized by the mechanical action of the muscles involved (13). Dynamic and isotonic exercise implicate changes in muscle length and joint movement with rhythmic contractions that generate a relatively lesser intramuscular force. Meanwhile, static or isometric exercise implicates the development of a relatively great intramuscular force with slight or no change in muscle length or joint movement (24).

It is well known that different types of exercise training contribute to differences in physical performance (34). It has been reported that nerve conduction velocity is associated with physical performance (31,37) and is dissimilar among sports disciplines (7,35). Borges and colleagues (7) have reported that strength athletes possess higher motor nervous conduction velocity than endurance athletes. There are factors influencing nerve conduction velocity, such as muscle and body temperature, heart rate (HR), and oxidative stress (8,11,33). Increased muscle and body temperature, increased HR or decreased oxidative stress have been reported as contributing to improving physical performance (8,11,33).

To our knowledge, studies investigating physical performance along with nerve conduction velocity and oxidative stress among practitioners training with different levels of static and dynamic components are to date inadequate. The purpose of this study was to determine plasma lipid peroxidation, nerve conduction velocity, and several types of physical performance in university athletes engaged in different sports classifications. Hence, findings from the present study may provide useful data for the design of training programs that will enhance physical performance and nerve conduction velocity while lessening oxidative stress.

METHODS

SubjectsThis study was cross-sectional in design. Male athletes from Burapha University were recruited. The inclusion criteria were as follows: (a) an athlete based at Burapha University; (b) aged between 18 to 30 years; (c) healthy of body and mind; and (d) provision of signed informed consent. The exclusion criteria consist of the following: (a) obese or underweight; and (b) a regular smoker or drinker. Prior to enrollment, all subjects were screened via physical examination including systolic and diastolic blood pressure (SBP and DBP) and heart rate (HR) along with a health questionnaire form that was applied to examine the subjects’ illness history, sports and exercise participation history, injury history, and supplementation intake history.

Ethical Statement

Prior to signing a consent form, all subjects were informed of their role in the study. The consent form and the study protocols in this study were in accordance with the ethical standards of the Human Ethics Committee of Burapha University (approval no. 18/2561), as well with the 1964 Helsinki declaration and its later amendments.

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Procedure

Forty-one male subjects were enrolled and divided into 4 groups according to sports classification (24): (a) low static moderate dynamic (LSMD) group (n = 8); (b) low static high dynamic (LSHD) group (n = 20); (c) moderate static moderate dynamic (MSMD) group (n = 4); and (d) high static low dynamic (HSLD) group (n = 9).

The LSMD sports group consisted of volleyball (n = 3), softball (n = 1), table tennis (n = 1), and handball (n = 3). The LSHD sports group consisted of soccer (n = 13), futsal (n = 6), and badminton (n = 1). The MSMD sports group consisted of long jump (n = 1), rugby (n = 2), and sprinting (n = 1), and the HSLD sports group consisted of taekwondo (n = 3), weight-lifting (n = 5), and karate (n = 1). Post enrollment, subjects were submitted to a single determination of variables that included marker of lipid peroxidation in plasma, nerve conduction velocity, and physical performance. In addition, the subjects’ maximal oxygen consumption (VO2 max) and body composition were determined.

Determination of Plasma Lipid Peroxidation

Lipid peroxidation was determined by MDA; a marker of lipid peroxidation (38). One mL of subjects’ blood was drawn in the morning using venepuncture technique and collected in an EDTA tube. The blood was then centrifuged (Eppendorf Centrifuge 5810R, Hamburg, Germany) at 3,500 rev·min-1 at 4ºC for 10 min. The plasma was collected for determination of MDA as a thiobarbituric acid reactive substance via the spectophotometric method (25). One hundred-fifty μL of plasma was reacted with 10% trichloroacetic acid, 5 mM EDTA, 8% sodium dodecylsulfate, and 0.5 μg·mL-1 butylated hydroxytoluene. The mixture was subsequently incubated for 10 min at room temperature. Then, 6% thiobarbituric acid was added with the mixture boiled for 30 min. After cooling to room temperature, the mixture was centrifuged at 3,500 rev·min-1 at 4ºC for 5 min. The supernatant was then measured with a spectophotometer at absorbance of 532 nm (Eppendorf UV/Vis Basic BioSpectrometer, Germany). A standard curve was produced with appropriate concentrations of 1,1,3,3-tetraethoxypropane (0.1-10 μmoL·L-1).

