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Despite BIA emerging as a clinical tool for assessing older adults, it remains unclear how to calculate whole-body impedance (Z), reactance (Xc), resistance (R), and phase angle (PhA) from segmental values using modern BIA devices that place electrodes on both sides of the body. This investigation aimed to compare both the whole-body and segmental device-generated phase angle (PhADG) with the phase angle calculated using summed Z, Xc, and R from the left, right, and combined sides of the body (PhACalc) and to compare bioelectric variables between sides of the body. A sample of 103 community-dwelling older adults was assessed using a 50 kHz direct segmental multifrequency BIA device. Whole-body PhACalc values were assessed for agreement with PhADG using 2.5th and 97.5th quantile nonparametric limits of agreement and Spearman's rho. Bioelectrical values between sides of the body were compared using Wilcoxon rank and Spearman's rho. A smaller mean difference was observed between PhADG and right PhACalc (−0.004°, p = 0.26) than between PhACalc on the left (0.107°, p = 0.01) and on the combined sides (0.107°, p < 0.001). The sum of Z, R, and PhACalc was significantly different (p < 0.01) between the left (559.66 ± 99.55 Ω, 556.80 ± 99.52 Ω, 5.51 ± 1.5°, respectively) and the right sides (554.60 ± 94.52 Ω, 552.02 ± 94.23 Ω, 5.41 ± 0.8°, respectively). Bilateral BIA values do not appear to be interchangeable when determining whole-body measurements. Present data suggest that using right-sided segmental values would be the most appropriate choice for calculating whole-body bioelectrical variables. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to establish a new threshold parameter called the physical working capacity at pain intensity threshold (PWCPIT) using a pain intensity scale and mathematical methods similar to those used to develop the physical working capacity at oxygen consumption threshold (PWCVO2) and physical working capacity at heart rate threshold (PWCHRT). The study had two objectives: (i) to examine the relationship between PWCPIT and traditional PWC measures and (ii) to explore the physiological mechanisms underlying the relationship between pain perception and capacity thresholds.Fourteen male volunteers (age 21 ± 2 years, height 176 ± 6 cm, weight 76 ± 9 kg, VO2peak 37.8 ± 7.8 ml/kg/min−1) underwent an incremental exhaustion test and four 8-min randomly ordered work bouts on different days at 70–100% peak power output (119–320 W) to establish their PWCPIT, PWCHRT and PWCVO2. One-way repeated-measures ANOVA with Bonferroni post hoc tests and a zero-order correlation matrix were used to analyze these thresholds.PWCPIT significantly correlated with PWCHRT (r = 0.88, P < 0.001), PWCVO2 (r = 0.84, P < 0.001), and gas exchange threshold (GET) (r = 0.7, P = 0.006).The model for estimating PWCHRT and PWCVO2 can be applied to determine the PWCPIT. By examining how PWCPIT aligns with, differs from, or complements existing PWC threshold measures, researchers may provide a more comprehensive understanding of the factors that govern endurance performance.Methods: This study aimed to establish a new threshold parameter called the physical working capacity at pain intensity threshold (PWCPIT) using a pain intensity scale and mathematical methods similar to those used to develop the physical working capacity at oxygen consumption threshold (PWCVO2) and physical working capacity at heart rate threshold (PWCHRT). The study had two objectives: (i) to examine the relationship between PWCPIT and traditional PWC measures and (ii) to explore the physiological mechanisms underlying the relationship between pain perception and capacity thresholds.Fourteen male volunteers (age 21 ± 2 years, height 176 ± 6 cm, weight 76 ± 9 kg, VO2peak 37.8 ± 7.8 ml/kg/min−1) underwent an incremental exhaustion test and four 8-min randomly ordered work bouts on different days at 70–100% peak power output (119–320 W) to establish their PWCPIT, PWCHRT and PWCVO2. One-way repeated-measures ANOVA with Bonferroni post hoc tests and a zero-order correlation matrix were used to analyze these thresholds.PWCPIT significantly correlated with PWCHRT (r = 0.88, P < 0.001), PWCVO2 (r = 0.84, P < 0.001), and gas exchange threshold (GET) (r = 0.7, P = 0.006).The model for estimating PWCHRT and PWCVO2 can be applied to determine the PWCPIT. By examining how PWCPIT aligns with, differs from, or complements existing PWC threshold measures, researchers may provide a more comprehensive understanding of the factors that govern endurance performance.Results: This study aimed to establish a new threshold parameter called the physical working capacity at pain intensity threshold (PWCPIT) using a pain intensity scale and mathematical methods similar to those used to develop the physical working capacity at oxygen consumption threshold (PWCVO2) and physical working capacity at heart rate threshold (PWCHRT). The study had two objectives: (i) to examine the relationship between PWCPIT and traditional PWC measures and (ii) to explore the physiological mechanisms underlying the relationship between pain perception and capacity thresholds.Fourteen male volunteers (age 