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Role of physique and physical fitness in the balance of Korean national snowboard athletes.

ABSTRACT: Background:The objective of this study is to understand the relationship between physique, physical fitness, and balance performance for snowboard athletes. Methods:We considered all Korean national snowboard athletes (n = 9 with 6 males and 3 females, age = 17.44 ± 4.42), who have an experience of competition at continental cup level, to measure their physique, physical fitness, and (both static and dynamic) balance. Static balance was evaluated based on one-legged standing, while dynamic balance was estimated using a stability platform. Results:Static balance is strongly correlated (p < 0.05) with circumference of the left lower leg (34.49 ± 2.42 cm; ? = 0.68), sit-up (57.56 ± 8.8; ? = 0.72), sargent jump (50.22 ± 11.78 cm; ? = 0.67), strength of bench press (39.11 ± 17.73 kg; ? = 0.67), angle of left ankle dorsiflexion (73.78 ± 7.86°; ? = 0.77), average extension strength at 180° for left knee (321 ± 63.95 %BW; ? = 0.77) and right knee (337 ± 60.32 %BW; ? = 0.77), and right knee peak flexion strength at 60° (148 ± 25.61 %BW; ? = 0.73). Center dynamic balance is negatively correlated with circumference of the right lower leg (34.63 ± 2.38 cm; ? = -0.67, p < 0.05), while right dynamic balance is positively correlated with left ankle flexion (148.44 ± 5.20°; ? = 0.78, p < 0.05). Conclusion:Static balance is related to core muscle endurance and power, ankle flexibility, and knee stability, while dynamic balance is negatively correlated with circumference of the most frequently used lower leg (i.e., the leg dominating the snowboarding stance). The relationship between physique, physical fitness, and balance provides an insight into improving the balance performance of elite snowboard athletes through a training program that can affect the physique and physical fitness factors related to balance.

SUBMITTER: Jeon Y

PROVIDER: S-EPMC7452248 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Role of physique and physical fitness in the balance of Korean national snowboard athletes.

Jeon Youngirl Y Eom Kilho K

Journal of exercise science and fitness 20200705 1

<h4>Background</h4>The objective of this study is to understand the relationship between physique, physical fitness, and balance performance for snowboard athletes.<h4>Methods</h4>We considered all Korean national snowboard athletes (n = 9 with 6 males and 3 females, age = 17.44 ± 4.42), who have an experience of competition at continental cup level, to measure their physique, physical fitness, and (both static and dynamic) balance. Static balance was evaluated based on one-legged standing, whil ...[more]

PMID: 32904222

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Project description:Objectives:The aim of this study was to assess the relationships between functional movement screen (FMS), star excursion balance test (SEBT), agility T test, and vertical jump test scores and sports injury risk in junior athletes. We compared these assessments and the differences between groups with high and low risks of sports injury. Subjects and Methods. Eleven volleyball, 12 basketball, and 9 handball athletes were recruited. All participants followed the routine training in school sports teams. Weekly training schedules followed a similar pattern. The 32 junior athletes (age = 16.06 ± 0.21?years; height = 167.28 ± 6.32?cm; and body?mass = 68.45 ± 9.67?kg) were assessed using the FMS, SEBT, agility T test, and vertical jump test in random order. The correlations of composite and individual item scores of these assessments were analyzed, and the differences between groups with high and low risks of sports injury were compared. Results:All participants completed the study protocol. No significant differences were observed between FMS, SEBT, agility T test, and vertical jump test scores in groups with high and low risks of sports injuries. Fair and moderate-to-good correlations were observed for anterior reach maximum of SEBT and deep squat (r = 0.47, P = 0.02) as well as inline lunge (r = 0.53, P = 0.01) of FMS. The hurdle step of FMS also exhibited moderate-to-good (r = 0.52, P = 0.01) and fair (r = 0.42, P = 0.04) correlations with posterior medial and posterior lateral reach maximum of SEBT, respectively. A fair correlation was observed between posterior lateral reach maximum of SEBT and rotary stability of FMS (r = -0.23, P = 0.03). Fair and moderate-to-good correlations were identified for agility T test and maximum anterior reach in the SEBT (r = -0.42, P = 0.04) and trunk stability push-up in the FMS, respectively (r = -0.57 and P = 0.006). Conclusions:Junior athletes with a high risk of sports injury did not exhibit differences in terms of FMS, SEBT, and physical fitness test scores. Deep squat, hurdle step, inline lunge, and rotary stability scores in the FMS were correlated with the item scores in the SEBT, which may be due to the use of similar movement patterns. Scores for anterior reach maximum in the SEBT and trunk stability push-up in the FMS were correlated with agility T test scores, suggesting a similar task requirement of trunk stability and dynamic weight shifting ability.

