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Comparisons between Bioelectrical Impedance Variables, Functional Tests and Blood Markers Based on BMI in Older Women and Their Association with Phase Angle.

Rafael Franco Soares OliveiraCésar LeãoAna Filipa SilvaFilipe Manuel ClementeCarlos Tadeu SantamarinhaHadi NobariJoão Paulo Brito
Published in: International journal of environmental research and public health (2022)
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/m 2 ); Group 2 (G2, BMI > 25-30 kg/m 2 ); Group 3 (G3, BMI > 30-35 kg/m 2 ); Group 4 (G4, BMI > 35 kg/m 2 ). 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.
Keyphrases
  • body mass index
  • body composition
  • weight gain
  • resistance training
  • physical activity
  • bone mineral density
  • adipose tissue
  • magnetic resonance
  • magnetic resonance imaging
  • high resolution
  • fatty acid