Effect of Hypohydration on Muscle Endurance, Strength, Anaerobic Power and Capacity and Vertical Jumping Ability: A Meta-Analysis

2015 ◽  
Vol 45 (8) ◽  
pp. 1207-1227 ◽  
Author(s):  
Félix-Antoine Savoie ◽  
Robert W. Kenefick ◽  
Brett R. Ely ◽  
Samuel N. Cheuvront ◽  
Eric D. B. Goulet
Keyword(s):  
Meta Analysis ◽  
Anaerobic Power ◽  
Muscle Endurance ◽  
Endurance Strength ◽  
Vertical Jumping

Trunk muscle endurance, strength and flexibility in rural subsistence farmers and urban industrialized adults in western Kenya

2021 ◽  
Author(s):  
Benjamin E. Sibson ◽  
Victoria A. Tobolsky ◽  
Timothy M. Kistner ◽  
Nicholas B. Holowka ◽  
Josphine Jemutai ◽  
...  
Keyword(s):  
Trunk Muscle ◽  
Muscle Endurance ◽  
Subsistence Farmers ◽  
Western Kenya ◽  
Endurance Strength

scholarly journals Do exercise-associated genes explain phenotypic variance in the three components of fitness? a systematic review & meta-analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0249501
Author(s):  
Henry C. Chung ◽  
Don R. Keiller ◽  
Justin D. Roberts ◽  
Dan A. Gordon
Keyword(s):  
Systematic Review ◽  
Candidate Genes ◽  
Meta Analysis ◽  
Anaerobic Power ◽  
Significant Proportion ◽  
Training Group ◽  
Cardiovascular Fitness ◽  
Specific Gene ◽  
Phenotypic Variance ◽  
Three Components

The aim of this systematic review and meta-analysis was to identify a list of common, candidate genes associated with the three components of fitness, specifically cardiovascular fitness, muscular strength, and anaerobic power, and how these genes are associated with exercise response phenotype variability, in previously untrained participants. A total of 3,969 potentially relevant papers were identified and processed for inclusion. After eligibility and study selection assessment, 24 studies were selected for meta-analysis, comprising a total of 3,012 participants (male n = 1,512; females n = 1,239; not stated n = 261; age 28 ± 9 years). Meta-Essentials spreadsheet 1.4 (Microsoft Excel) was used in creating the forest plots and meta-analysis. IBM SPSS statistics V24 was implemented for the statistical analyses and the alpha was set at p ≤ 0.05. 13 candidate genes and their associated alleles were identified, which were associated with the phenotypes of interest. Analysis of training group data showed significant differential phenotypic responses. Subgroup analysis showed; 44%, 72% and 10% of the response variance in aerobic, strength and power phenotypes, respectively, were explained by genetic influences. This analysis established that genetic variability explained a significant proportion of the adaptation differences across the three components of fitness in the participants post-training. The results also showed the importance of analysing and reporting specific gene alleles. Information obtained from these findings has the potential to inform and influence future exercise-related genes and training studies.

scholarly journals Do exercise-associated genes explain phenotypic variance in the three components of fitness? A Systematic review & Meta-analysis.

2021 ◽  
Author(s):  
Henry Chung ◽  
Justin D Roberts ◽  
Don R KEILLER ◽  
Dan A Gordon
Keyword(s):  
Systematic Review ◽  
Candidate Genes ◽  
Meta Analysis ◽  
Anaerobic Power ◽  
Significant Proportion ◽  
Training Group ◽  
Cardiovascular Fitness ◽  
Specific Gene ◽  
Phenotypic Variance ◽  
Three Components

The aim of this systematic review and meta-analysis was to identify a list of common, candidate genes associated with the three components of fitness, specifically cardiovascular fitness, muscular strength, and anaerobic power, and how these genes are associated with exercise response phenotype variability, in previously untrained participants. A total of 3,969 potentially relevant papers were identified and processed for inclusion. After eligibility and study selection assessment, 24 studies were selected for meta-analysis, comprising a total of 3,012 participants. Meta-Essentials spreadsheet 1.4 (Microsoft Excel) was used in creating the forest plots and meta-analysis. IBM SPSS statistics V24 was implemented for the statistical analyses and the alpha was set at p ≤ 0.05. 13 candidate genes and their associated alleles were identified, which were associated with the phenotypes of interest. Analysis of training group data showed significant differential phenotypic responses. Subgroup analysis showed; 44%, 72% and 10% of the response variance in aerobic, strength and power phenotypes, respectively, were explained by genetic influences. This analysis established that genetic variability explained a significant proportion of the adaptation differences across the three components of fitness in the participants post-training. The results also showed the importance of analysing and reporting specific gene alleles. Information obtained from these findings has the potential to inform and influence future exercise-related genes and training studies.

