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| ORIGINAL ARTICLE |
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| Year : 2018 | Volume
: 18
| Issue : 3 | Page : 128-135 |
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Stopping height growth and their outcome on aerobic fitness profile through elite soccer players
Mohammed Zerf
Sports Training Department, Physical Education Institute, Université Abdelhamid Ibn Badis Mostaganem, Mostaganem, Algeria
| Date of Web Publication | 6-Nov-2019 |
Correspondence Address:
Mohammed Zerf
Physical Education Institute, Université Abdelhamid Ibn Badis Mostaganem, Mostaganem
Algeria
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/sjsm.sjsm_31_17
Aim: It is understood at age 20 or 21 that men stop growing taller since testosterone causes epiphyseal closure, which prevents the long bones. In contrast to the increase in weight gain as body fat making weight loss difficult, as well as health problems associated with obesity. Our interest in this study deals with the superiority of anthropometric risk index in predicting the effect of stopping height growth on aerobic fitness profile. As the fundamental morphofunctional index risks documented by similar studies in its importance via adult elite soccer players.
Methods: The present study was based on standardizing data for maximum volume of oxygen (VO2max) categories fitness as morphofunctional characteristics versus waist circumference, body mass index, body shape index (ABSI), and body fat percent index (BFP). As the most anthropometric risk index for sixty adults, elite players in the Algerian championship, division one.
Results: Thus, the analyses statistics we confirm are as follows: (a) Stopping growing taller affect negatively all anthropometric risk index relative to VO2max in the opposite height. (b) Stopping growing taller increased the total body fat validity by ABSI z-score complimentary to ABSI as risk index predicting the impact stop height on body excess relative to aerobic fitness profile among elite soccer players. (c) Heart rate (HR) relates to ABSI z-score scoring are the superior's anthropometric index risk, taking into their account the fat distribution and their outcome of cardiovascular diseases narrates with O2 transportation or consumption.
Conclusions: The results of the current research allow us for the following conclusions: (1) the stopping growing taller increase the accumulation of fat, making the weight loss difficult at this stage of age. (2) Preventing the aftermath of the testosterone requires from the coach to appropriate training procedures based on dominant energy relative to the body changes compared to the levels of aerobic capacity. (3) RHR and ABSI z-score are the favorable anthropometric index risk, predicting the excess of body weight on the request aerobic fitness profile through soccer player.
Keywords: Adult elite soccer players, aerobic fitness profiles, anthropometric, risk index
How to cite this article:
Zerf M. Stopping height growth and their outcome on aerobic fitness profile through elite soccer players. Saudi J Sports Med 2018;18:128-35 |
How to cite this URL:
Zerf M. Stopping height growth and their outcome on aerobic fitness profile through elite soccer players. Saudi J Sports Med [serial online] 2018 [cited 2023 Sep 21];18:128-35. Available from: https://www.sjosm.org/text.asp?2018/18/3/128/270320 |
| Introduction | |  |
At age 20 or 21, men stop growing taller because testosterone causes epiphyseal closure, which prevents the long bones.[1] In the opposite of Weight Gain mostly accumulate based on fat,[2] making the weight loss difficult.[3] As well,[4] that is negatively correlated with physical capacity. Therefore, players at top level need to have a physical capacity related to the physiological demands required in soccer.[5] The frequent values quoted by similar studies in a game is about 10 km at an average distance, requiring maximum oxygen uptake of 60 ml/kg/min as moderate overall aerobic demand.[6] Whereas before soccer develop physiological requirements profile,[7] the international soccer match play [8] indicate the importance of individual anthropometric parameters in success of sportsmen.[9] Although morphofunctional features are the key tools for athletic training and choice of talent.[10] Considered in similar as the basis of technical and tactical development.[11] Manifested in the privies in their relation with nutritional aspects correlated with physical performance training, contribute to the success of an athlete, especially in high-performance sport.[12] However, the relationship between body mass index (BMI) and physical performance has not been clarified [13] as well as a body shape index (ABSI) as new measures of bodies [14] anthropometric risk index.[15] Through the above, the aim of the current study was inspected to determine the superiority of anthropometric index risks in predicting the effect of stopping taller on aerobic fitness profiles. Revoked in similar via morphofunctional index risks relative to weight gain Associate with testosteron anabolic effect.[16] However, the sports participation cannot guarantee physiological body mass and body composition, and it is necessary to prescribe an exercise targeting body mass and fat control.[17] Second, that individual with lower or normal, BMI performs better in physical fitness tests than overweight/obese or those with higher BMI.[18] Third, VO2max is inversely related to body fat or obesity, due to reductions in cardiac output. Fourth, VO2 is the more accurate predictors of appropriate training intensities for clinical, health, and sports populations than HR (HR) during moderate intensity exercise.[19] Through the above, the objectives of this study were to examine (a) the prevalence of overweight/obesity through this age, (b) the relationship between the anthropometric risk index and VO2max, and (c) their superiority to predict the impact of stopping height on aerobic fitness. For that, our assessment based on the maximum volume of oxygen (VO2max), using the indirect measurement tests, which presented good acceptance among indoor soccer players due to their high correlation with the direct measurement tests and their low cost and their attainment of important information, which will be helpful in the training prescribed [20] although this data can serve as a launching point for further research regarding the weight-control program for fitness and health among this specific age.
