Asociación entre la composición corporal y la condición física en estudiantes de grado sexto, pertenecientes a la institución educativa moderna de Tuluá, Colombia año 2019 (Association between body composition and the physical condition in sixth grade st

Retos ◽  
2020 ◽  
pp. 539-546
Author(s):  
Luis Hebert Palma Pulido ◽  
Carlos Hernán Méndez Díaz ◽  
Alfonso Cespedes Manrrique ◽  
Jorge Andrés Castro Mejía ◽  
Alejandro Viveros Restrepo ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Body Mass ◽  
Fat Mass ◽  
Physical Condition ◽  
Pearson Correlation ◽  
Sixth Grade ◽  
The Body ◽  
Fat Percentage ◽  
Cardiovascular Capacity

 El siguiente estudio, tuvo como finalidad, determinar la correlación entre la composición corporal y la condición física en niños de sexto grado de la Institución Educativa de Tuluá, Colombia. El estudio fue no experimental, descriptivo y de alcance correlacional. La valoración de la composición corporal, se realizó mediante el índice de masa corporal y el porcentaje de grasa (fórmula de Slaughter y Lohmann). La condición física, se determinó por medio de la batería Fitnessgram. La muestra fue de 193 niños y niñas, entre ocho y 12 años. Los resultados se determinaron, por medio de estadísticos descriptivos y correlación de Pearson. Estos resultados, evidenciaron una r=-0,52 y -0,72 para niño y niña respectivamente, entre el porcentaje de grasa y la capacidad cardiovascular. Las correlaciones entre el índice de masa corporal y peso corporal, con el porcentaje de grasa fueron, r=0,59 niña 0,76 y niño y r=0,46 niña y 0,67 niño respectivamente, indicando que, a mayor masa corporal mayor grasa. La correlación entre masa grasa y el test de barra fija fue inversa, pero no alta, r=-0,23 y -0,24, sin embaro, cuando este test se correlacionó con el índice de masa corporal, dicha correlación fue mayor, r=-0,57 y -0,78, reflejando que, la masa corporal, afectó la resistencia en la barra. La flexibilidad y agilidad, no se alteraron por la masa grasa, r < 0,20. Como conclusión, se evidencia que, la masa grasa puede disminuir la capacidad cardiovascular y resistencia a la fuerza, sin embargo, la flexibilidad y la velocidad-agilidad pueden no alterarse.  Abstract. The following study aimed at determining the correlation between body composition and physical condition in sixth grade students from the high school Institución Educativa Moderna in Tuluá, Colombia. It was carried as a non-experimental, descriptive, and correlational study. The assessment of body composition was carried out using the body mass index and the fat percentage based on Slaughter and Lohmann formula. Physical condition was determined by using the Fitnessgram battery. The sample consisted of 193 boys and girls, around eight and 12 years old. The results were determined by means of descriptive statistics and Pearson correlation. These results showed r = -0.52 and -0.72 for boys and girls respectively, after correlating the percentage of fat and cardiovascular capacity. The correlation of their body mass index and their body weight, towards the percentage of fat were: r = 0.59 girl, 0.76 boy and r = 0.46 girl and 0.67 boy respectively, indicating that, the higher the body mass the higher the increase of fat. The correlation between fat mass and the fixed bar test was inverse, but not high: r = -0.23 and -0.24. However, when this test was correlated with the body mass index, that correlation was higher: r = -0.57 and -0.78, reflecting that the body mass affected the resistance at the bar. Flexibility and agility were not altered by fat mass: r <0.20. In conclusion, it is evidenced that fat mass can decrease cardiovascular capacity and resistance to strength, however, flexibility and speed-agility may not be altered.

scholarly journals Body Mass Index and Measures of Body Fat for Defining Obesity and Underweight: A Cross-Sectional of Various Specialties in Montenegrin Army Soldiers

2020 ◽  
Author(s):  
Stevo POPOVIC ◽  
Boris BANJEVIC ◽  
Bojan MASANOVIC ◽  
Dusko BJELICA
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Physical Fitness ◽  
Body Mass ◽  
Body Fat ◽  
Armed Forces ◽  
The Body ◽  
Fat Percentage ◽  
Anthropometric Measures ◽  
General Terms