21 ± 2 years, height 176 ± 6 cm, weight 76 ± 9 kg, VO2peak 37.8 ± 7.8 ml/kg/min−1) underwent an incremental exhaustion test and four 8-min randomly ordered work bouts on different days at 70–100% peak power output (119–320 W) to establish their PWCPIT, PWCHRT and PWCVO2. One-way repeated-measures ANOVA with Bonferroni post hoc tests and a zero-order correlation matrix were used to analyze these thresholds.PWCPIT significantly correlated with PWCHRT (r = 0.88, P < 0.001), PWCVO2 (r = 0.84, P < 0.001), and gas exchange threshold (GET) (r = 0.7, P = 0.006).The model for estimating PWCHRT and PWCVO2 can be applied to determine the PWCPIT. By examining how PWCPIT aligns with, differs from, or complements existing PWC threshold measures, researchers may provide a more comprehensive understanding of the factors that govern endurance performance.Conclusion: This study aimed to establish a new threshold parameter called the physical working capacity at pain intensity threshold (PWCPIT) using a pain intensity scale and mathematical methods similar to those used to develop the physical working capacity at oxygen consumption threshold (PWCVO2) and physical working capacity at heart rate threshold (PWCHRT). The study had two objectives: (i) to examine the relationship between PWCPIT and traditional PWC measures and (ii) to explore the physiological mechanisms underlying the relationship between pain perception and capacity thresholds.Fourteen male volunteers (age 21 ± 2 years, height 176 ± 6 cm, weight 76 ± 9 kg, VO2peak 37.8 ± 7.8 ml/kg/min−1) underwent an incremental exhaustion test and four 8-min randomly ordered work bouts on different days at 70–100% peak power output (119–320 W) to establish their PWCPIT, PWCHRT and PWCVO2. One-way repeated-measures ANOVA with Bonferroni post hoc tests and a zero-order correlation matrix were used to analyze these thresholds.PWCPIT significantly correlated with PWCHRT (r = 0.88, P < 0.001), PWCVO2 (r = 0.84, P < 0.001), and gas exchange threshold (GET) (r = 0.7, P = 0.006).The model for estimating PWCHRT and PWCVO2 can be applied to determine the PWCPIT. By examining how PWCPIT aligns with, differs from, or complements existing PWC threshold measures, researchers may provide a more comprehensive understanding of the factors that govern endurance performance. [ABSTRACT FROM AUTHOR]

Background: Older adults experience a significant decline in muscle integrity and function with aging. Early detection of decreased muscle quality can pave the way for interventions to mitigate the progression of age-related physical declines. Phase angle (PhA) and impedance ratio (IR) are measures of muscle integrity, which can be assessed quickly via bioelectrical impedance analysis (BIA) and may be indicative of physical function., Objective: This study aimed to characterize the relationships among handgrip strength (HGS), sit-to-stand (STS), BTrackS balance scores, fear of falling (evaluated using the Short Falls Efficacy Scale-International [Short FES-I]), and IR among community-dwelling older adult women classified as having a low or high PhA., Methods: A cross-sectional analysis was conducted with 85 older women (mean age 75.0, SD 7.2 years; mean weight 71.0, SD 15.0 kg; mean height 162.6, SD 6.1 cm). To examine the influence of PhA on performance measures, participants were divided into 2 PhA groups: high (>4.1°; n=56) and low (≤4.1°; n=29). Data were nonnormative; hence, the Mann-Whitney U test was used to evaluate between-group differences, and Kendall τ coefficients were used to determine the partial correlations., Results: The low PhA group had a significantly higher IR (mean 0.85, SD 0.03) than the high PhA group (mean 0.81, SD 0.03; r=.92; P<.001). The high PhA group had superior HGS (mean 21.4, SD 6.2 kg; P=.007; r=0.36), BTrackS balance scores (mean 26.6, SD 9.5 cm; P=.03; r=0.30), and STS scores (mean 16.0, SD 5.5; P<.001; r=0.49) than the low PhA group (mean HGS 17.6, SD 4.7 kg; mean BTrackS balance score 37.1, SD 21.1 cm; mean STS score 10.7, SD 6.2). Both PhA and IR were significantly correlated with HGS and BTrackS balance, STS, and Short FES-I scores (P<.05). However, on adjusting for the whole sample's age, only PhA was strongly correlated with HGS (τb=0.75; P=.003) and STS scores (τb=0.76; P=.002). Short FES-I scores were moderately correlated with IR (τb=0.46; P=.07) after controlling for age. No significant between-group differences were observed for height, weight, or BMI., Conclusions: PhA and IR are associated with physical function and the fear of falling in older women. However, only PhA was significantly associated with physical function (HGS and STS) independent of age. Conversely, only IR was significantly associated with the fear of falling. Diminished physical function and increased IR appear to be characteristics of older women with a PhA of ≤4.1°. These findings suggest that PhA and IR measured through BIA together may serve as a valuable tool for early identification of older women at the risk of functional decline and a heightened fear of falling., (© Danielle A Sterner, Jeffrey R Stout, Kworweinski Lafontant, Joon-Hyuk Park, David H Fukuda, Ladda Thiamwong. Originally published in JMIR Aging (https://aging.jmir.org).)