Determination of Nerve Conduction Velocity

Nerve conduction velocity was determined in the subjects’ dominant side in both the upper and lower limbs as well as in both motor and sensory nerves using the Neuro-MEP digital EMG and EP system (Neurosoft, Russia). The motor and sensory nerves of the upper and lower limbs were accounted for, as were the median and deep peroneal nerves which are mixed nerves. The subjects rested in the supine and supination position in a quiet room (temperature 26.88 0.71 ºC, humidity 48.78 5.11 %).

In the determination of the motor nerve conduction velocity of the upper limbs, stimulation was applied at three distinct points: the wrist, elbow, and arm, with the stimulating electrode positioned 2-cm above the wrist-crease and under the bicipital aponeurosis and bicipital groove. Stimulus intensity was 10 mA with a duration of 0.2 ms. For sensory nerve conduction velocity of the upper limbs, stimulation was applied at the wrist, with the stimulating electrode positioned at the midline of the wrist, 14-cm above the proximal phalanx

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of the middle finger (above the pisiform bone). Stimulus intensity was set at 2 mA at a duration of 0.1 ms.

For motor nerve conduction amid velocity of the lower limbs, stimulation was applied at three distinct points: the ankle, fibula head, and popliteal fossa with the stimulating electrode positioned on the midline between malleoli tops, under the head of the fibula, and popliteal space. Stimulus intensity was 25 mA and stimulus duration was 0.2 ms. For sensory nerve conduction velocity of the lower limbs, stimulation was applied at the ankle, with the stimulating electrode positioned on the dorsal surface of the foot, 8-cm below the midline between the most prominent parts of the malleoli. Stimulus intensity was set at 2 mA at a duration of 0.1 ms.

Determination of Physical Performance

Muscle StrengthMuscle strength was determined via leg strength using a back and leg dynamometer (T.K.K. 5102 Back.D, Takei, Japan). The subjects were instructed to stand erect with the knees bent while grasping hand rests at the appropriate height. Then, the subjects lifted the handle of the dynamometer and straightened their legs with maximal effort (16). The leg muscle strength test was repeated over 2 trials, with a 30-sec rest in between. The best value in kg units was reported as muscle strength.

Muscle EnduranceMuscle endurance test was determined via the bench-press method following the standard YMCA test (15). After a warm-up of subjects’ preference, each subject was set in the supine position and a 36-kg barbell was placed on the chest with the hands grasping the bar at a comfortable position, which was typically 10 to 20 cm beyond shoulder width. With cadence set at 30 rev·min-1 using a metronome, the bar was either raised or pressed with each beat. The subject was instructed to maintain a controlled pace throughout the test. The test was terminated when the subject could no longer lift the bar or could not maintain cadence. The number of repetitions performed in full range of motion in accordance with cadence was reported as muscle endurance.

FlexibilityFlexibility was determined via the sit-and-reach test (6). A standard sit and reach box (Baseline evaluation instruments, Fabrication Enterprises Inc., USA) was placed on the floor. The subjects sat on the floor barefoot and fully extended the knees so that the soles of the feet were flat against the end of the box. Then, the subjects extended the arms forward, placing one hand on top of the other. With palms down, the subjects reached their hands forward along the measuring scale of the box as far as possible without bending the knees. The test was repeated over 2 trials with a 30-sec rest in between. The best reach distance in cm was reported as the flexibility outcome.

Weight-Bearing BalanceThe weight-bearing balance test was determined using the E-LINK Dual Axis ForcePlate System (Biometrics Ltd., UK). In this test, the symmetrical weight distribution in both anterior-posterior (front/back) and medial-lateral (left/right) axes were quantified simultaneously. The subjects were instructed to stand barefoot on the force plates (medial arch of feet placed over

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the gap between front and back force plates). Then, they were instructed to bend the whole body to the front, left, back, and right as far as possible with the feet attached to the force plates with the knees, hips, and trunk straightened. This test measured fluctuations in weight distributed over the force plates. Analysis included the average % deviation from the center, thus documenting the symmetry of the subjects’ stance as well as the standard deviation %, documenting stability. Data were reported as dual axis (front/back and left/right) and single axis (front/back or left/right) ForcePlate peaks.