Background: The body composition and physical fitness of members of the army is always a relevant topic for research, since the level of defense and security of people and material goods in a specific territory in many ways depends on the level of ability of the army. However, members of the armed forces are a heterogeneous group, typified by different abilities, characteristics, but also everyday needs, and the trend of changing body composition and reducing physical fitness is a current issue that has not bypassed this population either. Therefore, this study aimed to determine possible differences in body composition indicators that could appear between members of the Army of Montenegro of different military specialties. Methods: The sample of respondents included 240 Montenegrin male soldiers (32.5yr±9.5), who were measured at the sports dispensaries within the barracks of Montenegrin Army around the country in the spring of 2020, was classified into eight numerically equal subsamples according to their military specialty. The sample of variables included five anthropometric measures, which were necessary to calculate two derived body composition indicators: Body Mass Index (BMI) and Body Fat Percentage (FAT %). Using the one-way ANOVA and Post Hoc test with Taki’s model, the variables were analyzed. Results: It was determined that the body composition of Montenegrin soldiers shows a certain peculiarity compared to other national military corps, while there are differences in body composition indicators between members of the Montenegrin Army of different military specialties. Conclusion: This fact dramatically strengthens the issues of Montenegrin distinctive regarding body composition, both in general terms and in terms of distinctive within specific professional vocations.  

scholarly journals Body mass index, physical activity, and physical fitness of adolescence

2021 ◽  
Vol 10 (2) ◽  
Author(s):  
Ratna Candra Dewi ◽  
Nanda Rimawati ◽  
Purbodjati Purbodjati
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Body Composition ◽  
Physical Fitness ◽  
Body Mass ◽  
Fat Mass ◽  
Pearson Correlation ◽  
Moderate Physical Activity ◽  
Normal Body Mass Index ◽  
Mass Percentage

Background: Adolescents experience growth and significant changes in body composition which influence physical activity and response to sport or exercise. The level of physical fitness in adolescent girls is usually lower than that of boys, due to differences in body composition and levels of physical activity. The aim of this study was to examine the relationship between fat mass percentage, body composition, physical activity, and physical fitness.Design and Methods: This study used an analytical observational, and cross-sectional design with total samples consisting of 70 male and female students aged 14-15 years. They were selected through simple random sampling, and the data collected were anthropometric measurements, body composition, physical activity and physical fitness. In addition, the Pearson correlation test was used for data analysis.Results: The results showed that 68.57% of participants had a normal body mass index, 74.3% had moderate physical activity, and 44.28% had fat mass percentage including an obesity category and, 54.29% had low physical fitness. Furthermore, the Pearson test showed a significant relationship between physical activity, body mass index and fat mass percentage with physical fitness.Conclusions: An increased fat mass percentage is associated with decreased levels of physical fitness. Furthermore, a good determinant of low physical fitness in obese conditions is the percentage of fat mass rather than BMI.

scholarly journals Evaluation of spirometric parameters and maximum oxygen consumption in athletes and non-athletes

2018 ◽  
Vol 71 (5-6) ◽  
pp. 157-161
Author(s):  
Aleksandra Rakovac ◽  
Lana Andric ◽  
Vedrana Karan ◽  
Maja Bogdan ◽  
Danijel Slavic ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Oxygen Consumption ◽  
Body Mass ◽  
Body Fat ◽  
Fat Mass ◽  
The Body ◽  
Body Fat Mass ◽  
Maximum Oxygen Consumption ◽  
Low Degree

Introduction. There is a great interest to identify factors that influence the value of maximum oxygen consumption. The goal of this research was to assess the body composition, pulmonary parameters, and maximum oxygen consumption in different types of sports and in non-athletes. Material and Methods. The research included 149 male participants: aerobic athletes (n = 55), anaerobic athletes (n = 53) and non-athletes (n = 41). The participants were tested at the Department of Physiology, Faculty of Medicine of the University of Novi Sad. Anthropometric parameters and body mass index were measured. Also, the body fat mass was determined by bioelectrical impedance. pulmonary parameters by spirometry and maximum oxygen consumption on a bicycle ergometer. Results. The body mass index values in non-athletes were the highest and significantly different compared to the aerobic athletes (p = 0.01). Also, non-athletes had significantly higher values of body fat mass compared to athletes (p < 0.001). The pulmonary parameters were not significantly different between the tested groups (p > 0.05). However. the values of maximum oxygen consumption were significantly different between all three tested groups (aerobic athletes 53.75 ? 7.82 ml/kg/min; anaerobic athletes 48.04 ? 6.79 ml/kg/min; non-athletes 41.95 ? 8.53 ml/kg/min) (p < 0.001). A low degree of correlation was found between maximum oxygen consumption and pulmonary parameters in the tested groups. Conclusion. Body composition has an impact on the pulmonary parameters. The values of maximum oxygen consumption depend on the type of sport and training. and the highest values are in aerobic sports. There is a low degree of correlation between maximum oxygen consumption and pulmonary parameters in the tested groups.

