Upper extremity skeletal muscle mass: potential of measurement with single frequency bioimpedance analysis

Relation Between Respiratory Muscle Strength and Skeletal Muscle Mass and Hand Grip Strength in the Healthy Elderly

Objective

To evaluate sarcopenic indices in relation to respiratory muscle strength (RMS) in elderly people.

Methods

This study included 65 volunteers over the age of 60 (30 men and 35 women). The skeletal muscle mass index (SMI) was measured using bioimpedance analysis. Limb muscle function was assessed by handgrip strength (HGS), the Short Physical Performance Battery (SPPB), and gait speed. RMS was addressed by maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP) using a spirometer. The relationships between RMS and other sarcopenic indices were investigated using the Pearson correlation coefficients and multiple regression analysis adjusted for age, HGS, and SPPB.

Results

Both MIP and MEP were positively correlated with SMI (r=0.451 and r=0.388, respectively, p<0.05 in both). HGS showed a significant correlation with both MIP and MEP (r=0.560, p<0.01 and r=0.393, p<0.05, respectively). There was no significant correlation between gait speed and either MIP or MEP. The SPPB was positively correlated with MEP (r=0.436, p<0.05). In the multiple regression analysis, MIP was significantly associated with HGS and SMI (p<0.001 and p<0.05, respectively), while MEP was related only with HGS (p<0.05).

Conclusion

This study suggests that respiratory muscles, especially inspiratory muscles, are significantly related to limb muscle strength and skeletal muscle mass. The clinical significance of MIP and MEP should be further investigated with prospective studies.

Muscle development in healthy children evaluated by bioelectrical impedance analysis

OBJECTIVES

This study aimed to use bioelectrical impedance analysis (BIA) to generate a new muscle density index (MDI), the MDI_BIA, to evaluate muscle development, and to demonstrate the changes that occur in the BIA-based muscle cross-sectional area index (MCAI_BIA) that accompany growth. We also sought to determine the traceability of chronological changes in the MDI_BIA and MCAI_BIA.

METHODS

Healthy children (n=112) aged 8.68±3.16years (0.33-14.00years) underwent bioelectrical impedance (BI) measurements of their upper arms, thighs, and lower legs. The MDI_BIA and MCAI_BIA were calculated, and cross-sectional investigations were conducted into the changes in these indices that accompanied growth. Data collected after 1.10±0.08years from 45 participants determined the traceability of the chronological changes in the MDI_BIA and MCAI_BIA.

RESULTS

The MDI_BIA and MCAI_BIA were significantly positively correlated with age and height at all locations (P<0.01). The relationships between the locations and the MDI_BIA and MCAI_BIA differed, indicating that these indices evaluated the muscles from different perspectives. Except for the upper arm MDI_BIA, both indices at all locations regardless of age, showed significant chronological increases after an average period of 1.10years.

CONCLUSIONS

The MDI_BIA and MCAI_BIA were significantly correlated with age and height in healthy children, and they showed significant chronological increases. Hence, these indices could be used to represent muscle development and muscle mass increases. BIA is non-invasive, convenient, and economical and it may be useful in evaluating muscle development and muscle cross-sectional areas in children.

Development and evaluation of a multi-frequency bioelectrical impedance analysis analyzer for estimating acupoint composition

The purpose of this study was to suggest a new method of estimating acupoint compositions by using a multi-frequency bioelectrical impedance analysis (MF-BIA) method at 5 kHz, 50 kHz and 200 kHz within 2 cm of acupoints divided into local segments. To verify the system developed, we confirmed the stable occurrence of a constant current at every frequency, regardless of the impedance connected to the electrodes. Moreover, we found left and right distal bicep brachii aponeurosis to be identical by using ultrasound imaging, and we analyzed the repeatability of the findings by making 10 consecutive sets of measurements (p > 0.05). To evaluate the practical use of the acupoint composition, we used the MF-BIA analyzer to measure the left and right LU3, LU4, and LU9 at the lung meridian. We confirmed that the potentials generated were equal to the changes in the cell membrane function, which were caused by the applied frequency (p < 0.01). We also verified that the MF-BIA analyzer measurements corresponded to the acupoint components by comparing the left and right potentials generated (p > 0.05). Hence, we conclude that the MF-BIA analyzer can be used to estimate the acupoint composition based on the acupoint state.

