Physiological and physical attributes of athletes are closely related with sports performance, and hence their assessment and monitoring form an integral part of sports training and performance optimization for a variety of sports, as well as for prehabilitation, injury risk minimization and rehabilitation (1, 2). Vertical jump (VJ) is a good marker of lower limb muscular strength and explosive power, and hence athletic performance (3-5). Countermovement jump test, consisting of eccentric followed by concentric muscle contraction, is a widely used test to assess lower limb muscle speed-strength or power, and has been associated with performance improvement with training (2). Vertical jump mainly involves the muscles of hip, knee and ankle including quadriceps, hamstrings, gastrocnemius and soleus. and back extensors and gluteus maximus etc (3, 6).

Since VJ is a commonly used measure of both the current and future sports performance level (3, 7), evaluating anthropometric and body composition correlates of VJ is an interesting area of translational research. With the increasing popularity of women's sports, understanding the gender gap is also important. However, not many published papers are available in this field among young Indian university players. There is a lack of universally accepted normative data for VJ for young Indian players. Hence, the study was planned with an aim to evaluate anthropometric and body composition correlates of VJ in male and female university young players, and also to evaluate the gender difference in these parameters.

The present cross-sectional study was done under Sports-Exercise Medicine and Sciences: Lifestyle and Performance Medicine (Health and Physiological Medicine: Clinical and Interventional Physiology) Lab., Department of Physiology, Institute of Medical Sciences (IMS), Banaras Hindu University (BHU). The volunteers were the university players and students from the Department of Physical Education, BHU belonging to different sports disciplines (athletics, badminton, basketball, cricket, football, gymnastic, hockey, kabaddi, karate, kho-kho, taekwondo, volleyball, wushu and yoga). The study was approved by the institutional ethical committee (Dean/2022/EC/3663) and informed consent was taken from all the volunteers. The following eligibility criteria were used: apparently healthy young adults from 18 to 30 years, having no acute and chronic medical illness or neuromusculoskeletal injuries and deformities, having no addiction and having played a sports discipline or participated in structured training program for a sports discipline for at least 1 year, or participated in any state or national level, inter-college or inter-university sports competition. Those players who were found to be unfit for any reason by a sports medicine physician in the pre-participation physical and medical screening were also excluded.

After clearly explaining the procedures, the volunteers were given sufficient practice sessions at least 2 days before the actual testing day. The volunteers were told to have an adequate night sleep of at least 7-8 hours and to avoid any strenuous exercise or physical activity for at least 24-48 hours before the testing day. A very light breakfast, least 1.5-2 hours before, with no caffeinated drinks was allowed. All the tests were completed from 9am to 11am by the same investigators.

After relevant history and brief examination, age and sports discipline of the volunteers were recorded. The following anthropometric data were measured: height (HT) in cm using a stadiometer (PRESTIGE company), and waist (WC) and hip circumference (HC) in cm using a non-elastic and flexible measuring tape (8). Waist-hip ratio (WHR) and waist-height ratio (WHtR) were calculated. Percentage body fat (%BF) and skeletal muscle mass (SKM) in kg were estimated using a bioelectric impedance analysis (BIA) based machine (TANITA BC-545N). Vertical jump (VJ) in cm was measured using a countermovement jump test (with no restriction on arm swing), and the best of the three attempts, with at least 1 min rest in between, for each player was taken for analysis (1, 3). Instead of using a force plate, vertical jump height was calculated as the difference between total jump height and standing reach height (1).

Statistical Analysis:

The data was analysed using SPSS (statistical package for the social sciences) version 20. Descriptive statistics were determined. Mean ±standard deviation (SD), median±quartile deviation (QD) and minimum and maximum values were given. Normality testing was done using Shapiro-Wilk test. The comparisons of age, studied anthropometric, body composition and vertical jump parameters between males and females was done using Unpaired t test and Mann-Whitney U test based on the normality testing. Correlation of VJ with age, studied anthropometric and body composition variables was done separately for males (n=32) and females (n=14) using either Pearson’s or Spearman’s correlation based on the normality testing. Correlation was also done after combining male and female data (n=46) after controlling for gender using parametric or nonparametric partial correlation as per the normality testing. Linear regression analyses were done with VJ as dependent variable (DV) with one independent variable (IV) each: HT, WC and SKM; and with two IVs: gender and HT, gender and WT, gender and WHtR, gender and %BF, and gender and SKM. The code used for gender was: 1=male, 2=female. Statistical significance was set at p-value<0.5.