| Methods | | |
The Laboratory OPAPS Institute of Physical Education and Sports Department, Sports Training, University of Mostaganem approved the study. All participants are volunteers evaluated based on field tests within the same conditions and procedures, based on saving and baseline measurements. Using the resting heart rate (RHR: the number of heart beats per minute) as a indicator of fitness level measured in the morning upon awakening of the players.[21] Height was evaluated to the nearest 0.5 centimeters using a portable stadiometer. Weight was assessed to the nearest 0.1 kg using a portable medical scale. Waist circumference (WC) was ranked in a private screening area where three abdominal circumference measurements were taken at the level of the superior border of the iliac crest on the participant's right side using a standard measuring tape.[22] Anthropometric measurements were derived based on their formula collected in above whereas the levels and aerobic fitness morphofunctional characteristic profiles (VO2max) were collected based on Rexhepi et al.'s formula control by the test Cooper 12 min.
Procedures and participants
In this investigation, a descriptive correlation design was used to examine the association between anthropometric risk index and the morphofunctional levels, where we chose Elite male soccer players (n = 60, aged 21.1 ± 2.6 year, weight 78.89 ± 3.97 kg, height 177.87 ± 3.77 m, BMI 22.46 ± 1.84 kg/m 2 WC 83.01 ± 9 cm, ABSI 0.064 ± 0.0052, ABSI z-score − 0.40 ± 0.08, BF 16.31% ±2.79%, RHR 52.58 ± 1.96 beats and VO2max46.32 ± 5.21 [ml/kg/min]). All recruits in the current study are members of competitive sports clubs, volunteered for this study. Soccer clubs in the West Side league Oran football first division were invited to participate in this research. All the participants are holders in Team A. They had 5.8 ± 2.5 years. Training experience engaged in soccer training 4.3 ± 0.9 days weekly with each session lasting 1.4 ± 0.3 h, i.e., a total weekly training volume of 4.7 ± 1.4 h. Oral and written informed consent was received from all participants or parents after verbal explanation of the experimental design and potential risks of the study.
Equipment and protocols
Anthropometric risk index
A body shape index calculator
Body shape index (BSI) is a metric for assessing the health implications of a given human body height, mass, and WC. Whereas similar studies confirm that the BSI a better indicator of the health risks of excess weight than the standard BMI according to the formula for calculating is:[15]
A body shape index formula
ABSI z-score is calculated based on the mean and standard deviations of ABSI calculated for the given age and gender. ABSI z-score is used to identify the premature mortality risk level.
- ABSI z score = (ABSI − ABSImean)/ABSISD
- ABSImean = Means of calculate ABSI with respect to age and gender
- ABSISD = Standard deviation of calculating ABSI with respect to age and gender.
See the standards and the source through this link.[23] http://www.mytecbits.com/tools/medical/absi-calculator
The body fat percentage
Body fat percentage can be calculated using the following formulas:[24] Percentage body fat = 1.2 × BMI + 0.23 × (age) − 10.8 × (gender) − 5.4; in this equation, the value of gender is 1 for men and 0 for women.