scholarly journals Differences in Fat Mass Estimation Formulas in Physically Active Adult Population and Relationship with Sums of Skinfolds

2020 ◽  
Vol 17 (21) ◽  
pp. 7777 ◽  
Author(s):  
Raquel Vaquero-Cristóbal ◽  
Mario Albaladejo-Saura ◽  
Ana E. Luna-Badachi ◽  
Francisco Esparza-Ros
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Body Mass ◽  
Fat Mass ◽  
Adult Population ◽  
The Body ◽  
Physically Active ◽  
Mass Estimation ◽  
Active Adults ◽  
And Training

Changes in body composition and specifically fat mass, has traditionally been used as a way to monitor the changes produced by nutrition and training. The objective of the present study was to analyse the differences between the formulas used to estimate fat mass and to establish the existing relationship with the body mass index and sums of skinfolds measurement in kinanthropometry. A total of 2458 active adults participated in the study. Body mass index (BMI) and skinfolds were measured, and the Kerr, Durnin-Womersley, Faulkner and Carter equations were used to assess fat mass. Significant differences were found between all the formulas for the percentage of fat mass, ranging from 10.70 ± 2.48 to 28.43 ± 5.99% (p < 0.001) and fat mass from 7.56 ± 2.13 to 19.89 ± 4.24 kg (p < 0.001). The correlations among sums of skinfolds and the different equations were positive, high and significant in all the cases (r from 0.705 to 0.926 p < 0.001), unlike in the case of BMI, were the correlation was lower and both positive or negative (r from −0.271 to 0.719; p < 0.001). In conclusion, there were differences between all the formulas used to estimate fat mass; thus, for the evaluation of fat mass with kinanthropometry of an active adult, the use of the same formula is recommended on all occasions when the results are going to be compared or when an athlete is compared with a reference.

scholarly journals The Relationship between Physical Activity, Body Mass Index and Body Composition among Students at a Pre-University Centre in Malaysia

2020 ◽  
Vol 19 (2) ◽  
Author(s):  
You HW ◽  
Tan PL ◽  
Mat Ludin AF
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Body Composition ◽  
University Students ◽  
Muscle Mass ◽  
Body Mass ◽  
Fat Mass ◽  
The Body ◽  
Study Results ◽  
The Relationship

INTRODUCTION: Physical activity is an essential element in our daily life that leads to long-term health benefits. Physical activity refers to movement of the body that requires energy. Body mass index (BMI) indicates a ratio of body weight to squared height, which is a useful health indicator. On the contrary, body composition describes the body by measuring percentages of fat and muscle in human bodies. MATERIALS AND METHODS: This cross-sectional study aimed to determine the relationship between physical activities, BMI and body composition among pre-university students from one of the universities in Selangor, Malaysia. Stratified random sampling was employed to recruit 70 pre-university students into this study. RESULTS: From the study, 50% of the respondents are categorized as minimally active. In addition, there is significant difference between the physical activity levels of male and female respondents. The relationship between physical activity and BMI indicates a very weak negative correlation. Similarly, the correlation between physical activity and fat mass is a weak negative relationship. Meanwhile, there is a weak positive correlation between physical activity and muscle mass. CONCLUSION: Therefore, it can be concluded that when physical activity increases, BMI and body fat mass will decrease, while muscle mass will increase. Moreover, it was shown that there was a significant relationship between physical activity and body composition. 

scholarly journals The Anthropometric Generalization of the Body Mass Index

2020 ◽  
Author(s):  
alexandru godescu
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Body Mass ◽  
Body Fat ◽  
The Body ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
The Difference ◽  
The 19Th Century ◽  
Highly Cited