Male players were having significantly higher HT, WT, SKM and VJ; but lower %BF and WHtR. Age, BMI, WC, HC, WHR were statistically similar in both the genders (Table 1). Except for SKM, when VJ was normalized by dividing it with HT, WT, WHtR and %BF, statistically significant differences were found between the genders (Table 1.).

Table 1. Comparison of studied parameters between male and female players

Unpaired t test, ^Mann-Whitney U test. *p-value<.05, **p-value<.01.

SD=Standard Deviation, QD=Quartile Deviation. Min.=Minimum Value, Max.=Maximum Value.

In the regression equation predicting VJ using gender and SKM as IVs, VJ=-9.29gender+0.21SKM+47.91 (p-value=<.001, r2=0.403, adjusted r2=0.374, SEE or standard error of the estimate=7.505), the unique contribution by gender over the total VJ variance, over and beyond that explained by SKM was not statistically significant (p-value=0.060, semi-partial correlation r2=0.053). Similarly, for VJ=-4.80gender-0.56%BF+63.56 (p-value=<.001, r2=0.427, adjusted r2=0.400, SEE=7.352), the unique contribution by gender over and above %BF was also not significant (p-value=0.393, semi-partial correlation r2=0.010). However, the unique contributions by gender over the total variance in VJ over and above of those by HT, WT and WHtR in the equations: VJ=-8.82gender+0.24HT+17.61 (p-value=<.001, r2=0.413, adjusted r2=0.385, SEE=7.439), VJ=-12.36gender+0.04WT+59.43 (p-value=<.001, r2=0.393, adjusted r2=0.364, SEE=7.565) and VJ=-11.995gender-16.56WHtR+68.87 (p-value=<.001, r2=0.398, adjusted r=0.370, SEE=7.534) were significant: p-value=0.035 (semi-partial correlation r2=0.066) for HT, p-value=<.001 (semi-partial correlation r2=0.215) for WT, p-value=<.001 (semi-partial correlation r2=.271) for WHtR respectively.

Among the female players, VJ was significantly and positively correlated with HT, HC and SKM (Table 2.). The regression equations for prediction VJ based on HT, HC and SKM were: VJ=0.491HT-39.781 (r2=0.570, p-value=0.003, SEE=2.8897), VJ=0.885HC-46.254 (r2=0.510, p-value=0.006, SEE=3.087) and VJ =0.990SKM+2.489 (r2=0.501, p-value=0.007, SEE=3.116) respectively.

Table 2. Correlation of vertical jump score with anthropometric and body composition variables in males, females and combined data (controlling for gender).

Pearson’s correlation, ^Spearman’s correlation/Non-parametric, #Partial correlation.

**p-value<.001

No significant correlation of VJ was found with the studied variables among male players and in the combined data, after controlling for gender. However, negative correlation of VJ was there with %BJ and WC, although not statistically significant, in both the genders. The positive correlation between VJ and SKM in males was also not statistically significant (Table 2.).

In the present study, the gender difference between selected anthropometric, body composition parameters and vertical jump were evaluated. The correlates of vertical jump among the studied variables were also determined.

The study revealed that skeletal muscle mass (SKM) was the primary driver of gender differences in vertical jump (VJ) among Indian athletes. As expected, the male players were significantly taller, heavier with more skeletal muscle mass, lower percentage body fat and waist-height ratio, and jumped higher than the female players (Table 1.). Previous studies have reported a similar pattern between male and female players in case of HT, %BF, lean body mass and VJ in Indian players (3-5). The differences in anthropometry and body composition might be related with gender specific differences in their physiology as the physical activity and dietary habits were similar (5, 9).

Males’ significantly higher VJ likely stemmed from their greater SKM and lean mass (due to their lower %BF) than females. The gender differences in strength and muscular performance are well established physiology (9-11). Among various factors affecting VJ, muscle mass has been reported to be an important one (3, 12). When VJ was normalized with SKM by dividing it with SKM, no statistical significance was found between the genders, which indicated that differences in VJ between males and females might be due to their difference in SKM. For VJ normalized by HT, WT, WHtR and %BF, the gender differences were still statistically significant (Table 1). The importance of SKM in gender difference for VJ was also suggested by the non-statistically significant (p-value=0.060, in result section) unique contribution of gender in VJ over and above that by SKM. Similar result was obtained for %BF (p-value=0.393). But for HT, WT and WHtR, the p-values were significant (in the result section). These findings again strengthened the important contributing factors for the gender difference in VJ as the differences in SKM and %BF.

