For verification of this paper, please visit on http://www.socialresearchfoundation.com/innovation.php#8

The physical characteristics play a significant role in the performance in sports. The physical characteristics are related to two areas namely the body constitution and body composition. The former deals with the structure of a supposedly unchangeable frame, while the later deals with the analysis of the existing composition or changes in composition within that frame. The bulk of shot putter, the muscularity of weightlifter and the leanness of the distance runner are a few examples of the relationship between structure and function which although lacking in quantification, are readily apparent to all who have been spectators of sports by virtue of their keen interest in the filed of games and sports. Truly speaking, human bio-type is the compound of morphological, functional and psychological characteristics. Coaches, physical education teachers, psychologists, medical experts and scholars from other fields have shown their interest in finding out relationship of factors related to their respective areas in order to help their athletes by their technical advice enabling them to further improve their performance. The scientists, however, have failed in their efforts as the new concepts have emerged out of consistent research and improved technology. Today, the concept of interaction of morphological, functional and psychological characteristics is well-recognized. It has been emphasized that in the research of athletes biotype the morphological profile (somatotype and body composition) must be related to those of functional (ergo type) and psychological (psyeho type), One’s. It is further conceived that the findings of such investigations can help in defining for each sports discipline the ideal type or champion. Body composition has been found related to performance and physical activity, in turn also effects the body composition. Studies have also been conducted to find out relationship of body composition to a number of physiological factors, but no effort seems to have been made to evaluate body composition and to find out its relationship with anaerobic work capacity and performance in the track and field events simultaneously.

Ackland T.R, et.al. (2012) The purpose of the study was to analyze the current status of body composition assessment in sport on behalf of the Ad hoc research working group on body composition health and performance, under the auspices of the I.O.C. medical commission. He found that there is no universally applicable criterion or ‘gold standard’ methodology for body composition assessment. Having considered issues of accuracy, repeatability and utility, the multi-component model might be employed as a performance or selection criterion, provided the selected model accounts for variability in the density of fat-free mass in its computation. However, when profiling change in interventions, single methods whose raw data are surrogates for body composition (with the notable exception of the body mass index) remain useful.

Battinelli (2010) The purpose of this study was to analyze the anthropometry and body composition associated with performance of university level male track and field athletes of South India. This study was conducted on 93 track and field athletes from South India, comprised of 22 sprinters, 20 middle distance runners, 16 long distance runners, 20 throwers  and jumpers, Besides height and weight, six skin folds were measured. Somatotype evaluations were made according to Carter and Heath (1990) method. BMI was calculated as body mass divided by square of height (kg/m2 ). The somatochart indicated that sprinters and middle distance runners are ectomorphic mesomorphs, long distance runners are mesomorph ectomorphs while throwers are endomorphic mesomorphs. The jumpers fell into the somatotype category of balanced mesomorphs. Among all groups body fat percent is lowest in sprinters (6.23±0.83%) and highest in throwers (7.38±0.85%). This was reflected in their endomorphic components which is lowest in sprinters (2.53±0.45) and highest in throwers (3.39±0.65). Ectomorphic component is highly marked in long distance runners (3.56±0.65) while mesomophy was highest in sprinters (4.31±0.91). Throwers have significantly higher values of skin folds than other groups. Compared to their overseas counterparts, the athletes of both track and field events in the present study exhibited greater endomorphic values.

Larsson P, Henriksson Larsen K (2008) The purpose of this study was to investigate the relationships between body composition and performance in cross-country skiing. Ten male college-aged elite cross-country skiers (17.9 yrs; S 1.0 yrs) participated in a 5.6-km cross-country skiing time trial and in dual energy X-ray absorptiometry (DXA, Lunar DPX-L, Madison, WI, USA) body composition measurements. A differential global positioning system (dGPS, GPS 12 CX, Garmin Int. Inc., Olathe, KS, USA; RXMAR 2, Aztec SA, Strasbourg, France) was used to compute speed in different sections of the course. Spearman correlation analyses were applied. Total body weight and absolute lean body mass were significantly related to final time (r = - 0.721; p < 0.05 and - 0.830; p < 0.01, respectively). Absolute lean arm mass (kg) was negatively correlated to final time (r = - 0.648; p < 0.05) and the relative lean arm mass was significantly related to speed mainly in uphill sections (r = 0.636 to 0.867; p < 0.05 to p < 0.01). We suggest that large amounts of lean body mass, especially in the arms, seem to be of great importance for cross-country skiing performance.