Project description:IntroductionPhysical fitness is regarded as a significant indicator of sarcopenia. This study aimed to develop and evaluate a deep-learning model for predicting the decline in physical fitness due to sarcopenia in individuals with potential sarcopenia.MethodsThis study used the 2010-2023 Korean National Physical Fitness Award data. The data comprised exercise- and health-related measurements in Koreans aged >65 years and included body composition and physical fitness variables. Appendicular muscle mass (ASM) was calculated as ASM/height2 to define normal and possible sarcopenia. The deep-learning model was created with EarlyStopping and ModelCheckpoint to prevent overfitting and was evaluated using stratified k-fold cross-validation (k = 5). The model was trained and tested using training data and validation data from each fold. The model's performance was assessed using a confusion matrix, receiver operating characteristic curve, and area under the curve. The average performance metrics obtained from each cross-validation were determined. For the analysis of feature importance, SHAP, permutation feature importance, and LIME were employed as model-agnostic explanation methods.ResultsThe deep-learning model proved effective in distinguishing from sarcopenia, with an accuracy of 87.55%, precision of 85.57%, recall of 90.34%, and F1 score of 87.89%. Waist circumference (WC, cm), absolute grip strength (kg), and body fat (BF, %) had an influence on the model output. SHAP, LIME, and permutation feature importance analyses revealed that WC and absolute grip strength were the most important variables. WC, figure-of-8 walk, BF, timed up-and-go, and sit-and-reach emerged as key factors for predicting possible sarcopenia.ConclusionThe deep-learning model showed high accuracy and recall with respect to possible sarcopenia prediction. Considering the need for the development of a more detailed and accurate sarcopenia prediction model, the study findings hold promise for enhancing sarcopenia prediction using deep learning.

Project description:Regular physical activity seems to have a positive effect on the microbiota composition of the elderly, but little is known about the added possible benefits of strenuous endurance training. To gain insight into the physiology of the elderly and to identify biomarkers associated with endurance training, we combined different omics approaches. We aimed to investigate the gut microbiome, plasma composition, body composition, cardiorespiratory fitness, and muscle strength of lifetime elderly endurance athletes (LA) age 63.5 (95% CI 61.4, 65.7), height 177.2 (95% CI 174.4, 180.1) cm, weight 77.8 (95% CI 75.1, 80.5) kg, VO2max 42.4 (95% CI 39.8, 45.0) ml.kg-1.min-1 (n = 13) and healthy controls age 64.9 (95% CI 62.1, 67.7), height 174.9 (95% CI 171.2, 178.6) cm, weight 83.4 (95% CI 77.1, 89.7) kg, VO2max 28.9 (95% CI 23.9, 33.9), ml.kg-1.min-1 (n = 9). Microbiome analysis was performed on collected stool samples further subjected to 16S rRNA gene analysis. NMR-spectroscopic analysis was applied to determine and compare selected blood plasma metabolites mostly linked to energy metabolism. The machine learning (ML) analysis discriminated subjects from the LA and CTRL groups using the joint predictors Bacteroides 1.8E + 00 (95% CI 1.1, 2.5)%, 3.8E + 00 (95% CI 2.7, 4.8)% (p = 0.002); Prevotella 1.3 (95% CI 0.28, 2.4)%, 0.1 (95% CI 0.07, 0.3)% (p = 0.02); Intestinimonas 1.3E-02 (95% CI 9.3E-03, 1.7E-02)%, 5.9E-03 (95% CI 3.9E-03, 7.9E-03)% (p = 0.002), Subdoligranulum 7.9E-02 (95% CI 2.5E-02, 1.3E-02)%, 3.2E-02 (95% CI 1.8E-02, 4.6E-02)% (p = 0.02); and the ratio of Bacteroides to Prevotella 133 (95% CI -86.2, 352), 732 (95% CI 385, 1079.3) (p = 0.03), leading to an ROC curve with AUC of 0.94. Further, random forest ML analysis identified VO2max, BMI, and the Bacteroides to Prevotella ratio as appropriate, joint predictors for discriminating between subjects from the LA and CTRL groups. Although lifelong endurance training does not bring any significant benefit regarding overall gut microbiota diversity, strenuous athletic training is associated with higher cardiorespiratory fitness, lower body fat, and some favorable gut microbiota composition, all factors associated with slowing the rate of biological aging.

Project description:The aim of this study was to establish maturation-, age-, and sex-specific anthropometric and physical fitness percentile reference values of young elite athletes from various sports. Anthropometric (i.e., standing and sitting body height, body mass, body mass index) and physical fitness (i.e., countermovement jump, drop jump, change-of-direction speed [i.e., T-test], trunk muscle endurance [i.e., ventral Bourban test], dynamic lower limbs balance [i.e., Y-balance test], hand grip strength) of 703 male and female elite young athletes aged 8-18 years were collected to aggregate reference values according to maturation, age, and sex. Findings indicate that body height and mass were significantly higher (p<0.001; 0.95≤d≤1.74) in more compared to less mature young athletes as well as with increasing chronological age (p<0.05; 0.66≤d≤3.13). Furthermore, male young athletes were significantly taller and heavier compared to their female counterparts (p<0.001; 0.34≤d≤0.50). In terms of physical fitness, post-pubertal athletes showed better countermovement jump, drop jump, change-of-direction, and handgrip strength performances (p<0.001; 1.57≤d≤8.72) compared to pubertal athletes. Further, countermovement jump, drop jump, change-of-direction, and handgrip strength performances increased with increasing chronological age (p<0.05; 0.29≤d≤4.13). In addition, male athletes outperformed their female counterpart in the countermovement jump, drop jump, change-of-direction, and handgrip strength (p<0.05; 0.17≤d≤0.76). Significant age by sex interactions indicate that sex-specific differences were even more pronounced with increasing age. Conclusively, body height, body mass, and physical fitness increased with increasing maturational status and chronological age. Sex-specific differences appear to be larger as youth grow older. Practitioners can use the percentile values as approximate benchmarks for talent identification and development.

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Role of physique and physical fitness in the balance of Korean national snowboard athletes.

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Role of physique and physical fitness in the balance of Korean national snowboard athletes.

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