Determination of Maximum Oxygen Consumption (VO2 max)VO2 max is widely recognized as a measure of aerobic fitness (4). VO 2 max was determined on a cycle ergometer (Monark Ergomedic 828E, Sweden) according to the YMCA cycle test. Seat height was adjusted appropriately for each subject and remained constant throughout the entire test. Subjects began the test by warming up at a free workload for 3 min. Then, the workload was adjusted to 1.0 kp that was increased every 3 min depending on subject’s HR. The test was designed to include three stages. However, a fourth stage was added if the subject’s HR did not exceed 75% of predicted HR (220-age). During the test, subjects were required to cycle at a fixed cadence of 50 rev·min -1. The test was terminated once the subject could not maintain cadence or the HR increased to 75% of the predicted HR. VO2 max was calculated using the program provided by ExRx.net. In this calculation, gender, weight, workload, and HR at the last two submaximal stages were utilized.

Anthropometry and Body Composition MeasurementHeight measurement was taken during inspiration using a stadiometer (Health-O-Meter ProSeries, USA). Body mass, body mass index (BMI), fat distribution, and body composition were measured in the standing position while wearing minimal clothes via a body composition analyzer (InBody 270, Korea).

Statistical Analyses

The sample size in this study was calculated from a statistical formula for comparison of the means of more than two groups. Amid calculation, α error was set at 0.05, β error was set at 0.20, and power of test was set at 0.80. Mean difference in motor nerve conduction velocity between sprint runners and non-practitioners was 9.0 m·s-1 with SD of 5.6 (7). Thus, the total sample size was 36 subjects. Data analyses were performed using IBM SPSS Statistics 21 (IBM, Armonk, NY, USA). All data were expressed as mean ± SD. One-way analysis of variance (ANOVA) and Bonferroni post hoc tests were applied to assess the differences between groups (LSMD, LSHD, MSMD, and HSLD groups). Statistical significance level was set as P<0.05.

RESULTS

Physical and Physiological CharacteristicsTable 1 shows the data concerning the physical and physiological characteristics of all the subjects. There were no significant differences in age, height, body mass, BMI, body fat percentage, fat mass, fat-free mass, water mass, protein mass, mineral mass, W/H ratio, and visceral fat level between LSMD, LSHD, MSMD, and HSLD groups. Moreover, physiological variables including VO2 max, SBP, DBP, and HR exhibited no significant variances between groups.

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Table 1. Physical and Physiological Characteristics of Subjects.Variables LSMD Group

(n = 8)LSHD Group

(n = 20)MSMD Group

(n = 4)HSLD Group

(n = 9)Age (yrs) 20.38 0.92 20.45 0.60 20.50 0.58 20.56 1.42Height (m) 1.75 0.07 1.74 0.06 1.74 0.02 1.75 0.05Body Mass (kg) 65.83 8.35 67.37 10.41 65.98 6.40 69.78 8.97BMI (kg·m-2) 21.53 2.15 22.44 3.01 21.88 2.38 22.71 2.68Body Fat (%) 15.89 5.02 16.67 6.59 14.00 1.20 14.56 5.66Fat Mass (kg) 13.23 8.93 11.81 6.17 9.20 1.16 10.43 4.97Fat-Free Mass (%) 78.08 19.25 83.34 6.58 86.05 1.22 85.44 5.62Fat-Free Mass (kg) 55.18 5.10 56.74 6.70 56.60 5.42 59.34 6.22Body Water (%) 57.26 14.11 61.08 4.89 63.05 0.88 62.63 4.21Water Mass (kg) 40.46 3.69 41.58 4.87 41.48 4.00 43.50 4.57Protein (kg) 10.98 1.00 11.29 1.34 11.33 1.07 11.83 1.27Mineral (kg) 3.75 0.42 3.87 0.52 3.78 0.33 3.99 0.40W/H ratio 0.85 0.05 0.83 0.06 0.82 0.02 0.84 0.03Visceral Fat Level 4.00 2.07 3.95 2.67 2.75 0.50 3.67 2.40VO2 max (mL·kg-1·min-1) 45.71 9.66 50.34 13.88 49.07 13.16 48.00 19.53SBP (mmHg) 129.00 4.69 126.10 13.03 125.00 11.40 127.89 7.29DBP (mmHg) 74.00 6.14 75.30 8.87 70.75 5.25 76.11 5.64HR (beats·min-1) 67.13 12.17 62.20 11.02 70.50 20.66 62.22 8.27