Ostojic S. M., Stojanovic M.D. (2010) A cross-sectional study was conducted in a random sample of 10 elementary schools. The study participants were a 170 healthy fifth-grade elementary school boys aged 11.9±0.4 years. Anthropometric data (height, body mass, waist circumference, abdominal skinfold thickness) were collected according to standard procedure. Aerobic fitness (VO2max) was assessed with the multistage shuttle-run fitness test. He found that waist circumference, abdominal skinfold thickness and total body fat were lower while muscle mass percentage was higher in overweight boys with high aerobic fitness in comparison with boys at the same BMI category with low fitness level (P<0.05). Aerobic fitness was inversely correlated with body fat in the whole group of subjects (r=-0,57, P<0.05), with particularly high correlation between VO2max and muscle mass in overweight boys (r=0.68, P<0.05).Indicators of local and total adiposity were lower in boys with high aerobic fitness. It seems that high aerobic fitness has is positively associated with body composition in overweight boys.

Stoggl T. et. al. (2010) The aims of this study were to ascertain the anthropometric characteristics of world-class sprint skiers and to evaluate whether a specific body composition and/or body dimension characterizes a successful sprint skier. Fourteen male national and international elite skiers performed two peak speed tests in double poling and diagonal stride roller skiing on a treadmill and were analysed using dual-energy X-ray absorptiometry to determine body composition and body dimensions. Relative pole length was positively correlated with both techniques (double poling: r = 0.77, P < 0.01; diagonal stride: r = 0.60, P < 0.05) and was the only variable that was part of the multiple regression model for both double poling and diagonal stride peak speed. Body height was not correlated with any technique, whereas lean trunk mass (r = 0.75, P < 0.01), body mass index (r = 0.66, P < 0.01), total lean mass (r = 0.69, P < 0.01), and body mass (r = 0.57, P < 0.05) were positively related to double poling peak speed. Total lean mass (absolute: r = 0.58, P < 0.05; relative: r = 0.76, P < 0.001) and relative lean mass of the trunk, arms (both r = 0.72, P < 0.01), and legs (r = 0.54, P < 0.05) were positively related to diagonal stride peak speed. In conclusion, skiers should aim to achieve a body composition with a high percentage of lean mass and low fat mass. A focus on trunk mass through increased muscle mass appears to be important, especially for double poling. The use of longer poles (percent body height) seems to be advantageous for both double poling and diagonal stride peak speed, whereas body dimensions do not appear to be a predictive factor.

Design and Procedure- The main purposes of the present study were: to find out relationship of body composition in terms of body-fat percentage with performance in the events of 100 meters, standing broad jump and putting the shot; secondly, to see if body composition had any relationship with anaerobic work capacity and lastly to see the relationship of the anaerobic work capacity with the performance in the events of 100 meters, standing broad jump and putting the shot. The study was designed to find out the association of body composition with anaerobic work capacity (power) of body composition with performance in selected track and field events including with performance in selected track and field events including standing broad jump, 100 meters and shot put and of anaerobic work capacity with the performance in aforesaid athletic events. The body composition variables were size (height and weight) and percent body fat.  

The study was conducted on 80 males subjects undergoing Teachers Training Course in physical education at Punjab Govt. College of Physical Education, Patiala and Department of Physical Education, Punjab University, Chandigarh during the session 2014-15. The mean age, weight of the subjects was – 24.39 years, 63.53 kg and 68.09 inches respectively.