Modeling upper and lower limb muscle volume by bioelectrical impedance analysis

Most studies employing bioelectrical impedance analysis (BIA) for estimating appendicular skeletal muscle mass using descriptive BIA models rely on statistical rather than biophysical principles. The aim of the present study was to evaluate the feasibility of estimating arm and leg muscle volume (MV) based on multiple bioimpedance measurements and using a recently proposed mathematical model and to compare this technique to conventional segmental BIA at high and low frequencies. MV of the arm and leg, respectively, was determined in 15 young, healthy, active men [age 22 ± 2 (SD) yr, total body fat 15.6 ± 5.1%] by magnetic resonance imaging (MRI) and BIA using a conventional and new bioimpedance model. MRI-determined MV for leg and arm was 6,268 ± 1,099 and 1,173 ± 172 cm3, respectively. Estimated MV by the new BIA model [leg: 6,294 ± 1,155 cm3 (50 kHz), 6,278 ± 1,103 cm3 (500 kHz); arm: 1,216 ± 172 cm3 (50 kHz), 1,155 ± 157 cm3 (500 kHz)] was not statistically different from MRI-determined MV (leg: P= 0.958; arm: P= 0.188). The new BIA model was superior to conventional BIA and performed best at 500 kHz for estimating leg MV as indicated by the lower relative total error [new: 3.6% (500 kHz), 5.2% (50 kHz); conventional: 7.6% (500 kHz) and 8.3% (50 kHz)]. In contrast, the new BIA model, both at 50 and 500 kHz, did not improve the accuracy for estimating arm MV [new: 10.8% (500 kHz), 10.6% (50 kHz); conventional: 11.8% (500 kHz), 11.4% (50 kHz)]. It was concluded that modeling of multiple BIA measurements has advantages for the determination of lower limb muscle volume in healthy, active adult men.

Laboratory and field measurements of body composition

Objective

This background paper was prepared in response to a request to review the concepts related to measurement of body composition, to discuss laboratory and field methods of assessing body composition and to discuss the practical applications of the methods – how they might be used singly or in combination to provide data for a selected population.

Design

The common laboratory and field methods are described and discussed, with particular attention to the assumptions involved and the applicability of the methods to the different population groups. Most measurements of body composition are made in the field, at the bedside or clinic as opposed to in the laboratory. The laboratory methods have a role to play in their own right, in research into new concepts, models and methods. However, they are particularly important in establishing the accuracy of the field methods.

Setting

Field, bedside and laboratory studies.

Subjects

Children, adults, the elderly, ethnic groups.

Results

Laboratory estimates of body compositions are best performed by multi-component methods or by 2-component methods adjusted for to the populations under investigation. There is a scarcity of data for most of the populations in the world.

Conclusions

Energy requirements based on body weight are an approximation since they do not take into account differences in body composition, which will better determine the true requirements. The measurement of body composition occurs in many branches of biology and medicine. It is used in the assessment of nutritional and growth status and in disease states and their treatment. Energy stores, skeletal muscle and protein content can be determined and changes monitored. In human energetics, body composition is widely used for the standardisation of other variables, such as basal metabolic rate (BMR), in the assessments of ethnic and environmental differences and of variability and adaptation to different levels of nutrition. Choosing a method is very problematic. Users want simple, inexpensive, rapid, safe accurate methods to measure body composition but speed and simplicity come at the expense of accuracy. Recommendations are made for age, sex, and in some cases, fatness and ethnic specific methods.