The importance of SKM on VJ was also suggested by the significant positive correlation of SKM with VJ among the females (in males, the positive correlation was not significant) (Table 2.). Among females, those who were taller with more hip circumference and having more skeletal muscle mass seemed to jump higher (Table 2.). With 1 cm increase in HT and HC for female players, VJ would increase by 0.491cm and 0.885cm respectively (regression equations given in result section). An increase in VJ of 9.9cm might be possible with a 10 kg increase in SKM among the studied females (regression equation given in result section). Appropriate resistance training along with adequate good quality protein intake might be beneficial in this direction (9, 13, 14).

The direction for correlation of HC with VJ was different for males and females: negative for males (although statistically non-significant) and positive for females, indicating possible opposite effects of HC in both the genders. In a previous study among obese females, hip circumference was found to be associated positively with lower and appendicular lean soft tissue (15). The opposite correlations (although not significant) were also found for WT, BMI, WHR and WHtR (Table 2).

Among the males, and when analysis was done combining both males and females (after controlling for gender), there was no significant correlation of VJ with the studied parameters. Among both males and females, %BF correlated negatively with VJ, but the correlation coefficients were statistically non-significant (Table 2). Interestingly BMI didn’t correlate significantly with VJ in each of the gender, also the direction of correlation of BMI was opposite unlike %BF (Table 2). This hinted at the relatively non-importance of BMI, unlike body composition parameters like SKM, in young players, as reported earlier (3, 5). Infact the use of BMI as a marker of body fatness or obesity should be discouraged among players (9, 16, 17).

In the present study, there were statistically significant differences in HT, WT, WHtR, %BF, SKM and VJ between male and female players. When VJ was normalized by dividing it with SKM, there was no statistical gender difference. Also, the unique contribution by gender in VJ variance over and above that by SKM was non-significant. This was the same for %BF, although VJ when divided by %BF was still significant between the genders. This hinted that gender difference in VJ might be related with gender difference in SKM, and also with %BF. Among the females, VJ was found to have significant positive correlations with HT, WC and SKM. With 1 unit increase in HT, WC and SKM, VJ would increase by 0.491cm, 0.885cm and 0.990cm respectively. The finding showed the importance of muscle mass for vertical jump performance.

Limitations:

Relatively small sample size and cross-sectional nature of the studies are few limitations. The use of force plates for vertical jump height performance analysis as well as DEXA (Dual-energy X-ray absorptiometry) scan for the body composition analysis would improve the validity and quality of the result. Incorporation of more biomechanical and physiological parameters including surface EMG (Electromyography) and other measures of lower limb muscular strength and power tests might further improve the result of this research.

Practical Applications:

In the current study group, since vertical jump performance was related with skeletal muscle mass specially among females, emphasis should be given for the incorporation of resistance or strength training and adequate high quality protein intake to increase lean body mass. With the increase in skeletal muscle mass and reduction in percentage body fat among the females, the gender difference in vertical jump performance might also decrease. Parameters like SKM along with HT and HC might be important for the selection of female players for vertical jump performance. This study forms the basis for future larger sample size study with gold standard equipments and better design in this direction. Also, the current result might contribute in establishing normative data for VJ for young north Indians.

Acknowledgements:

The authors acknowledge the officials of University Sports Board and Department of Physical Education of BHU for their support. The authors express their deep gratitude for the financial supports from BHU under IoE (Institute of Eminence) schemes [R/Dev/D/IoE/Equipment/Seed Grant-II/2022-23/50023, R/Dev/D/IoE/Additional (Seed Grant)/2024-25/83144 and R/Dev/IoE/TDR-Projects/2023-24/61656]. Lastly, the authors thank all the players who have participated voluntarily in the study.

Authors contribution:

All authors have made substantial contributions to this work as follows:

1. Sumya Akter: Contributed to [specific role, e.g., data acquisition, analysis], manuscript drafting, critical revision, and approved the final version.
2. Sankalp: Involved in [e.g., study design, data interpretation], manuscript revision, and final approval.
3. Ashish Kumar Gupta: Participated in [e.g., conceptualization, methodology], intellectual content revision, and final approval.
4. Yumnam Ruhinkumar Singh: Responsible for [e.g., data curation, formal analysis], manuscript editing, and final approval.
5. Anurag Kumar: Contributed to [e.g., investigation, resources], manuscript review, and final approval.
6. Ruby Pal: Engaged in [e.g., software, validation], manuscript drafting, and final approval.
7. Gopal Krishna Shukla: Assisted with [e.g., visualization, project administration], critical revisions, and final approval.
8. Pragya Tiwari: Involved in [e.g., supervision, funding acquisition], manuscript refinement, and final approval.
9. (Dr) Abhimanyu Singh: Led [e.g., conceptualization, methodology], manuscript revision, and final approval.
10. Hanjabam Barun Sharma: Oversaw [e.g., study design, coordination], manuscript finalization, and approval.

