scholarly journals Cardiorespiratory Fitness in University Level Volleyball Players and its Correlation with Body Fat

2020 ◽  
Vol 27 (3) ◽  
pp. 15-19
Author(s):  
Archana Khanna ◽  
Ankita Singh ◽  
Bhanu Pratap Singh ◽  
Faiz Khan
Keyword(s):  
Lean Body Mass ◽  
Body Mass ◽  
Cardiorespiratory Fitness ◽  
Body Fat ◽  
Vigorous Physical Activity ◽  
Step Test ◽  
Male And Female ◽  
Percentage Body Fat ◽  
Volleyball Players ◽  
University Level

Abstract Introduction. The present study was aimed to compare the cardiorespiratory fitness levels (VO2max) between university level male and female volleyball players and to find its correlation with percentage body fat. Material and Methods. In the present cross-sectional study, male and female volleyball players (n = 15 each) aged 18-25 years were randomly selected from Teerthanker Mahaveer University, Moradabad, India. An equal number of sedentary individuals were also selected who did not indulge in any vigorous physical activity or training. Body height, body weight, body mass index (BMI), % lean body mass of players and sedentary individuals were recorded using standard methods. Percentage body fat was calculated using the sum of four skinfolds and VO2max was recorded using Queen’s college step test. Data were analysed using SPSS software version 20.0. Unpaired t-test was used for comparison between players and sedentary individuals and two-way ANOVA was used to examine interaction of status (active players and sedentary individuals) and gender on VO2max. Results. Players had higher mean values for % lean body mass and VO2max. Statistically, highly significant differences (p < 0.05) were observed between male and female players for all variables except BMI. Players had better cardiorespiratory fitness (VO2max) as compared to their sedentary counterparts. Conclusions. Significant differences exist between players and sedentary individuals for percentage body fat and percentage lean body mass. Cardiorespiratory fitness of players is negatively correlated with percentage body fat. Players have higher VO2max as compared to their sedentary counterparts.

Morphologic and Anthropometric Characteristics of High Level Dutch Korfball Players

1996 ◽  
Vol 82 (1) ◽  
pp. 35-42 ◽  
Author(s):  
Mário Godinho ◽  
Isabel Fragoso ◽  
Filomena Vieira
Keyword(s):  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Team Sport ◽  
The Other ◽  
Endurance Athletes ◽  
Anthropometric Characteristics ◽  
Volleyball Players ◽  
Apparent Similarity ◽  
High Level

In this study a morphologic and anthropometric characterisation of Dutch korfball players ( N = 36) is performed. Data, compared with those of other sports populations, showed that (1) korfball athletes are smaller and lighter than basketball and volleyball players but heavier and taller than other team-sport players; (2) korfball players have less relative body fat, more lean body mass, more limb fat, and less or similar trunk fat than the other athletes. (3) Male korfball players presented a somatotype (1.9–4.4–3.4) similar to endurance athletes and an endomorphic value lower than or similar to the other athletes. (4) The only apparent similarity between female korfball somatotype (3.2–4.0–2.8) and other athletes' somatotypes is the dominance of mesomorphy.

Conjugated Linoleic Acid Combined with Physical Activity Reduces Body Fat Accumulation But Does Not Modify Lean Body Mass in Male and Female Wistar Rats

2012 ◽  
Vol 15 (4) ◽  
pp. 406-412 ◽  
Author(s):  
Jocelem Mastrodi Salgado ◽  
Tânia Rachel Baroni Ferreira ◽  
Carlos M. Donado-Pestana ◽  
Omer Cavalcanti de Almeida ◽  
Aline Mouro Ribeiro das Neves ◽  
...  
Keyword(s):  
Physical Activity ◽  
Linoleic Acid ◽  
Conjugated Linoleic Acid ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Wistar Rats ◽  
Male And Female ◽  
Fat Accumulation ◽  
Female Wistar Rats

scholarly journals PO-100 Analysis of Body Composition and Body Function of Athletes in Freestyle ski Half-pipe National Team

2018 ◽  
Vol 1 (3) ◽  
Author(s):  
Lin Li ◽  
Hao Wu
Keyword(s):  
Body Composition ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Female Athletes ◽  
Anaerobic Power ◽  
The Body ◽  
Male And Female ◽  
National Team ◽  
Body Function

