Players [both males & females] engaged in regular practice & participating in professional sport tournaments were taken as subjects for the present study. These were young players [aged 18 – 22 years] engaged in different sports disciplines such as athletics, volleyball, cricket, judo, gymnastics, weight lifting, hurdle racing, half marathon, badminton, cross country etc. The subjects were chosen from a well known Physical Education Institution from Vidarbha, Maharashtra, India. Athletes who were participating in regular practice schedules & in many sports events from the past few years [players were in the field from last 3 – 7 years] were mainly of choice. Subjects were classified game wise, the data of which is shown in Table 1.

Figure 1

Table 1: Game-Wise Classification of Subjects

Anthropometric measurements:

• Following measurements were taken:-

• Body weight

• Standing height

• Mid upper arm circumference (MUAC)

• Chest circumference (CHC)

• Waist Circumference (WC)

• Hip circumference (HC)

• Thigh circumference (TC)

• Calf Circumference (CAC)

• Shoulder width (SW)

Body mass index (BMI) was calculated using the formula – weight (kg) / (height in meters)2 (Bamji et al., 2005).

Measurements were taken using standard procedures (Sodi & Sidhu, 1991; Debnath, 1994; Bamji et al., 2005) & equipments & compared with NCHS/ICMR standards.

Means, standard deviations, & range were computed to draw conclusions. BMI categories of the players were derived & represented in percentages. Pearson’s Product Moment method was used to derive coefficient of correlations. A level of probability at both 0.05 & 0.01 levels was assumed to draw significance.

The height of an individual is influenced both by genetic (hereditary) and environmental factors. During periods of severe deprivation, linear growth rate slows down and leads to stunting as a consequence of chronic food deficiency (Bamji et al., 2005).

Figure 2

Table 2 shows data on mean height, weight & BMI for female & male players classified game wise

Table 2: Mean Height, Weight & Body Mass Index [BMI] Values of Players Classified Game-Wise

Among females, half marathon group showed the highest & & athletics group showed the lowest mean values for height (162.56 & 152.4 cm respectively). Irrespective of sports, all groups of female players were found to be shorter than their respective standards. With the exception of athletics group, rest of the groups of female players showed mean values of weight lower than their respective standards.

Among male players volleyball group were found to be tallest & judo & judo & gymnastics groups were found to be shortest (170.18 & 165.1 cm respectively). Irrespective of sports, all groups of male players were found to be shorter than their respective standards. Computed mean values for height were found to be similar for athletics, badminton & cricket groups. Mean body weights for athletics, badminton & judo groups were found to be higher than their respective standards. Rest of the groups showed mean weights less than the standards.

Figure 1 shows coefficient of correlation between height & weight for female & male players classified game wise. Correlation was found to be highly positive & significant for female half marathon players (r = 0.99, 0.010.05). Data on height of female Montreal Olympic players aged between 22 – 35 years showed that the average basketballers & high jumpers were tallest (177 cm) than all other categories. The players of the gold medalist team of basketball had an average height of 182.4 cm (http//:www.gssiweb.com).

From Figure 1, it is clear that male badminton & judo players had a negative insignificant correlations between height & weight (r = - 0.97, highly negative & r = - 0.53, medium negative, respectively, p>0.05). Rest of the groups of male players showed positive correlations (r = 0.13 – 0.76, p>0.05).

Figure 3

BMI was calculated based on height & weight of players (Table 2). It can be seen that with the exception of half marathon among females & badminton among males, all other groups showed mean BMI values above 20 kg / m2 which is considered as normal. It is said that BMI is easy to calculate and correlates better with body fat than desirable body weight. The BMI or Quetelete’s index is the most commonly used weight / height ratio in adult populations (Bamji et al., 2005).

An attempt had been made to derive BMI categories for female & male players classified game wise. Results are shown in Figures 2 & 3. It can be seen that among females, 50 % hurdle racers, 25 % each from athletics & badminton players fell in the category of chronic energy deficient (CED) grade I (BMI – between 17.0 – 18.5 kg / m2). 25 % of female players from athletics & badminton groups were found to be grade II CED (BMI – between 16.0 – 17.0 kg / m2). Among males, majority of players were found under normal category of BMI, however, sports disciplines athletics, cricket & judo & gymnastics showed few players with CED grade II. Players need to gain weight in relationship with height to maintain normal BMI.