Conflict of Interest

All authors confirm there are no conflict of interest to disclose.

Data Availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

1. Fukuda, David H. Assessments for Sport and Athletic Performance. Human Kinetics, 2019.
2. Tanner, Ross, and Christopher Gore. Physiological Tests for Elite Athletes. 2nd ed., Human Kinetics, 2000.
3. Sharma, H.B., et al. “Anthropometric Basis of Vertical Jump Performance: A Study in Young Indian National Players.” Journal of Clinical and Diagnostic Research, vol. 11, no. 2, 2017, pp. CC01–CC05.
4. Sharma, H.B., and J. Kailashiya. “Anthropometric Correlates for the Physiological Demand of Strength and Flexibility: A Study in Young Indian Field Hockey Players.” Journal of Clinical and Diagnostic Research, vol. 11, no. 6, 2017, pp. CC01–CC05.
5. Hanjabam, B., and K.K. Meitei. “Anthropometric Basis for the Physiological Demand of Anaerobic Power and Agility in Young Indian National Level Field Hockey Players.” Fiziologia - Physiology, vol. 25, no. 3(87), 2015, pp. 41–48.
6. Reeves, R.A., O.D. Hicks, and J.W. Navalta. “The Relationship Between Upper Arm Anthropometrical Measures and Vertical Jump Displacement.” International Journal of Exercise Science, vol. 1, no. 1, 2008, p. 4.
7. Davis, D.S., et al. “The Relationship of Body Segment Length and Vertical Jump Displacement in Recreational Athletes.” The Journal of Strength & Conditioning Research, vol. 20, no. 1, 2006, pp. 136–140.
8. Sharma, H.B., et al. “Cardiorespiratory Fitness and Heart Rate Recovery in Type-II Diabetic Males: The Effect of Adiposity.” Indian Journal of Physiology and Pharmacology, vol. 60, no. 3, 2016, pp. 260–267.
9. Kenney, W. Larry, et al. Physiology of Sport and Exercise. 6th ed., Human Kinetics, 2015.
10. Thomas, Jerry R., and Keith E. French. “Gender Differences Across Age in Motor Performance: A Meta-Analysis.” Psychological Bulletin, vol. 98, no. 2, 1985, pp. 260–282.
11. Miller, A.E., et al. “Gender Differences in Strength and Muscle Fiber Characteristics.” European Journal of Applied Physiology and Occupational Physiology, vol. 66, no. 3, 1993, pp. 254–262.
12. Golomer, Eveline, et al. “Unipodal Performance and Leg Muscle Mass in Jumping Skills Among Ballet Dancers.” Perceptual and Motor Skills, vol. 98, no. 2, 2004, pp. 415–418.
13. Sharma, H.B. “COVID-19: Lifestyle, CoVesity and Exercise - Time to Identify and Defeat the Real Culprits with Clinical Physiological Interventions.” Journal of Clinical and Diagnostic Research, vol. 16, no. 11, 2022, pp. CE01–CE11.
14. Sharma, H.B., and J. Kailashiya. “Effects of 6-Week Sprint-Strength and Agility Training on Body Composition, Cardiovascular, and Physiological Parameters of Male Field Hockey Players.” Journal of Strength and Conditioning Research, vol. 32, no. 4, 2018, pp. 894–901.
15. Cavedon, Valentina, et al. “Are Body Circumferences Able to Predict Strength, Muscle Mass and Bone Characteristics in Obesity? A Preliminary Study in Women.” International Journal of Medical Sciences, vol. 17, no. 7, 2020, pp. 881–891.
16. Ode, J.J., et al. “Body Mass Index as a Predictor of Percent Fat in College Athletes and Nonathletes.” Medicine & Science in Sports & Exercise, vol. 39, no. 3, 2007, pp. 403–409.
17. Turocy, Paula S., et al. “National Athletic Trainers' Association Position Statement: Safe Weight Loss and Maintenance Practices in Sport and Exercise.” Journal of Athletic Training, vol. 46, no. 3, 2011, pp. 322–336.