The biophysical response of the human body to electric current is widely appreciated as a barometer of fluid distribution and cell function. From distinct raw bioelectrical impedance (BIA) variables assessed in the field of body composition, phase angle (PhA) has been repeatedly indicated as a functional marker of the cell's health and mass. Although resistance training (RT) programs have demonstrated to be effective to improve PhA, with varying degrees of change depending on other raw BIA variables, there is still limited research explaining the biological mechanisms behind these changes. Here, we aim to provide the rationale for the responsiveness of PhA determinants to RT, as well as to summarize all available evidence addressing the effect of varied RT programs on PhA of different age groups. Available data led us to conclude that RT modulates the cell volume by increasing the levels of intracellular glycogen and water, thus triggering structural and functional changes in different cell organelles. These alterations lead, respectively, to shifts in the resistive path of the electric current (resistance, R) and capacitive properties of the human body (reactance, Xc), which ultimately impact PhA, considering that it is the angular transformation of the ratio between Xc and R. Evidence drawn from experimental research suggests that RT is highly effective for enhancing PhA, especially when adopting high-intensity, volume, and duration RT programs combining other types of exercise. Still, additional research exploring the effects of RT on whole-body and regional BIA variables of alternative population groups is recommended for further knowledge development. 

https://link.springer.com/content/pdf/10.1007/s11154-023-09791-8.pdf

Phase angle, muscle tissue, and resistance training

The study aimed to explore the relationships of skeletal muscle mass with disease severity in MAFLD patients with different methods. Consecutive subjects undergoing bioelectrical impedance analysis were included. The steatosis grade and liver fibrosis were evaluated by magnetic resonance imaging-derived proton density fat fraction and two-dimensional shear wave elastography. The appendicular skeletal muscle mass (ASM) was adjusted by height2 (ASM/H2), weight (ASM/W) and body mass index (ASM/BMI). Overall, 2223 subjects (50.5%, MAFLD; 46.9%, male) were included, and the mean age was 37.4 ± 10.6 years. In multivariate logistic regression analysis, the subjects with the lowest quartile (Q1) of ASM/W or ASM/BMI had higher risk ratios for MAFLD [ORs (95% CI) in male: 2.57 (1.35-4.89), 2.11(1.22-3.64); in female: 4.85 (2.33-10.01), 4.81 (2.52-9.16), all P <0.05, all for Q1 vs Q4]. The MAFLD patients with lower quartiles of ASM/W had the higher risk ORs for insulin resistance (IR), both in male and female [2.14 (1.16-3.97), 4.26 (1.29-14.02) for Q4 vs. Q1, both P<0.05]. While the significant ORs were not observed when ASM/H2 and ASM/BMI was used. There were significant dose-dependent associations between decreased ASM/W as well as ASM/BMI and moderate-severe steatosis [2.85(1.54-5.29), 1.90(1.09-3.31), both P <0.05] in male MAFLD patients. There was no such association in male MAFLD patients with ASM/H2 or in female MAFLD with three of methods. In conclusion, ASM/W is superior to ASM/H2 and ASM/BMI in predicting the degree of MAFLD. A lower ASM/W is associated with IR and moderate-severe steatosis in non-elderly male MAFLD.

Impact of skeletal muscle mass evaluating methods on severity of metabolic associated fatty liver disease in nonelderly adults.

There are several equations based on bioelectrical impedance analysis (BIA) to estimate with high precision appendicular skeletal muscle mass (ASM). However, most of the external validation studies have reported that these equations are inaccurate or biased when applied to different populations. Furthermore, none of the published studies has derived correction factors (CFs) in samples of community-dwelling older adults, and none of the published studies have assessed the influence of the dual-energy X-ray absorptiometry (DXA) model on the validation process. This study assessed the agreement between six BIA equations and DXA to estimate ASM in non-Caucasian older adults considering the DXA model and proposed a CF for three of them. This analysis included 547 non-institutionalized subjects over 60 years old from the northwest of Mexico who were physically independent and without cognitive impairment: 192 subjects were measured using DXA Hologic, while 355 were measured by DXA Lunar. The agreement between each of the equations and DXA was tested considering the DXA model used as a reference method for the design of each equation, using the Bland and Altman procedure, a paired t test, and simple linear regression as objective tests. This process was supported by the differences reported in the literature and confirmed in a subsample of 70 subjects measured with both models. Only six published BIA equations were included. The results showed that four equations overestimated ASMDXA, and two underestimated it (p < 0.001, 95% CI for Kim's equation:−5.86-−5.45, Toselli's:−0.51-−0.15, Kyle's: 1.43–1.84, Rangel-Peniche's: 0.32–0.74, Sergi's: 0.83–1.23, and Yoshida's: 4.16–4.63 kg). However, Toselli's, Kyle's and Rangel-Peniche's equations were the only ones that complied with having a homogeneous bias. This finding allowed the derivation of CFs, which consisted of subtracting or adding the mean of the differences from the original equation. After estimating ASM applying the respective CF, the new ASM estimations showed no significant bias and its distribution remained homogeneously distributed. Therefore, agreement with DXA in the sample of non-Caucasian was achieved. Adding valid CFs to some BIA equations allowed to reduce the bias of some equations, making them valid to estimate the mean values of ASM at group level.

External validation of BIA equations to estimate appendicular skeletal muscle mass in older adults: Importance of the bias analysis and derivation of correction factors to achieve agreement

Guadalupe Figueroa-Pesqueira

Papers

External validation of BIA equations to estimate appendicular skeletal muscle mass in older adults: Importance of the bias analysis and derivation of correction factors to achieve agreement