Estimation of maximal oxygen uptake by bioelectrical impedance analysis

Previous non-exercise models for the prediction of maximal oxygen uptake VO(2max) have failed to accurately discriminate cardiorespiratory fitness within large cohorts. The aim of the present study was to evaluate the feasibility of a completely indirect method for predicting VO(2max) that was based on bioelectrical impedance analysis (BIA) in 66 young, healthy fit men and women. Multiple, stepwise regression analysis was used to determine the usefulness of BIA and additional covariates to estimate VO(2max) (ml min(-1)). BIA was highly correlated to VO(2max) (r = 0.914; P < 0.001) and entered the regression equation first. The inclusion of gender and a physical activity rating further improved the model which accounted for 88% of the variance in VO(2max) and resulted in a relative standard error of the estimate (SEE) of 7.2%. Substantial agreement between the methods was confirmed by the fact that nearly all the differences were within +/-2 SD. Furthermore, in contrast to previously published non-exercise models, no trend of a reduction in prediction accuracy with increasing VO(2max) values was apparent. It was concluded that a non-exercise model based on BIA might be a rapid and useful technique to estimate VO(2max), when a direct test does not seem feasible. However, though the present results are useful to determine the viability of the method, further refinement of the BIA approach and its validation in a large, diverse population is needed before it can be applied to the clinical and epidemiological settings.

A comparison of three bioelectrical impedance analyses for predicting lean body mass in a population with a large difference in muscularity

This study tested the hypothesis that, as compared to whole-body bioelectrical impedance (BI) analysis, segmental BI analysis can estimate lean body mass (LBM) more accurately in a population with a large difference in muscularity. In addition to whole-body BI, which determines impedance (Z) between the wrist and ankle, two segmental BI analyses which determine the Z value of every body segment in each of (1) the arms, legs and trunk (distal BI) and (2) the upper arms, upper legs and trunk (proximal BI) were applied to a group of 125 male athletes and 75 non-athletes. The subjects were divided into validation and cross-validation groups. Simple and multiple regression analyses were applied to (length)(2)/Z (BI index) values for the whole-body and each body segment, to develop the prediction equations of LBM measured using air-displacement plethysmography. In the validation group, the SE of estimation was similar in the whole-body (3.4 kg, 5.4%), distal (3.4 kg, 5.5%) and proximal BI (3.3 kg, 5.2%) analyses. However, the whole-body and distal BI analyses produced systematical errors in the estimates of LBM. Moreover, the residuals in the two methods significantly (P < 0.05) correlated with the ratios of BI indices of the upper arms and upper legs to those of the arms and legs, respectively, calculated as variables approximating the relative development of lean tissues at the proximal area of limbs. On the other hand, the proximal BI analysis was validated and cross-validated. Thus, the accuracy of estimating LBM was similar in the whole-body and the two segmental BI analyses. However, the prediction equations derived from the use of the whole-body BI index and a combination of the arms, legs and trunk BI indices produced a systematical error relating to the difference between the limb segments in lean tissue development.

Comparison of bioelectrical impedance analysis and dual-energy X-ray absorptiometry for the assessment of appendicular body composition in anorexic women

OBJECTIVE

To establish the accuracy of bioelectrical impedance analysis (BIA) for the assessment of appendicular body composition in anorexic women.

DESIGN

Cross-sectional study.

SETTING

Outpatient University Clinic.

SUBJECTS

A total of 39 anorexic and 25 control women with a mean (s.d.) age of 21 (3) y.

METHODS

Total, arm and leg fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry and predicted from total and segmental BIA at 50 kHz. The predictor variable was the resistance index (Rl), that is, the ratio of height (2) to body resistance for the whole body and the ratio of length(2)/limb resistance for the arm and leg.

RESULTS

Predictive equations developed on controls overestimated total, arm and leg FFM in anorexics (P<0.0001). Population-specific equations gave a satisfactory estimate of total and appendicular FFM in anorexics (P=NS) but had higher percent root mean square errors (RMSEs%) as compared to those developed on controls (8% vs 5% for whole body, 12% vs 10% for arm and 10% vs 8% for leg). The accuracy of the estimate of total and leg FFM in anorexics was improved by adding body weight (Wt) as a predictor with Rl (RMSE%=5% vs 8% and 7% vs 10%, respectively). However, the same accuracy was obtained using Wt alone, suggesting that in anorexics, BIA at 50 kHz is not superior to Wt for assessing total and leg FFM.