Body mass index calculator
BMI can be used to indicate if you are overweight, obese, underweight, or normal.[25] A healthy BMI score is between 20 and 25. In case of the actual study, we use metric BMI formula:[26]
BMI = (Weight [in kg]/(Height [in m] × Height [m])
Morphofunctional characteristics level fitness profiles
Maximum volume of oxygen
VO2max is the volume of oxygen that an athlete can consume by exerting a maximum capacity which can measure fitness. VO2max is the maximum amount of oxygen in milliliters, one can use in one minute per kilogram of body weight. Since anthropometric risk index based on the BMI, we founded on VO2max-using age, BMI, and HRrest according to Rexhepi and Brestovci formula which researchers with 1500 active football players aged 16 to 35 produced the following equation based on the results of their Astrand Bike Test using their age, body mass and RHR.[27]
VO2max = 3.542 + (−0.014 × age) + (0.015 − body mass [kg]) + (−0.011 − RHR)
To check the validity of the previous test to estimate the VO2max. We based on the Cooper test, as a valid control test to estimate VO2max, as well as fitness and mortality for all causes, according to Winnick and Short.[28] Its application request from the player to run as far as possible within 12 min.[29] Whereas comparison between the two tests using the paired samples t-test is not significant in the opposite of Pearson correlation which is strongly positive.
Normative data for maximum volume of oxygen and their corresponding categories aerobic fitness
To analysis score VO2max, we use normative data (Heywood 2006) for male (values in ml/kg/min) and their categories to categorize our sample. Based on standards VO2max, we find that13.33% of total players are in the superior category, 8.33% in excellent, 23.33% in Good, and 55% in fairness.
Data analysis
All calculations present in the current study were carried out using Statistical Package for the Social Sciences (SPSS, IBM Corporation, Chicago, US) Version 20. According to the goals of the study, our statistical study was based on the computing of ANOVA one-way, Levene's, and correlation Pearson to compare implementations of the proposed. Regression analysis was used to predict the superiority of anthropometric risk index in the interpretation of morphofunctional characteristics level fitness profiles. P ≤ 0.05 was considered statistically significant.
| Results | | |
Through [Table 1], our total sample is categorized between fairness and superior category, according to the normative data set in [Table 2]. while to judge the performance of our total sample, we confirm their weakness (a) based on VO2max, according to the normative provided by Wells CM et al.'s VO2max(professional 56.5 ± 2.9 mL/kg/min; amateur 55.7 ± 3.5 mL/kg/min: P =0.484).[30] (b) founded on the RHR quoted we refer to the normative set by Peter Kokkinos between 30 and 40 bpm through elite athletes soccer players.[31] (c) Built on the difficulty of consuming VO2max enough energy to meet the high metabolic demands to maintain the rate of exercise endurance.[32] (d) Set up on the maximal oxygen uptake as measures related to metabolic and cardiorespiratory capacity among soccer players, according to McMillan et al.,[33] outcome revoked in previous as changes in energy expenditure related to weight maintenance energy.[34] Achieving an abnormal energy metabolism contributes to the further development of obesity.[35] The case of the current study, as well as BMI, set our sample in the normal category in the opposite of BFP between athletes and average. While the WC recognized our sample between very low and low risk, according to Porcari et al.[36] since the ABSI z-score records the sample in the lowest mortality risk categories giving to ABSI standards. whereas all study variables (weight, WC, IMC, ABSI and BFP) reject homogeneity, unlike height, ABSI z-score and VO2max based on Levene. Although ANOVA is significant in all comparisons practiced. Indicate to the researcher the state of our total sample, which is healthier than higher performers Interpreted in the context of this study, first, that at age 20 or 21, men stop growing taller because testosterone prevents the long bones, making further gains in length and the weight loss difficult. Second, the need for the individual to control weight change for long term [37] at this stage. Third, preserved the body composition changes in lean body mass, body weight, and body fat.[38] Particularly, at stop growing taller, due to testosterone, which prevents the long bones, as its loss may be related to increased androgen output, which has a fat-mobilizing effect.[39] Requiring 60% to 80% of the VO2max exercise training resulted in significant improvement in both global (performance and health),[40] the case of our Fair VO2max category. | Table 1: The characteristics of sample based on normative data for maximum volume of oxygen and their corresponding category fitness
Click here to view |
 | Table 2: Present normative data for maximum volume of oxygen categories aerobic fitness and comparison between Rexhepi versus Cooper based on paired samples t-test and pairwise correlation
Click here to view |
Through the [Table 3], all the comparisons VO2max and Height in the case of this study are inversely associated with other parameters chosen to study, strongly significant at P v ≈ 0.05 and 0.01. Our statement of accounts lines in one hand, with similar studies, the case of BMI, WC, BFP, ABSI, and ABSI z-score having a high inverse correlation with VO2max, due to excessive body fat, which can profoundly affect cardiovascular fitness as well as metabolic issues and even that affects other fitness components through the active athletes.[41] On the other hand, our finding shows that the highest positive correlation was found between VO2max (L/min) and body height, set by Gormley et al. in stature that is positively correlated with lung size more than any other anthropometric index and consequently, height is the reference variable of choice for most purposes.[42] Confirmed through soccer players in ideal body weights allied with differences between height and body build.[43] The case of the present study confirmed by the ANOVA and Levene's set in [Table 1]. While these results allow us to agreed that our fair aerobic fitness players' are faced to reducing their body FAT in order to improve their competitive performance advantages.