scholarly journals The Effect of Core Strength Training on Core Muscle Endurance, Balance, Agility and Anaerobic Power in Adolescent Basketball Players

2020 ◽  
Vol 12 (3) ◽  
pp. 274-282
Author(s):  
Nihan KAFA ◽  
Pelin AKSEN CENGİZHAN ◽  
Gamze ERİKOĞLU ÖRER ◽  
Gamze ÇOBANOĞLU ◽  
Çağatay Müslüm GÖKDOĞAN ◽  
...  
Keyword(s):  
Strength Training ◽  
Anaerobic Power ◽  
Muscle Endurance ◽  
Basketball Players ◽  
Core Strength

scholarly journals COMPARISON OF BLOOD PARAMETERS AND SOME MOTOR PERFORMANCE VALUES IN A FACULTY OF SPORT SCIENCES STUDENTS

2020 ◽  
Vol 6 (8) ◽  
Author(s):  
Feyzullah Koca
Keyword(s):  
Low Density Lipoprotein ◽  
Anaerobic Power ◽  
Density Lipoprotein ◽  
Blood Parameters ◽  
Soccer Players ◽  
Vertical Jumping ◽  
Disease Risks ◽  
Judo Athletes ◽  
Aerobic And Anaerobic ◽  
One Way Anova

In this study is proposing to compare lipid and lipoprotein values in faculty of sport sciences students in order to investigate cardiovascular disease risks. The research included sports-educated college students. They were 20 wrestlers, 25 judo athletes and 30 soccer players. Comparison of age and height were used in the research and, to identify the differences among groups, one-way Anova and Scheffe tests were performed. In this study, vertical jumping value was not found statistically significant among the groups (p> 0.05). In this study, aerobic and anaerobic power of the educated wrestlers and judo athletes were found to be different than the soccer players (p <0.05). In our study, wrestlers and judo athletes’ values are clearly higher than the values soccer players group in terms of total cholesterol (TC), triglyceride (TG), low density lipoprotein (LDL-C) amounts (p<0.01). In our study, wrestlers and judo athletes’ values are found to be significantly lower than the values soccer players in terms of high-density lipoprotein (HDL-C) amounts (p<0.01). The ratio TC / HDL-C and LDL-C / HDL-C of educated judo athletes and wrestlers is higher than soccer players (p<0.05). Conclusion: Faculty of sport sciences students who wrestlers, judo athletes and soccer players were found to be different in blood fat values. This difference in bloods fat are thought to be due to their training. Healthy risk factors for cardiovascular diseases of all three branch athletes were found to be low. Wrestler and Judo players were recommended to include more aerobic activities in their trainings. <p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0723/a.php" alt="Hit counter" /></p>

THE COMPARISON OF THE STRUCTURAL AND MOTORIC PROPERTIES OF JUNIOR PLAYERS ACCORDING TO THEIR POSITIONS IN SOCCER

2021 ◽  
Vol 0 (38) ◽  
pp. 0-0
Author(s):  
Halit EGESOY ◽  
Hayrettin GÜMÜŞDAĞ ◽  
İzzet KIRKAYA ◽  
Aydın İLHAN ◽  
Arif Süleyman IŞIK
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Body Fat ◽  
Anaerobic Power ◽  
The Other ◽  
Soccer Players ◽  
Body Fat Percentage ◽  
Fat Percentage ◽  
Speed Test ◽  
Vertical Jumping

Aim: The purpose of this study was made a comparison of young soccer players according to their positions in game in terms of structural and motoric properties. Method: Total 41 soccer players who were between 16-18 ages participated voluntary to this study. Age, height, weight, body mass index, body fat percentage, vertical jumping, anaerobic power,10m -30m speed values were determined. The data were analyzed statistically with SPSS program. Results: At the end of this study, the defender players were taller and heavier than the other position’s players. But this difference was not significant statistically (p<0.05). Conclusion: The attack players were faster than the others in 10m speed test. This difference was significant (p<0.05). In other measurements, there were no relations statistically according to the player’s positions.

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