Data expressed as mean ± SD; BMI = Body Mass Index; W/H = Waist to Hip Circumference; VO2 max = Maximal Oxygen Consumption; SBP = Systolic Blood Pressure; DBP = Diastolic Blood Pressure; HR = Heart Rate; LSMD = Low Static Moderate Dynamic; LSHD = Low Static High Dynamic; MSMD = Moderate Static Moderate Dynamic; HSLD = High Static Low Dynamic.

Plasma Lipid PeroxidationThere was no significant difference in plasma MDA concentration between LSMD, LSHD, MSMD, and HSLD groups (see Figure 1 below).

Plas

ma

MD

A (u

M)

0

1

2

3

4

5

6

7

8

LSMD LSHD MSMD HSLD

Figure 1. Plasma Malondialdehyde (MDA) of Low Static Moderate Dynamic (LSMD), Low Static High Dynamic (LSHD), Moderate Static Moderate Dynamic (MSMD), and High Static Low Dynamic (HSLD) Groups. Data expressed as mean ± SD.

Nerve Conduction Velocity

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Table 2 presents the nerve conduction velocity among subjects comprising of the motor and sensory nerves of the upper and lower limbs. There was significantly higher sensory nerve conduction velocity in the median nerve in the LSMD group than in the HSLD group (P<0.05). Nevertheless, a statistically significant difference in motor nerve conduction velocity between groups was not indicated.

Table 2. Motor and Sensory Nerve Conduction Velocity of Subjects.Variables LSMD Group

(n = 8)LSHD Group

(n = 20)MSMD Group

(n = 4)HSLD Group

(n = 9)Motor Nerve VelocityMedian NerveElbow (m·s-1) 56.10 8.07 52.26 16.61 60.18 1.65 60.50 3.15Arm (m·s-1) 100.64 86.38 67.65 20.91 70.15 16.49 104.43

105.73Peroneus NerveHead of Fibula (m·s-1) 53.46 7.44 49.99 10.99 50.78 6.04 46.50 18.11Popliteal Fossa (m·s-1) 61.24 14.28 55.22 28.94 53.40 6.09 50.62 27.44Sensory Nerve VelocityMedian NerveWrist (m·s-1) 110.88 58.49* 88.19 76.41 135.90 127.76 62.52 21.92Peroneus NerveAnkle (m·s-1) 55.94 46.79 51.96 30.17 40.43 14.28 50.44 42.48

Data expressed as mean ± SD; LSMD = Low Static Moderate Dynamic; LSHD = Low Static High Dynamic; MSMD = Moderate Static Moderate Dynamic; HSLD = High Static Low Dynamic, *Significantly different from HSLD Group (P<0.05)

Physical PerformanceTable 3 demonstrates physical performance among subjects. There were no significant differences in muscle strength, muscle endurance, and weight-bearing balance between groups. Notwithstanding, there was significantly higher flexibility in the MSMD group as compared to the subjects’ flexibility in the LSMD, LSHD, and HSLD groups (P<0.05) (see Figure 2 below).

Flex

ibili

ty (c

m)

0

10

20

30

40

50

60

70

80

90

100

LSMD

*

LSHD MSMD HSLD

Figure 2. Flexibility of Low Static Moderate Dynamic (LSMD), Low Static High Dynamic (LSHD), Moderate Static Moderate Dynamic (MSMD), and High Static Low Dynamic (HSLD) Groups. Data expressed as mean ± SD; *Significantly different from LSMD, LSHD, and HSLD groups (P<0.05).