Through [Table 4], based on VO2max Vs, all Anthropometric indexes, the totality of the relationships analyzed between independent variables and predictors are significant at P ≤ 0.05. Where Model 1 program showed that ABSI z-score was able to explain the changes in the VO2max, confirmed by F and T as significant at P < 0.001 although Model 2program showed that ABSI z-score and height were able to explain the changes in the VO2max, where F and T are significant at P < 0.001. In addition, Model 3, the program showed that ABSI z-score, Height and ABSI were able to explain the changes in the VO2max, where F and T are significant at P < 0.001. On viewing these results, we confirm that ABSI z-score complimentary to ABSI and the change in height in predicting the effect of fat composition or distribution, owing to body loss difficult at this stage of human life, affecting the maximal oxygen uptake (VO2max), considered in similar as “gold standard” of cardiopulmonary health and the body's ability to adapt the body to metabolize demand.[44] and agreed by several studies in the firmness of ABSI as health index risk associated with HR variability and abdominal adiposity-related to defects of metabolic syndrome and cardiomyopathy risk factors.[45] | Table 4: Regression analyses relating maximum volume of oxygen and other indexes used in present study
Click here to view |
Through [Table 5], all the relationships analyzed between independent variables and predictors are significant at P ≤ 0.05. Based on the regression analyses relating VO2max and health risk index used in the current study, Model 1 program showed that HRH was able to explain the changes in the VO2max, where F and T are significant at P < 0.001. Toward Model 2, HRH and ABSI z score computed as predictive power of ABSI based on WC, Height to BMI was able to explain the changes in the VO2max, where F and T are significant at P < 0.001. Our findings line with the similar studies: first, ABSI expresses the excess risk from high WC complimentary to BMI and to other known risk factors.[14] Secondly, the strong correlation between excess body fat (BMI or BFP) support by cardiovascular increase.[46] Guide the researcher to confirm that stops of height in the opposite of the weight leads to increased cardiovascular risk factors and disease. Third, ABSI expresses the excess risk of obesity associated with metabolic abnormalities related to the risk blood lipids, cardiovascular disease, and reduce of aerobic fitness related to body fat responses to aerobic exercise testing or training.[47] Fourth, our results are in conformity with the pediatric strategy for attenuating cardiometabolic disease health risk among their population, based on optimizing health-related fitness and body composition related to cardiorespiratory endurance, as it is seen that they have the strongest links to health outcomes.[22] | Table 5: Regression analyses relating maximum volume of oxygen and health risk index used in the current study
Click here to view |
| Discussion | | |
Our findings in the present study show in the case of the levels morphofunctional based on VO2max and their related aerobic fitness profiles, all anthropometric used in the actual study represent important prerequisites for successful participation in a soccer game, perceived in their relation with VO2max, which is strongly negative in the opposite of height. A proof set by Allen and Prentice [48] that the BMI is considered to be one of the most objective anthropometric indices when it permits the correction of body weight for height, established by Yarbro et al.[49] in the case of estimate the adjusted body weight. Needing the detected of the excess body weight in the form of fat that Bean and Vorderman [50] report as a distinct disadvantage in almost every sport Sst in the present by VO2max correlation, strongly negative with all anthropometric risk index in the opposite height, as well as ABSI z-score, height, and ABSI as a superior factor predicting the effect of body fat composition or shape on the request levels of VO2max, expected in the similar as measurement capable of providing more information than other traditional anthropometric measures to predict adiposity-related health risks. Indicated in similar owing to trunk fat associated with cardiovascular and decrement of VO2max conducting to the decline in the effectiveness of the cardiovascular system.