This study investigated the relationship of body fat and fitness measures in schoolchild handball players. Twenty-eight young male handball players from handball first youth league volunteered for the present investigation (age: 10.9 ± 0.72 years; body mass: 54.8 ± 22.9 kg; height: 1.48 ± 0.10 m; body fat: 27.6 ± 9.23%). Measures included the Yo-Yo Intermittent Recovery Test level 1 (Yo-Yo IR1), jumping ability [squat and counter-movement jumps (SJ, CMJ)], and sprint tests (10 m, 15 m). Anthropometry was assessed by body mass, body mass index (BMI), and fat percentage (%BF). The power of the upper limb was measured as the total distance thrown overhead using a 2 kg medicine ball. Intrarater reliability for all parameters showed a coefficient of variation (CV) below 10% and an intraclass correlation coefficient (ICC) above 0.75. All ICC were excellent (ICC ≥ 0.96). Reliability as shown by the CV differed between 1.0 (sprint 15 m) and 5.6 (sprint 10 m). With the exception of medicine ball throw, we found significant differences between non-obese and obese in all performance parameters. The differences ranged from η = 0.47 (sprint 10 m) to η = 0.09 (medicine ball throw). The two-step-linear regression analysis using the predictors body height and body weight (step 1) and body fat (step 2) showed a marked increase of explained variance by adding body fat. The largest r changes were calculated for sprint 10 m (0.54), CMJ (0.49), and sprint 15 m (0.42). The lowest influence of the predictors was observed for medicine ball throw (step 1: = 0.03, step 2: = 0.07). With the exception of sprint parameters (β-coefficient sprint 10 m: -0.74; β-coefficient sprint 20: -0.66), a decrease of %BF leads to a higher performance in all parameters. %BF in youth handball players should be an important concern for practitioners working in this team sport in contrast to the frequently used BMI. It seems sensible and appropriate to engage very young children in physical activities such as team handball in order to improve their physical fitness. Decrease in% body fat could be considered both as a training and nutritional target to enhance and optimize sport performance-related outcomes.
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http://dx.doi.org/10.3389/fphys.2020.580991 | DOI Listing |
Eur J Sport Sci
February 2025
Department of Sport and Health Sciences and Social Work, Oxford Brookes University, Oxford, UK.
Some technical limitations to using the eccentric mode to measure peak eccentric strength of the hamstrings (PTH) were raised. PTH also has limited validity to predict performance or injury risk factor. Therefore, our aim was to compare PTH and other isokinetic variables tested in the eccentric and passive modes.
View Article and Find Full Text PDFBMC Cardiovasc Disord
January 2025
Department of Pharmacology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Background: Atherosclerosis (AS) is a major contributor to vascular disorders and represents a significant risk to human health. Currently, first-line pharmacotherapies are associated with substantial side effects, and the development of atherosclerosis is closely linked to dietary factors. This study evaluated the effects of a dietary supplement, EsV3, on AS in apolipoprotein E (ApoE) model mice.
View Article and Find Full Text PDFEnviron Pollut
January 2025
Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA. Electronic address:
PNPLA3-I148M genotype is the strongest predictive single-nucleotide polymorphism for liver fat. We examine whether PNPLA3-I148M modifies associations between oxidative gaseous air pollutant exposure (O) with i) liver fat and ii) multi-omics profiles of miRNAs and metabolites linked to liver fat. Participants were 69 young adults (17-22 years) from the Meta-AIR cohort.
View Article and Find Full Text PDFIntroduction There are controversies about whether women with polycystic ovary syndrome (PCOS) show a disproportionately higher visceral adiposity, and its relevance to their higher cardiometabolic risks. We investigated in women of Asian Indian descent in Mauritius, a population inherently prone to abdominal obesity, whether those with PCOS will show a more adverse cardiometabolic risk profile that could be explained by abnormalities in fat distribution. Methods Young women newly diagnosed with PCOS (n=25) were compared with a reference control cohort (n =139) for the following measurements made after an overnight fast: body mass index (BMI), waist circumference (WC), body composition by dual-energy x-ray absorptiometry, blood pressure and blood assays for glycemic (glucose, HbA1c, insulin) and lipid (triglycerides, cholesterols) profiles.
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