Objective The objectives were to analyze the body composition and body functions of the freestyle ski half-pipe national team athletes, to understand the body composition characteristics of the athletes , and to explore the relationship between body composition and body function in the sports program, in preparation for 2022 The Winter Olympics provides a theoretical reference. Methods 9 members of the freestyle ski half-pipe national team were used as subjects (average age 15.78±0.97, exercise age 6.38±2.75), and they were tested and analyzed using an ultrasonic body composition tester and Wingate anaerobic power bike. Body composition test indicators: body fat rate, lean body mass. Body function test indicators: maximum anaerobic power.  This paper uses literature, experimental and mathematical statistics. And the mathematical statistics method: using SPSS 2.0 to analyze the data by Pearson correlation. Results 1. The body fat rate of male and female athletes in freestyle half-pipe national team was: 7.60±1.16; 19.75±1.25. The lean body mass of male and female athletes was: 53.8±1.85KG; 44.75±0.62KG. The maximum anaerobic power of male and female athletes in freestyle half-pipe national team was: 453.80±17.87; 345.50±3.01. The lean body mass of male athletes was significantly positively correlated with the maximum anaerobic power (r=0.995, P<0.01). Female athletes' lean body mass was positively correlated with maximum anaerobic power, but not significant. There is no correlation between the body fat rate and the maximum anaerobic power of male and female athletes in the freestyle ski half-pipe national team. Conclusions 1. Freestyle ski half-pipe players have a positive correlation between lean body mass and anaerobic capacity.  According to the characteristics of the sports program, the higher lean body weight has a positive impact on improving the athletic ability and thus ensuring the completion of difficult movements.       2. Due to the relationship between athletes' age and sample size, the data in this paper is only a recommended reference for this sports program. It is not applicable to all programs. It is necessary to continue to supplement the data to establish a body composition evaluation system for the freestyle ski half-pipe team.

scholarly journals A comparison of thermoregulatory responses to exercise between mass-matched groups with large differences in body fat

2016 ◽  
Vol 120 (6) ◽  
pp. 615-623 ◽  
Author(s):  
Sheila Dervis ◽  
Geoff B. Coombs ◽  
Georgia K. Chaseling ◽  
Davide Filingeri ◽  
Jovana Smoljanic ◽  
...  
Keyword(s):  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Sweat Rate ◽  
Whole Body ◽  
Total Body Mass ◽  
Percentage Body Fat ◽  
Thermoregulatory Responses ◽  
Local Sweat Rate ◽  
Total Body

We sought to determine 1) the influence of adiposity on thermoregulatory responses independently of the confounding biophysical factors of body mass and metabolic heat production (Hprod); and 2) whether differences in adiposity should be accounted for by prescribing an exercise intensity eliciting a fixed Hprod per kilogram of lean body mass (LBM). Nine low (LO-BF) and nine high (HI-BF) body fat males matched in pairs for total body mass (TBM; LO-BF: 88.7 ± 8.4 kg, HI-BF: 90.1 ± 7.9 kg; P = 0.72), but with distinctly different percentage body fat (%BF; LO-BF: 10.8 ± 3.6%; HI-BF: 32.0 ± 5.6%; P < 0.001), cycled for 60 min at 28.1 ± 0.2°C, 26 ± 8% relative humidity (RH), at a target Hprod of 1) 550 W (FHP trial) and 2) 7.5 W/kg LBM (LBM trial). Changes in rectal temperature (ΔTre) and local sweat rate (LSR) were measured continuously while whole body sweat loss (WBSL) and net heat loss (Hloss) were estimated over 60 min. In the FHP trial, ΔTre (LO-BF: 0.66 ± 0.21°C, HI-BF: 0.87 ± 0.18°C; P = 0.02) was greater in HI-BF, whereas mean LSR (LO-BF 0.52 ± 0.19, HI-BF 0.43 ± 0.15 mg·cm−2·min−1; P = 0.19), WBSL (LO-BF 586 ± 82 ml, HI-BF 559 ± 75 ml; P = 0.47) and Hloss (LO-BF 1,867 ± 208 kJ, HI-BF 1,826 ± 224 kJ; P = 0.69) were all similar. In the LBM trial, ΔTre (LO-BF 0.82 ± 0.18°C, HI-BF 0.54 ± 0.19°C; P < 0.001), mean LSR (LO-BF 0.59 ± 0.20, HI-BF 0.38 ± 0.12 mg·cm−2·min−1; P = 0.04), WBSL (LO-BF 580 ± 106 ml, HI-BF 381 ± 68 ml; P < 0.001), and Hloss (LO-BF 1,884 ± 277 kJ, HI-BF 1,341 ± 184 kJ; P < 0.001) were all greater at end-exercise in LO-BF. In conclusion, high %BF individuals demonstrate a greater ΔTre independently of differences in mass and Hprod, possibly due to a lower mean specific heat capacity or impaired sudomotor control. However, thermoregulatory responses of groups with different adiposity levels should not be compared using a fixed Hprod in watts per kilogram lean body mass.

scholarly journals Body mass index: a measure of fatness or leanness?

