ArticleInternational journal of environmental research and public health2022
Comparisons between Bioelectrical Impedance Variables, Functional Tests and Blood Markers Based on BMI in Older Women and Their Association with Phase Angle.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Postprandial exercise attenuates glucose and insulin and is associated with age, cognitive function, and extracellular/intracellular body water.Physiological reports · 2025Article
- A predictive model for body water and fluid balance using 3D smartphone anthropometry.Frontiers in physiology · 2025Article
- Phase Angle and Impedance Ratio as Indicators of Physical Function and Fear of Falling in Older Adult Women: Cross-Sectional Analysis.JMIR aging · 2024Article
- Article
- Role of phase angle in older adults with focus on the geriatric syndromes sarcopenia and frailty.Reviews in endocrine & metabolic disorders · 2023Review
- Association between the Phase Angle and the Severity of Horizontal Gaze Disorder in Patients with Idiopathic Dropped Head Syndrome: A Cross-Sectional Study.Medicina (Kaunas, Lithuania) · 2023Article
- Relationship among Body Composition, Adipocytokines, and Irisin on Exercise Capacity and Quality of Life in COPD: A Pilot Study.Biomolecules · 2022Article
- Phase Angle as a Predictor for Physical Function in Institutionalized Independent Older Adults.International journal of environmental research and public health · 2022Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the present study was to compare electrical bioimpedance variables, blood markers and functional tests based on Body Mass Index (BMI) in older women. Associations between Phase Angle (PhA) with functional tests and blood markers were also analyzed. A total of 46 independent elderly people participated in the study, and they were divided into four groups according to BMI values: Group 1 (G1, BMI < 25 kg/m2); Group 2 (G2, BMI > 25−30 kg/m2); Group 3 (G3, BMI > 30−35 kg/m2); Group 4 (G4, BMI > 35 kg/m2). In addition to the weight and height used to calculate the BMI, the following body composition variables were collected: fat mass (FM), fat-free mass, intracellular water (ICW), extracellular water (ECW), total body water (TBW) and PhA (50 kHz) through InBody S10 equipment. Functional capacity was assessed using the Fullerton battery of tests: arm-curl; chair-stand; 6 min walking test (6MWT); time up-and-go test (TUG); standing on one leg (SOOL) and take 10 foot-lines (10FL). The main results showed differences between groups in the tests: 6MWT, SOOL and 10FL between G1 vs. G3 and G2 vs. G3 (p < 0.05); ACT, AIC and AEC between G1 vs. G4 (p < 0.05); FM among all groups (p < 0.05). Negative correlations were found between PhA and the agility test in G1 (r = −0.848; p = 0.008) and G4 (r = −0.909; p = 0.005); PhA and chair-stand in G3 (r = 0.527; p = 0.044); PhA and forearm flexion in G3 (r = 0.641; p = 0.010) and G4 (r = 0.943; p = 0.001); PhA and 6MWT in G4 (r = 0.771; p = 0.042). This study found that there is a clear trend towards better functional capacities with better parameters of body composition. Although there were no differences between groups in PhA, associations were found between different functional tests with PhA, which reveals the importance of this variable as a marker of health status.
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