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Table 3. Muscle Strength, Endurance, and Weight-Bearing Balance of Subjects.Variables LSMD Group

(n = 8)LSHD Group

(n = 20)MSMD Group

(n = 4)HSLD Group

(n = 9)Muscle Strength (kg) 177.75 60.05 158.78 48.78 208.88 87.02 178.28 52.07Muscle Endurance (repetitions)

12.75 5.28 11.75 7.84 19.00 9.83 17.78 8.00

Weight-Bearing BalanceDual Axis Forceplate PeakTo Right (%) 89.75 3.96 88.50 13.75 91.50 4.73 88.25 6.34To Left (%) 88.25 6.71 90.65 6.18 92.50 5.20 89.75 4.27To Back (%) 91.13 5.28 88.80 10.11 97.25 4.86 90.00 11.01To Front (%) 87.00 10.18 86.55 11.63 89.50 2.89 83.63 7.87Single Axis Forceplate PeakTo Right (%) 89.13 10.76 91.80 8.76 95.50 4.51 81.00 18.43To Left (%) 87.75 7.70 90.20 9.76 94.25 2.06 86.13 13.50To Back (%) 89.38 11.87 87.90 11.77 94.00 4.08 90.75 6.84To Front (%) 86.63 8.93 87.95 8.28 90.50 7.85 88.00 10.64

Data expressed as mean ± SD; LSMD = Low Static Moderate Dynamic; LSHD = Low Static High Dynamic; MSMD = Moderate Static Moderate Dynamic; HSLD = High Static Low Dynamic

DISCUSSION

Previous studies (8,31,37) indicate the link between lipid peroxidation, nerve conduction velocity, and physical performance. Hence, this study determined physical performance along with plasma lipid peroxidation and motor and sensory nerve conduction velocity in male university athletes engaged in different sports classifications. We hypothesized that the athletes who regularly practiced diverse forms of static and dynamic components including LSMD, LSHD, MSMD, or HSLD may demonstrate a difference in outcome measurements.

In this study, lipid peroxidation was estimated via plasma MDA concentration. MDA is the principal and most studied product of polyunsaturated fatty acid peroxidation in cells (10). It is the most frequently used biomarker of oxidative stress in clinical investigations for many common health problems including cancer, cardiovascular, pulmonary, psychiatric, infectious, aging, and degenerative diseases (5,18). Several studies have demonstrated that high-intensity exercise causes oxidative stress relating to inflammation, tissue injury, tissue lesion, and fatigue (9,22). Our results showed no significant variance in the concentration of plasma MDA among athletes who trained differently in static and dynamic components. A lack of significant difference in plasma MDA concentration among the groups of athletes reflects that different forms of static and dynamic sports affect a similar magnitude of oxidative stress.

Although, there are several factors determining oxidative stress status in athletes including antioxidant capacity, physical activity levels, and rate of VO2 (20,39); in part, it is possible that a similarity in VO2 max may have led to similar oxidative stress levels among the athletes in this study. Moreover, it is possible that an increase will occur in the antioxidant defense system in athletes to protect the body against the adverse effects of oxidative stress as well as the generation of oxidative damage (40). Such an increase may develop similarly in all groups of athletes leading to comparable levels of oxidative stress. Our findings are consistent with the results of Naseri et al. (26) who investigated blood MDA levels in male athletes engaged in aerobic exercise training as well as anaerobic exercise training. On the other hand, a study by Hadžović-Džuvo et al. (12) reported that the level of blood MDA was

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significantly higher in basketball players compared to those playing soccer. Based on static and dynamic sports classification, basketball is categorized in the moderate static and high dynamic sport classification that calls for a higher cardiovascular demand than soccer that is categorized as a low static, high dynamic sport. Also, there are several factors that determine oxidative stress in athletes, including type, intensity, and duration of exercise training (30).

Oxidative stress can cause neurological changes by affecting neurons directly or indirectly via deleterious changes in nerve vascular supply as endothelial function (8). It has been shown to augment the conduction deficit in diabetic nerves (19). The present study investigated nerve conduction velocity of the median and deep peroneal nerves that are mixed nerves. The median nerve arises from the anteromedial and anterolateral cords of the brachial plexus and is innervated by the C6, C7, C8 and T1 nerve roots. The median nerve only provides motor function to the forearm muscles in addition to motor and sensory function to the wrists and hands (23). Median nerve mononeuropathy is the most common peripheral nerve neuropathy. The carpal tunnel is the most common site of compression (23).