1995 ◽  
Vol 73 (4) ◽  
pp. 507-516 ◽  
Author(s):  
Alan M. Nevill ◽  
Roger L. Holder
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Normal Range ◽  
Percentage Body Fat ◽  
Distributional Properties ◽  
Two Indices ◽  
The Relationship

The relationship between body fat and stature-adjusted weight indices was explored. Assuming the term height2 is a valid indicator of a subject's lean body mass, height2/weight was shown to be an accurate measure of percentage lean body mass and, as such, a better predictor of percentage body fat than the traditional body mass index (BMI; weight/height2). The name, lean body mass index (LBMI), is proposed for the index height2/weight. These assumptions were confirmed empirically using the results from the Allied Dunbar National Fitness Survey (ADNFS). Using simple allometric modelling, the term heightp explained 74% of the variance in lean body mass compared with less than 40% in body weight. For the majority of ADNFS subjects the fitted exponent from both analyses was approximately p = 2, the only exception being the female subjects aged 55 years and over, where the exponent was found to be significantly less than 2. Using estimates of percentage body fat as the dependent variable, regression analysis was able to confirm that LBMI was empirically, as well as theoretically, superior to the traditional BMI. Finally, when the distributional properties of the two indices were compared, BMI was positively skewed and hence deviated considerably from a normal distribution. In contrast, LBMI was found to be both symmetric and normally distributed. When height and weight are recorded in centimetres and kilograms respectively, the suggested working normal range for LBMI is 300–500 with the median at 400.

scholarly journals Relationship between body fat, lean body mass and disease severity in AECOPD patients

2021 ◽  
Author(s):  
Yiben Huang ◽  
Jiedong Ma ◽  
Xueting Hu ◽  
Jianing Wang ◽  
Xiaqi Miao ◽  
...  
Keyword(s):  
Disease Severity ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat

Comparison of the Effect of Soy protein and Whey protein on Body Composition: A Meta-Analysis of Randomized Clinical Trials

2021 ◽  
pp. 1-27
Author(s):  
Masoome Piri Damaghi ◽  
Atieh Mirzababaei ◽  
Sajjad Moradi ◽  
Elnaz Daneshzad ◽  
Atefeh Tavakoli ◽  
...  
Keyword(s):  
Body Composition ◽  
Whey Protein ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Fat Mass ◽  
Soy Protein ◽  
Protein Supplementation ◽  
Body Fat Percentage ◽  
Fat Percentage

Abstract Background: Essential amino acids (EAAs) promote the process of regulating muscle synthesis. Thus, whey protein that contains higher amounts of EAA can have a considerable effect on modifying muscle synthesis. However, there is insufficient evidence regarding the effect of soy and whey protein supplementation on body composition. Thus, we sought to perform a meta-analysis of published Randomized Clinical Trials that examined the effect of whey protein supplementation and soy protein supplementation on body composition (lean body mass, fat mass, body mass and body fat percentage) in adults. Methods: We searched PubMed, Scopus, and Google Scholar, up to August 2020, for all relevant published articles assessing soy protein supplementation and whey protein supplementation on body composition parameters. We included all Randomized Clinical Trials that investigated the effect of whey protein supplementation and soy protein supplementation on body composition in adults. Pooled means and standard deviations (SD) were calculated using random-effects models. Subgroup analysis was applied to discern possible sources of heterogeneity. Results: After excluding non-relevant articles, 10 studies, with 596 participants, remained in this study. We found a significant increase in lean body mass after whey protein supplementation weighted mean difference (WMD: 0.91; 95% CI: 0.15, 1.67. P= 0.019). Subgroup analysis, for whey protein, indicated that there was a significant increase in lean body mass in individuals concomitant to exercise (WMD: 1.24; 95% CI: 0.47, 2.00; P= 0.001). There was a significant increase in lean body mass in individuals who received 12 or less weeks of whey protein (WMD: 1.91; 95% CI: 1.18, 2.63; P<0.0001). We observed no significant change between whey protein supplementation and body mass, fat mass, and body fat percentage. We found no significant change between soy protein supplementation and lean body mass, body mass, fat mass, and body fat percentage. Subgroup analysis for soy protein indicated there was a significant increase in lean body mass in individuals who supplemented for 12 or less weeks with soy protein (WMD: 1.48; 95% CI: 1.07, 1.89; P< 0.0001). Conclusion: Whey protein supplementation significantly improved body composition via increases in lean body mass, without influencing fat mass, body mass, and body fat percentage.

