Bioelectrical impedance vector-analysis (BIVA) describes cell-mass, cell function and hydration status of an individual or a group. The goal of the present investigation was to provide bioelectrical impedance data for 525 male road cyclists (155 professionals, 79 elite, 59 elite-youth, and 232 amateurs) at the time of their optimal performance level. Data were plotted on the resistance-reactance (R-Xc) graph to characterize cyclists group vectors using BIVA. Compared to the general male population, the mean vector position of the road cyclists indicates a higher body cell mass (BCM) and phase angle (p<0.001). The vector position of the high-performance, compared to the amateur cyclists showed similar patterns with higher BCM and phase angles and higher reactance values for the high-performance athletes (p<0.001). The bio-impedance data were used to calculate the 50%, 75%, and 95% tolerance ellipses of each group of cyclists. The characteristic vector positions of the road cyclists indicate normal hydration and greater muscle mass and function of the high-performance cyclists compared to amateur cyclists and the normal population. The cyclists specific tolerance ellipses, particularly the high-performance cyclists might be used for classifying a cyclist according to the individual vector position and to define target vector regions for lower level cyclists.
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http://dx.doi.org/10.1080/02640414.2018.1470597 | DOI Listing |
Cent Eur J Public Health
December 2024
Department of Public Health and Hygiene, Faculty of Medicine, Pavol Jozef Safarik University in Kosice, Kosice, Slovak Republic.
Objective: Childhood overweight and obesity has been a major global problem for a long time, with a steadily increasing prevalence of obesity and a growing number of cases of serious health complications associated with childhood obesity. The main objective of the study is to assess the prevalence of overweight and obesity in boys and girls before the COVID-19 pandemic in the Czech Republic.
Methods: Body height, weight, BMI, and body composition (fat free mass, skeletal muscle mass, body fat, visceral fat area) were assessed in a cohort of 4,475 subjects (2,180 boys and 2,295 girls) aged 6-15 years.
Br J Hosp Med (Lond)
December 2024
Department of Clinical Nutrition, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China.
This study expanded the existing literature on obesity and distortion of body image by examining subjective and objective body type among young medical workers, specifically investigating whether fat percentage independently influences body type cognitive bias. We recruited 264 participants (41.29% male, mean age 26.
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January 2025
Department of Clinical Nutrition, Zhongda Hospital, Southeast University School of Medicine, Nanjing, Jiangsu, China.
The purpose of this analysis was to investigate the associations between phase angle (PhA), body mass index (BMI) and insulin resistance (IR) in patients with type 2 diabetes mellitus (T2DM). The retrospective cross-sectional study included 200 T2DM patients treated during 2018 to 2019 in Zhongda Hospital Southeast University. PhA and other body composition indicators were measured by bioelectrical impedance analysis (BIA).
View Article and Find Full Text PDFFront Med (Lausanne)
January 2025
Instituto de Medicina Fisica e Reabilitacao, IMREA, Hospital das Clínicas HCFMUSP, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil.
Background: Knee osteoarthritis (KOA) is the most common form of arthritis in adults and a leading cause of years lived with disability, representing a significant burden on healthcare worldwide.
Objective: Describe the structure and educational elements of the Knee-SCHOOL, a brief patient-centered multidisciplinary educational program for patients with KOA.
Design: Observational prospective study.
NPJ Digit Med
January 2025
Josué de Castro Institute of Nutrition, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
There is a growing need to evaluate the agreement between the field methods and integrate artificial intelligence (AI) using two-dimensional (2D) photos for enhanced real-world analysis. This study evaluated the agreement between AI-2D photos and the clinical reference method, dual-energy X-ray absorptiometry (DXA) to estimate the body fat percentage (BFP). Other methods were also investigated, including skinfolds, A-mode ultrasound, and bioelectrical impedance analysis (BIA).
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