CONCLUSION

BIA shows some potential for the assessment of appendicular body composition in anorexic women. However, Wt is preferable to BIA at 50 kHz on practical grounds. Further studies should consider whether frequencies >50 kHz give better estimates of appendicular composition in anorexics as compared to Wt.

SPONSORSHIP

University of Napoli.

Detection of segmental internal fat by bioelectrical impedance analysis in a biological phantom

OBJECTIVE

Quantification of internal adipose tissue such as visceral adipose tissue currently relies on expensive, cross-sectional imaging modalities. The purpose of this study was to test the hypothesis that surface impedance, determined by bioimpedance analysis, might be used to predict regional internal fat content change in a phantom model.

METHODS

Fresh hollowed-out cucumbers were used as cylindrical biological phantoms to test this hypothesis. After removal of the seeds, the cucumbers were filled with normal saline, mixture of saline and corn oil, or porcine adipose tissue bathed in saline. Surface resistance and reactance were measured with a bioimpedance analyzer accurate to 0.1 Omega (Quantum 10X, RJL Systems), and impedance was calculated. A linear regression model was used to interpret the association between composition and impedance.

RESULTS

Surface impedance varied linearly with changes in the relative internal corn oil portions (r- = 0.98). A similar relation was noted with porcine adipose tissue bathed in saline (r(2) = 0.95) regardless of the specific position of adipose tissue within the cucumber.

CONCLUSION

Surface impedance measured by bioimpedance analysis can detect variations in fat content in the interior of a cylindrical phantom.

Assessment by bioimpedance of forearm cell mass: a new approach to calibration

OBJECTIVE

Changes in skeletal muscle mass are involved in several important clinical disorders including sarcopenia and obesity. Unlike body fat, skeletal muscle is difficult to quantify in vivo, particularly without highly specialized equipment. The present study had a two-fold aim: to develop a regional (40)K counter for non-invasively estimating cell mass in the arm, mainly skeletal muscle cell mass, without radiation exposure; and to test the hypothesis that cell mass in the arm is highly correlated with electrical impedance after adjusting for the arm's length.

METHODS

Forearm cell mass was estimated using a rectangular lead-shielded (40)K counter with 4-NaI crystals; impedance of the arm was measured at multiple frequencies using a segmental bioimpedance analysis (BIA) system. The system's within- and between-day coefficient of variation (CV) for (40)K-derived elemental potassium averaged 1.8+/-1.3 and 5.8+/-1.2%, respectively. The corresponding BIA system's CVs were 1.0+/-0.4 and 2.1+/-1.0%, respectively.

SUBJECTS AND RESULTS

Participants in the study were 15 healthy adults (eight females, seven males; age 39+/-2.8 y, BMI 22.9+/-4.5 kg/m(2)). The right arm's K (5.2+/-1.7 g) was highly correlated with length-adjusted impedance (r(2)=0.81, 0.82, and 0.83 for 5, 50 and 300 kHz, respectively; all P<0.001); multiple regression analysis showed no additional improvement by adding age or sex to the prediction models.

CONCLUSION

These results demonstrate the feasibility of calibrating BIA-measured electrical properties of the arm against estimates of arm cell mass, mainly of skeletal muscle, obtained by regional (40)K counting. This simple and practical approach should facilitate the development of BIA-based regional cell mass prediction formulas

Techniques used in measuring human body composition

Remarkable progress is evident in the field of body composition research. This review summarizes main body composition research concepts, examines new component measurement methodologies and identifies potential areas for future research. As the dual-energy X-ray absorptiometry is now gaining acceptance, both clinically and in the research laboratory, as a useful body composition method, particular emphasis is placed on this important approach.