Biathlon Performance: Heart Rate, Hit Rate, Speed and Physiological Variables

2021 ◽  
Vol 15 (10) ◽  
pp. 3245-3249
Author(s):  
Gökhan Atasever ◽  
Fatih Kiyici ◽  
Deniz Bedir ◽  
Fatih Ağduman
Keyword(s):  
Heart Rate ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Maximum Speed ◽  
Fat Percentage ◽  
Physiological Variables ◽  
Cross Country Skiing ◽  
Cross Country ◽  
Short Time

Aim: Biathlon is a sport that combines cross-country skiing and rifle shooting. The athlete is fast in the cross-country skiing section, in the gun shooting section, the heart rate should be low. This study aims to determine the hitting rate of the shots made with different training loads on low altitude in elite biathletes in terms of maximum speed and physiological variables. Methods: To evaluate shooting performances first with the resting pulse and then after 2.5 km skiing respectively with 50%, 70% and 100% pulse rate which is separately calculated for each athlete according to karvonen formula. Results: Our findings show that while there was negative relation between maximum speed and body fat there was a positive relation with lean body mass. It has been determined that low body fat percentage and high lean body mass are effective at the athletes’ maximum speed and the pulse level with the highest target shooting accuracy rate was at rest and 70% in the second level. Conclusion: Since the pulse of the athlete who comes to the shooting area cannot be reduced to a resting level in a short time, focusing the 70% pulse zone may be beneficial in terms of shooting accuracy and acceleration after the shot. The lowest results in target shooting accuracy were seen at 50% and 100% loads. Keywords: Athletes, performance, heart, rate, lean body mass.

A Simple Test for the Assessment of Aerobic Fitness

1988 ◽  
Vol 74 (2) ◽  
pp. 107-114
Author(s):  
D. J. Smith ◽  
R. J. Pethybridge ◽  
A Duggan
Keyword(s):  
Heart Rate ◽  
Body Weight ◽  
Physical Fitness ◽  
Lean Body Mass ◽  
Body Mass ◽  
Test Score ◽  
Linear Regression Analysis ◽  
Treadmill Running ◽  
Step Test ◽  
Anthropometric Measures

SummaryThe relationship between physical fitness, anthropometric measures, and the scores in three submaximal step tests have been evaluated in a group of 30 male subjects. Physical fitness was assessed as VO2max measured directly during uphill treadmill running. Each submaximal exercise test was of six minutes duration and the heart rate recorded during the last minute (fH6) constituted the test score. Significant negative correlation coefficients were found between VO2max and each test score while lean body mass, gross body weight and body surface area were allpositively correlated with VO2max (1/min). The score in the least severe step test was included with anthropometric measures in multiple linear regression analysis for the prediction of VO2max and a number of prediction equations were derived. It was found that when lean body mass is calculated from skinfold measurements and weight, VO2max can be calculated from the equation:VO2max(1/min) = 1.470 + 0.0614 × Lean Body mass −0.0131 × fH6This equation accounts for 73% of the total variation of VO2max. If lean body mass cannot be calculated, a combination of gross body weight and age plus fH6 gives the equation:VO2max = 3.614 + 0.0349 × Weight – 0.0177 × fH6−0.0161 × Ageaccounting for 66% of the variance. The test has the following advantages over those currently employed:It is simple to administer requiring 6 minutes of stepping onto a 32 cm platform—the height of a gymnasium bench—20 times per minute.Although ideally an assessment oflean body mass is required, gross body weight plus age is a good second best.It is submaximal, minimising the stress on the individual (mean heart rate achieved 121 beats per minute).Its accuracy in terms of its ability to predict maximal aerobic power is better than either the Ohio or Harvard University tests.It is suggested that this test could be used where maximal testing is contraindicated or where currently used tests are insufficiently accurate.

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