Figure 4

Figure 5

Figures 4 & 5 depict coefficient of correlations of BMI against height & weight for female & male players respectively. For female half marathon & badminton players, relationship of BMI with body weight was found to be highly positive (r = 1.00, p<0.01 & r = 0.73, p>0.0, respectively). Group of female athletics players reflected a medium positive relationship between BMI & height (r = 0.61, p>0.05).

Figure 6

With the exception of volleyball players, male players involved in other sports disciplines showed positive correlations between BMI & body weight (r = 0.5 to 0.96, correlation was significant for weight lifters (0.01

Figure 7

Mid upper arm circumference (MUAC):

From Table 3, it can be seen that male players from judo & judo & gymnastics showed lower mean MUAC (25.30 & 27.2 cm, respectively) than that from female hurdle racers (27.5 cm). Female badminton players showed lowest value for mean MUAC (21.9 ± 1.8 cm). Male weight lifters did show larger muscle mass as their mean MUAC was found to be highest of all sports disciplines (31.0 ± 1.0 cm). Rest of the groups of male players had mean MUAC ranged between 25.3 - 29.0 cm. In college aged ‘middle sized’ subjects greatest increase in muscle girths with exercise was reported by Loucks (1997).

Chest circumference (CHC):

Mean CHC values for female players engaged in different sports disciplines were found to be in the range of 80.0 to 91.0 cm (Table 3). Among male players, judo group had highest value of mean CHC (89.2 ± 4.2 CM) whereas volleyball group had lowest value of mean CHC (82.2 ± 2.4 cm).

Thigh circumference (TC):

From Table 3, it is clear that female hurdle racers showed largest mean TC (51.5 ± 6.5 cm) followed by half marathon group (49.7 ± 2.4 cm). Male volleyballers showed lowest mean TC (43.5 ± 1.7 cm). Rest of the groups of male players showed mean TC ranged between 45.8 to 47.3 cm, the maximum was for athletics.

Calf circumference (CAC):

Highest mean CAC value among female players was found out for hurdle racing (33.0 ± 3.0 cm) & that of lowest for badminton (30.0 ± 1.5 cm). Male weight lifters showed greater CAC values (43.6 ± 3.6 cm) whereas volleyballers showed lowest value of mean CAC (34.3 ± 2.8 cm) (Table 3)

Waist circumference (WC):

Female players showed higher mean values for WC as compared to males (Table 3). Mean WC among female players was found to be ranged between 83.0 to 90.0 cm, the highest value for half marathon & the lowest value for badminton. Less differences were noticed between different sports disciplines among males for mean WC. Means were found to be in the range of 76.5 to 81.5 cm.

Hip circumference (HC):

From Table 3, female players involved in different sports disciplines had mean HC ranged between 91.0 to 97.0 cm (lowest value for badminton & highest value for hurdle racing). Fewer differences were observed for mean HC among male players. Highest mean HC was recorded for athletics (93.3 cm) & that of lowest for badminton (88.7 cm).

Shoulder width (SW):

For female players no obvious differences were noted between different sports disciplines for mean SW. Female hurdle racers showed highest whereas badminton players showed lowest mean SW values (38.0 & 34.5 cm, respectively). Highest & lowest mean SW values among male players were recorded for weight lifting & volleyball respectively (40.5 & 38.0 cm) (Table 3).

MUAC - Mid Upper Arm Circumference CHC - Chest Circumference

TC - Thigh Circumference CAC - Calf Circumference

WC - Waist Circumference HC - Hip Circumference

SW - Shoulder Width

Figures in parenthesis indicate range.

Figure 8

Table 3: Mean Values of Body Measurements of Male & Female Players Engaged In Different Sports Disciplines

Shoulder width has a direct impact on body weight. It is said that broader the shoulders larger the body weight & vice versa. Many researchers & educationists use shoulder width criteria for prediction of body weight (Almeida et al, 2003; Mahan & Escott – Stumps, 2004). For the present study, coefficient of correlations between shoulder width & body weight were derived & data is presented in Figure 6. Among female players, athletics & badminton groups showed a high positive correlation between shoulder width & weight. No correlations were drawn for half marathon & hurdle racing as recorded shoulder width values were found to be same. Shoulder width reflected a strong positive & significant correlation with body weight among males (r = 0.84, 0.010.05). Rest of sports disciplines among male players reflected medium positive but insignificant relationship between shoulder width & body weight.

Figure 9