[51] Determined by Bassett DR Jr et al. in maximal oxygen uptake (VO2max) limited by the ability of the cardiorespiratory system to deliver oxygen to the exercising muscles from the air to the tissues at a given level of physical conditioning and oxygen availability according to Hawkins et al.[52] Results, which guide us to support the superiority of RHRs and ABSI in predicting the VO2max. Founded on similar studies, which confirm their associations with cardiorespiratory fitness and the metabolic syndrome. Claims by football studies via the ability of players to sustain the 150-250 brief intense actions a top-class player performs during a game, which also indicates that aerobic energy system is highly taxed, with mean and peak heart rates of around 85 and 98% of maximal values, requiring from top-class players a significant energy intake during a week.[53] This is confirmed in this study as a disadvantage related to body loss in this stage of life, inspected in the case of health risks related to level aerobic fitness narrate to anthropometric risk index in predicting the default of body fat loss at this age, agreeing by RHRs related to ABSI z-score as the only predictors of the body fat loss as a training process requiring from the coach to enhance the aerobic fitness levels. Guiding the searcher to indicate that coaches who understand the benefit of anthropometric risk index based on ABSI as a better predictor of energy metabolism can help their athletes to optimize their training by soliciting the dominant energy, affirmed by similar in low levels of energy expenditure and aerobic fitness that have been hypothesized to be risk factors for obesity [54] and overweight. While on the other hand, we acclaim the weaker of our fair players based on the findings of various studies that have found that the average intensity of a soccer match is around 75% of the player's aerobic capacity that is not the case of the totality of our players at this stage of age. For that, we refer to the principle of training that matching energy intake with expenditure can be challenging for competitive athletes through weight loss which is difficult in this stage of life, requiring from player to account its ideal weight based on multiple body measurements risk index as part of a weight-control program related to the VO2max, which is the best index for aerobic fitness and program body fat loss.[55]
| Conclusions | | |
Viewing most sports studies confirm that VO2max is the primary aims of fitness testing or training associated with the level of fitness and changes in the levels of body composition. It is an important element of success in sports achievements, indicating the levels of cardiorespiratory endurance and athletic fitness, needing from athletes to know their “ideal” body weight or “ideal” body composition related to their performance. Our approach based on phase age in the taller stop on the opposite of weight gain mostly accumulates as fat-making weight loss harder because of the degree of fat deposition occurs owing to the temporary reduction in testosterone secretion, which is also reflected in the greater long bone growth in this age, confirmed by similar through athletes with more 15%–18% body fat classified as fat or fatness and appreciated by large WC related to the excess of BMI, affecting VO2max and the cardiovascular status of the athletes record in the present as a phenomenon involving the coach to evaluate the anatomic-physiological and morphofunctional data. Based on the ABSI z-score as marking systems, complementary to ABSI. Highest in the present as a phenomenon involving from the coach to evaluate the anatomic-physiological and morphofunctional data. Founded on the ABSI z-score, as the superior anthropometric risk index. Predicting the excess of body weight associated with WC as paired measure to BMI in the interpretation of the aerobic fitness profiles among soccer players.