The classic Body Mass Index, (BMI), developed in the 19th century by the Belgian mathematician Adolphe Quetelet [1] is an important indicator of the risk of death, of obesity, of negative health consequences, body fat percentage and of the shape of the body. While he BMI is assumed to indicate obesity in sedentary people and in people who do not practice sports, it is undisputed and a consensus among researchers [2][3][4][5][9][25] that Body Mass Index (BMI) is not a good indicator for obesity in people who developed their body through heavy physical work or sport but also in other segments of population such as those who appear to have a normal weight but in fact have a high body fat percentage and obese methabolism. The BMI also does not include all the variables essential for a health predictor. The BMI is not always a good predictor of metabolic disease, people who appear of healthy weight according to BMI have in some cases an obese metabolic syndrome. The BMI was developed as a law of natural sciences and &ldquo;social physics&rdquo; [1], as it was called then, before the middle of the 19th century, and it had been used from the 70s for medical purposes, to detect obesity and the risk of mortality [6][7]. The BMI has a huge importance for modern society, affected by an obesity epidemic [8]. BMI has applications in medicine, sport medicine, sport, fitness, bodybuilding, insurance, nutrition, pharmacology. The main limitation of the BMI is that it does not account for body composition including non fat body mass such as muscles, joints, body frame and makes no difference between fat and non fat components of the body weight. The body composition and the proportion of fat and muscles make a difference in health outcomes [12][13][14][25][26][27][35][36][37] [38][39][40][41][42][43][44]&hellip;[100]. Body composition makes a difference also in the level of sport performance for athletes of every level. In nearly two centuries since the Body Mass Index was developed, no formula had been successfully developed to account for body composition and make the difference between muscle and fat in a consistent way. This can be considered a longstanding open problem of major importance for society. The objective of this analysis is to develop new formulae taking into account the health implication of body composition measured through indirect, simple indicators and making the difference between muscles and fat, healthy and non healthy metabolism. The formulae developed in this article are the only formula to successfully generalize BMI and make this difference. I develop a direct generalization of BMI, in the mathematical and physiological sense to account for fat and fat free mass and muscles, small and large body frames. It is the first such generalization because the classic BMI can be determined as a particular case of my formulae in the strict mathematical and practical physiologic sense. No other formula generalized the BMI to make the difference between fat and a large frame and muscles has ever been published in nearly two centuries since the BMI formula had been developed. The formulae I developed explain and generalize the conclusions of a large number of highly cited empirical experiments cited in the reference section. [35][36][37][38][38][39] [40][42][43][44]..[100] Most of the experimental proof I bring in support of my formulae and bodyweight quantification theory comes from many highly cited experimental research publications in medicine, sports medicine, sport science and physiology. My formulae explain also performance in decades of competitive sports and athletics

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.

scholarly journals Seasonal and Longitudinal Changes in Body Composition by Sport-Position in NCAA Division I Basketball Athletes

Sports ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 85 ◽  
Author(s):  
Jennifer Fields ◽  
Justin Merrigan ◽  
Jason White ◽  
Margaret Jones
Keyword(s):  
Body Composition ◽  
Body Mass ◽  
Body Fat ◽  
Fat Mass ◽  
Ncaa Division I ◽  
The Body ◽  
Fat Free Mass ◽  
Strength And Conditioning ◽  
Air Displacement Plethysmography ◽  
Within Subjects

The purpose of this study was to assess the body composition of male and female basketball athletes (n = 323) across season, year, and sport-position using air displacement plethysmography. An independent sample t-test assessed sport-position differences. An analysis of variance was used to assess within-subjects across season (pre-season, in-season, and off-season), and academic year (freshman, sophomore, and junior). For both men and women basketball (MBB, WBB) athletes, guards had the lowest body fat, fat mass, fat free mass, and body mass. No seasonal differences were observed in MBB, but following in-season play for WBB, a reduction of (p = 0.03) in fat free mass (FFM) was observed. Across years, MBB showed an increase in FFM from freshman to sophomore year, yet remained unchanged through junior year. For WBB across years, no differences occurred for body mass (BM), body fat (BF%), and fat mass (FM), yet FFM increased from sophomore to junior year (p = 0.009). Sport-position differences exist in MBB and WBB: Guards were found to be smaller and leaner than forwards. Due to the importance of body composition (BC) on athletic performance, along with seasonal and longitudinal shifts in BC, strength and conditioning practitioners should periodically assess athletes BC to ensure preservation of FFM. Training and nutrition programming can then be adjusted in response to changes in BC.

Sign in / Sign up

Export Citation Format

Share Document