After the collection of data appropriate statistical tools were employed for describing the results and also their interpretation. Statistical correlation like Mean, standard Deviation, standard error of mean, standard error of standard Deviation, and zero order co-efficient of correlation were worked out for the entire sample in order to compare the association of performance scores obtained in 100 meters, putting the shot and standing broad jump with body composition and anaerobic work capacity. In order to determine the significance of the correlation the ‘t’ value were also worked out. The height of the subjects was recorded to nearest .05 inch with the help of standard steadiometer the weight was taken with the help of a standard weighing machine in bathing suit i.e. with a short only. The weight was recorded to the nearest 0.5 pound and the percent body fat was obtained with the help of sloan-weir nomogram using the measurements from thigh and subscapular skin-folds thicknesses. The measurement techniques prepared by Heath and carter were followed. The power in which an individual ATP-PC system is employed, was obtained from the performance of sargent jump (vertical jump) and the power (anaerobic work capacity) was determined with the help of Lewis-nomogram taking jump reach score and body weight into account (Mathews and Fox, 1976). The performance in athletic events was adjudged on the college track observing all normal rules of the events.

Keeping in view the purpose of the present study, the data obtained by best available methods on various variables of body composition, performance and anaerobic work capacity very classified, organized, analyzed and statistically treated as per requisition. Zero-order correlations were obtained for the entire sample to compare the association of performance scores in the events of 100 meters, shot put, standing Broad jump, with anaerobic work capacity, age and measure of body size and composition. Means, standard Deviations and range of all the variables included in the study are presented in the Table no. I.

Zero-order correlation coefficients for body composition measurements with physical performance scores and power (anaerobic work capacity) are presented in Table no. II.

Table No. 1

Showing Mean SD and Range of Age, weight composition variables anaerobic work capacity and Athletic events (N = 80)

Variable	Mean	SD	Range
Age	24.39	2.97	19.33 to 34.33
Weight	63.54	2.07	51.00 to 80.00
Height	68.09	2.62	63.00 to 75.00
Fat	11.01	3.54	5.75 to 24.00
Power	99.75	17.04	77.00 to 190.00
Vertical Jump	19.45	2.58	14.00 to 25.00
Broad Jump	92.84	6.58	81.00 to 105.5
100 meters	7.00	0.37	6.1 to 7.7
Shot Put	281.48	41.21	205 to 439

Table No. II

Showing Zero-order correlation coefficients for body composition measurements with physical performance scores and power (anaerobic work capacity)

	Age	Weight	Height	Fat	Power	Vertical	Broad	100m	Shot put
Age	-	+.075	-.089	+.170	-.049	-.185	+.155	-.091	+.019
Weight	-	-	+.637	+.470	+.636	+.202	+.160	-.134	+.536
Height	-	-	-	-.052	+.598	+.245	+.346	-.196	+.338
Fat	-	-	-	-	+.165	+.105	-.277	-.008	+.114
Power	-	-	-	-	-	+.252	+.303	-.131	+.471
V. Jump	-	-	-	-	-	-	-.138	-.017	+.106
B. Jump	-	-	-	-	-	-	-	-.172	+.429
100 mtr	-	-	-	-	-	-	-	-	-.137
S. Put	-	-	-	-	-	-	-	-	-

Table III

t-value for the body composition variables anaerobic work capacity and physical performance variables (N=80)

	Age	Weight	Height	Fat	Power	Vertical	Broad	100m	Shot put
Age	-	0.66	-0.79	1.52	-0.43	-1.66	1.39	-0.81	0.17
Weight	-	-	7.30*	4.70*	7.28*	1.82	1.43	-1.19	5.61*
Height	-	-	-	0.46*	6.59*	2.23	3.26*	-1.77	3.17*
Fat	-	-	-	-	1.48	0.93	-2.55**	0.07	1.01
Power	-	-	-	-	-	2.30	2.81*	-1.17	4.72*
V. Jump	-	-	-	-	-	-	-1.23	-0.15	0.94
B. Jump	-	-	-	-	-	-	-	-1.54	4.19*
100 mtr	-	-	-	-	-	-	-	-	1.22
S. Put	-	-	-	-	-	-	-	-	-

*2.58 significant at .01 level

**.195 significant at .05 level

 

on the basis of the data statistically treated and analyzed it is concluded that the size including weight and height are positively correlated with anaerobic work capacity which means that as weight and height increase the power also increases.

The variable of percent body fat did not show significant correlation ship with anaerobic work capacity which means that more the fat of an individual less the anaerobic work capacity. Hence it is desirable that the fat is decreased by proper methods of training and conditioning by proper methods of training and conditioning to have success in the athletic events of power.