Recommendations
From the proof, the current study supports the hypothesis that athletes may support health training adaptations and performance by generally adequate diets and a cautious nutrient timing. However, in this stage of age and their characteristics, we agree that soccer players stop height request different body builds to expect the ideal body weights allied with aerobic fitness, necessitating some obsolete recommendations as the control of the body weight excess related to WC and BMI as the best way to maintain a good aerobic fitness compared to ideal weight founded on the effect of testosterone, which stops growth long bones, prevents the body weight loss and catabolism induced by cortisone through in this age station. See the limitations of this study; we agree that other studies are necessary to implement the actual results.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Rathus SA. Hdev + Online, 1 Term-6 Months Access Card. US: Wadsworth Publishing; 2017.  |
| 2. | Giampapa VC. The Principles and Practice of Antiaging Medicine for the Clinical Physician. Denmark: River Publishers; 2012. |
| 3. | Arem R. The Protein Boost Diet: Improve Your Hormone Efficiency for a Fast Metabolism and Weight Loss. US: Atria Books; 2014. |
| 4. | Talbott SM. The Cortisol Connection: Why Stress Makes You Fat and Ruins Your Health–and What You Can do About it. Alameda, CA: Hunter House; 2007. |
| 5. | Spinks W, Reilly T, Murphy A. Science and Football IV. UK: Routledge; 2002. |
| 6. | Tumilty D. Physiological characteristics of elite soccer players. Sports Med 1993;16:80-96. |
| 7. | National Soccer Coaches Association of America. The Soccer Coaching Bible. Champaign, IL: Human Kinetics; 2004. |
| 8. | Carling C, Williams AM, Reilly T. Handbook of Soccer Match Analysis: A Systematic Approach to Improving Performance. USA: Routledge; 2006. |
| 9. | Baker J, Farrow D. Routledge Handbook of Sport Expertise. USA: Routledge; 2015. |
| 10. | Leone M, Lariviere G, Comtois AS. Discriminant analysis of anthropometric and biomotor variables among elite adolescent female athletes in four sports. J Sports Sci 2002;20:443-9. |
| 11. | Chamari K, Hachana Y, Ahmed YB, Galy O, Sghaïer F, Chatard JC, et al. Field and laboratory testing in young elite soccer players. Br J Sports Med 2004;38:191-6. |
| 12. | Fidelix YL, Berria J, Ferrari EP, Ortiz JG, Cetolin T, Petroski EL, et al. Somatotype of competitive youth soccer players from Brazil. J Hum Kinet 2014;42:259-66. |
| 13. | Shen S, Li J, Guo Q, Zhang W, Wang X, Fu L, et al. Body mass index is associated with physical performance in suburb-dwelling older Chinese: A cross-sectional study. PLoS One 2015;10:e0119914. |
| 14. | Krakauer NY, Krakauer JC. A new body shape index predicts mortality hazard independently of body mass index. PLoS One 2012;7:e39504. |
| 15. | Krakauer NY, Krakauer JC. An anthropometric risk index based on combining height, weight, waist, and hip measurements. J Obes 2016;2016:8094275. |
| 16. | Nieschlag E, Behre HM. Testosterone: Action, Deficiency, Substitution. Cambridge: Cambridge University Press; 2006. |
| 17. | Nikolaidis PT. Elevated body mass index and body fat percentage are associated with decreased physical fitness in soccer players aged 12-14 years. Asian J Sports Med 2012;3:168-74. |
| 18. | Dupuis JM, Vivant JF, Daudet G, Bouvet A, Clément M, Dazord A, et al. Personal sports training in the management of obese boys aged 12 to 16 years. Arch Pediatr 2000;7:1185-93. |
| 19. | Solheim TJ, Keller BG, Fountaine CJ. VO 2 reserve vs. Heart rate reserve during moderate intensity treadmill exercise. Int J Exerc Sci 2014;7:311-7. |
| 20. | Jaguaribe de Lima AM, Gomes Silva DV, Soares de Souza AO. Correlation between direct and indirect VO2max measurements in indoor soccer players. Rev Bras Med Esporte 2005;11:159e. |
| 21. | Floyd PA, Mimms SE, Yelding C. Personal Health: Perspectives and Lifestyles. Belmont, CA: Thomson Wadsworth; 2003. |
| 22. | Burns RD, Brusseau TA, Fang Y, Fu Y, Hannon JC. Establishing waist-to-height ratio standards from criterion-referenced BMI using ROC curves in low-income children. J Obes 2016;2016:2740538. |
| 23. | |
| 24. | Plowman S, Smith D. Exercise Physiology for Health, Fitness, and Performance. Philadelphia: Wolters Kluwer Health/Lippincott Williams & Wilkins; 2008. |