The deep peroneal nerve originates from the common peroneal nerve that arises from the sciatic nerve (3). It innervates the anterior compartment muscles of the leg and the extensor digitorum brevis, and provides cutaneous and articular sensibility to portions of the foot’s dorsum. Injury to the distal portion of the deep peroneal nerve results predominantly in sensory deficits or painful neuromata (17). It has been suggested that genetic and environmental factors are important determinants of motor nerve conduction velocity (14). In the present, motor nerve conduction velocity among the athlete groups was not significant, while sensory nerve conduction velocity of the median nerve in the LSMD group was higher than in the HSLD group. Hence, based on the present data, low static sports are superior in sensibility than high static sports; or moderate dynamic sports are superior in sensibility than low dynamic sports. This may be explained by the difference in biological and environmental stimuli (27) demonstrated by the LSMD group (i.e., volleyball, softball, table tennis, and handball) who were more frequently exposed to training or competition than the HSLD group (i.e., taekwondo, weight-lifting, and karate). As a consequence, this may influence the development of the sensory nerve conductive system amid the median nerve (29).

A similarity in motor nerve conduction velocity may be partly due to a comparable modality of exercise among the athletes. Additionally, a study by Soodan and Kumar (35) reported the differences in motor nerve conduction velocity amid the ulnar and common peroneal nerves between sprinters and distance runners. A study by Borges et al. (7) did not indicate a difference in motor nerve conduction velocity amid the median and common fibular nerves between middle distance runners, sprinters, and handball players. Current data concerning motor nerve conduction velocity are rather inconsistent and arduous to elucidate. However, our data may support a possible link between oxidative stress and nerve conduction velocity in athletes.

Oxidative stress and nerve conduction velocity have been reported as being associated with physical performance (21,36). Nevertheless, we assumed to reveal differences in physical performance between groups of athletes; except for flexibility, the findings did not imply a significant variance in muscle strength, muscle endurance, and weight-bearing balance between the LSMD, LSHD, MSMD, and HSLD groups. Most groups in this study (LSHD, MSMD, and HSLD groups) were classified as the same degree of cardiovascular demand,

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i.e., moderate. This may relate to a comparable VO2 max and, thus a similar endurance performance among groups (2,32).

Although there should be differences in strength performance between low static and high static sports, this could be due to a fundamental determinant of subjects’ performance, and muscle mass that did not differ greatly (1). In addition, according to employing static and dynamic components to classify groups of athletes, it is possible that the sports variety in each group may result in a lessening of distinction of strength, endurance, and balance between groups. In fact, most sports involve both isometric (static) and isotonic (dynamic) components (24). Interestingly, flexibility was significantly higher in the subjects in the MSMD group than those in the LSMD, LSHD, and HSLD groups. Hence, the results suggest that sports equally combining static and dynamic compositions are better in terms of offering flexibility in the muscles and joints, as opposed to those sports predominantly consisting of either static or dynamic composition.

Limitations of This Study

The present study was conducted using a small sample size with unequal distribution of subjects in each group. These points may underlie the small differences in our findings. Accordingly, future studies should include a larger sample size with equally distributed subjects in each group in order to discover more variations in the outcome measurements. Moreover, future studies should be conducted in a heterogeneous population to uncover gender differences. Lastly, further exploration with regards to antioxidant capacity, that is, glutathione peroxidase, superoxide dismutase, and catalase should to be considered.

CONCLUSION

The findings of the present study suggest that male university athletes engaging in moderate static and moderate dynamic sports appear to possess greater flexibility than university athletes who participate in other sports. However, neither plasma lipid peroxidation, nor motor nerve conduction velocity differed among varying static and dynamic sports. It is also suggested that the sports variety in each group may result in a lessening of distinction of physical performance among groups of athletes.

ACKNOWLEDGMENTSThis work was supported by the Faculty of Allied Health Sciences, Burapha University, Thailand under Grant AHS 03/2561.

Address for correspondence: Piyapong Prasertsri, PhD, Faculty of Allied Health Sciences, Burapha University, 169 Longhaad Bangsaen Road, Saensook, Mueang, ChonBuri 20131, Thailand, Phone: 66 3810 3166, Email: piyapong@buu.ac.th

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