Anaerobic work capacity effects the performance in the events of standing broad jump, 100 meters sprint and the shot put. The V.J.P. had positive correlation with the performance in standing broad jump and shot put showing that if power increases the performance in the two events is also increased. The anaerobic work capacity was found to be negatively correlated with the performance in 100m sprint showing that as the power increase the performance in sprint is better.

It can be summarized that extra subcutaneous fat affects the anaerobic work capacity and the performance in the athletic events of power adversely. Also, the performance in the athletic events of power is improved with the improvement of anaerobic work capacity. Hence, the success in the athletic events of power can be predicted by putting the athletes to sargent jump test and working out their power with the help of Lewis nomogram.

1. Ackland T.R, et.al. (2012) Current status of body composition assessment in sport; Sports Med. Mar.1:42(3):227-49. 2. Battinelli (2010), Indian Journal of Science and Technology Research article “Anthropometry of Indian athletes” George Abraham. Vol. 3 No. 12 ISSN: 0974- 6846. 3. Burke L. M., G. Millet, and M. A. Tarnopolsky (2007), Nutrition for distance events Journal of Sports Sciences 25 Suppl 1: 29-38. 4. Burke L. M. (2001), Nutritional practices of male and female endurance cyclists Sports Medicine 31: 521-32. 5. Chauhan, M.S. Sehgal, Subash., Yadav, Dinesh. (Jan, 2003) “Prediction of sprinting ability of secondary school boys of Haryana in relation to their anthropometric measurements.” Sports Authority of India, NSNIS Patiala. 6. Chauhan, M.S. (July, 2003) “Correlation between selected anthropometric variables and middle distance running performance”. Sports Authority of India, NSNIS Patiala. 7. Chauhan, M.S. (2004), "Prediction of Performance of University Throwers in relation to their Anthropometric measurements." Journal of sports and sports sciences. 26 (2):30-35. 8. Gil, S.M., J. Gil, F. Ruiz, A. Irazusta, and J. Irazusta (2007) “Physiological and anthropometric characteristics of young soccer players according to their playing position: relevance for the selection process”. Journal of strength and conditioning research: the research journal of the NSCA, ISSN 1064-8011, Vol. 21, Nº. 2, p. 438-445. 9. Gopinathan, P and Helina, G. (2009) : Correlation of selected anthropometric and physical fitness variables to handball performance. Journal of sports and sports sciences, 32(1): 25-30. 10. Larsson P, Henriksson Larsen K (2008) Body composition and performance in cross-country skiing. Int J Sports Med. Dec;29(12):971-5. 11. Latt, E. Jurimae, J., Haljaste, K., Cicchella, A., Purge, P., Jurimae, T. (2009) “Anthropometrical parameters and body composition influence swimming performance in young swimmers”. 14th annual Congress of the European College Of Sport Science Oslo/Norway, June 24-27. p 568. 12. Meckel, Y, Machnai, O, and Eliakim, A. (2009) : Relationship among repeated sprint tests, aerobic fitness, and anaerobic fitness in elite adolescent soccer players. J Strength Cond Res 23(1): 163–169. 13. Okely A.D, Booth M.L, Chey T (2004) Relationship between body composition and fundamental movement skills among children and adolescents. Rea Q Exerc Sport. Sep; 75(3):238-47 14. Ostojic S. M., Stojanovic M.D. (2010) : High aerobic fitness is associated with lower total and regional adiposity in 12-year-old overweight boys. Journal of Sports Medicine and Physical Fitness December; 50(4):443-9. 15. Sallinen J., Ojanen T., Karavirata L., Ahtiainen J. P., Hakkinen K. (2008) : Muscle mass and strength, body composition and dietary intake in master strength athletes vs untrained men of different ages. The Journal of Sports Medicine and Physical Fitness June; 48(2):138-42. 15. Stoggl T. Enqvist J. Muller E. Holmberg H.C. (2010) Relationships between body composition, body dimensions, and peak speed in cross-country sprint skiing J Sports Sci. Jan;28(2) : 161-9.