| 25. | Zerf M. Obesity degrees and their relationships with weakness of musculoskeletal system among the obese housewife. Saudi J Sports Med 2017;17:7-13. Available from: http://www.sjosm.org/text.asp?2017/17/1/7/197458. [Last accessed on 2017 Jan 22]. |
| 26. | Mohammed Z. Body Fat Percentage (BFP) Versus Body Mass Index (BMI) which cassel parameter predict estimated Vital Capacities (VC) and the maximal aerobic capacity (VO2MAX). Cresco Int J Med 2016;1:1-6. Available from: http://www.crescopublications.org/pdf/cijm/CIJM-1-001.pdf. [Last accessed on 2017 Jan 22]. |
| 27. | Rexhepi AM, Brestovci B. Prediction of VO2max based on age, body mass, and resting heart rate. Hum Mov 2014;15:56-9. |
| 28. | Winnick JP, Short FX. Brockport Physical Fitness Test Manual: A Health-Related Assessment for Youngsters with Disabilities. 133 rd ed. Champaign, IL: Human Kinetics; 2014. |
| 29. | Ashok C. Test Your Physical Fitness. Delhi: Kalpaz Publications; 2008. |
| 30. | Wells CM, Edwards AM, Winter EM, Fysh ML, Drust B. Sport-specific fitness testing differentiates professional from amateur soccer players where VO 2max and VO2 kinetics do not. J Sports Med Phys Fitness 2012;52:245-54. |
| 31. | Kokkinos P. Physical Activity and Cardiovascular Disease Prevention. Sudbury, Mass: Jones and Bartlett; 2010. |
| 32. | Abernethy B. Biophysical Foundations of Human Movement. Champaign, IL: Human Kinetics; 2013. |
| 33. | McMillan K, Helgerud J, Macdonald R, Hoff J. Physiological adaptations to soccer specific endurance training in professional youth soccer players. Br J Sports Med 2005;39:273-7. |
| 34. | Ahima RS. Metabolic Basis of Obesity. New York: Springer; 2011. |
| 35. | Melmed S, Polonsky KS, Larsen PR, Kronenberg H. Williams Textbook of Endocrinology. Philadelphia: Elsevier; 2016. |
| 36. | Porcari JP, Bryant CX, Comana F. Exercise Physiology. Philadelphia, PA: F.A. Davis Company; 2015. |
| 37. | McComb JJ, Norman R, Zumwalt M. The Active Female: Health Issues Throughout the Lifespan. New York: Springer; 2014. |
| 38. | Kang J. Bioenergetics Primer for Exercise Science. Champaign, IL: Human Kinetics; 2008. |
| 39. | Malina RM, Bar-Or O. Bouchard C. Growth, Maturation, and Physical Activity. Champaign, Ill: Human Kinetics; 2004. |
| 40. | LeMura LM. Clinical Exercise Physiology: Application and Physiological Principles. Philadelphia: Lippincott Williams & Wilkins; 2004. |
| 41. | Kanosue K, Nagami T, Tsuchiya J. Sports Performance. Tokyo: Springer; 2015. |
| 42. | Gormley J, Hussey J. Exercise Therapy: Prevention and Treatment of Disease. Malden, Mass: Blackwell Publication; 2005. |
| 43. | Brown EW. Youth Soccer: A Complete Handbook. Dubuque, IA: Brown & Benchmark; 1992. |
| 44. | Maddox GL. The Encyclopedia of Aging: A Comprehensive Resource in Gerontology and Geriatrics. New York: Springer Publication; 2001. |
| 45. | Li WC, Chen IC, Chang YC, Loke SS, Wang SH, Hsiao KY, et al. Waist-to-height ratio, waist circumference, and body mass index as indices of cardiometabolic risk among 36,642 taiwanese adults. Eur J Nutr 2013;52:57-65. |
| 46. | Kopelman PG, Caterson I, Dietz W. Clinical Obesity in Adults and Children. Chichester: John Wiley & Sons; 2009. |
| 47. | Vivian HH, Ann G. Advanced Fitness Assessment and Exercise Prescription. Champaign, IL: Human Kinetics; 2014. |
| 48. | Allen L, Prentice A. Encyclopedia of Human Nutrition. US: Elsevier; 2005. |
| 49. | Yarbro CY, Frogge MH, Goodman M. Cancer Nursing: Principles and Practice. US: Jones & Bartlett Learning; 2005. |
| 50. | Bean A, Vorderman C. The Complete Guide to Sports Nutrition. US: A & C Black Publishers; 2000. |
| 51. | Halter JB, Ouslander JG, Tinetti M. Hazzard's Geriatric Medicine and Gerontology. 6 th ed. USA: McGraw Hill Professional; 2008. |
| 52. | Hawkins MN, Raven PB, Snell PG, Stray-Gundersen J, Levine BD. Maximal oxygen uptake as a parametric measure of cardiorespiratory capacity. Med Sci Sports Exerc 2007;39:103-7. |
| 53. | |
| 54. | Ashok C. Research Abstracts in Physical Education and Sports Sciences. Delhi: Kalpaz Publications; 2008. |
| 55. | Hodson M, Bush A, Geddes D. Cystic Fibrosis. 3 rd ed. US: CRC Press; 2012. |
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]
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