Validation of a bioelectrical impedance analysis equation to predict appendicular skeletal muscle mass (ASMM)

doi:10.1016/S0261-5614(03)00048-7

Clinical Nutrition

Volume 22, Issue 6, December 2003, Pages 537-543

https://doi.org/10.1016/S0261-5614(03)00048-7 Get rights and content

Abstract

Rationale: Appendicular skeletal muscle mass (ASMM) is useful in the evaluation of nutritional status because it reflects the body muscle protein mass. The purpose of this study was to validate, against dual-energy X-ray absorptiometry (DEXA), a BIA equation to predict ASMM to be used in volunteers and patients.

Method: Healthy men (n = 246 men, BMI 25.3±2.9 kg/m²) and women (n =198, 24.1±3.6 kg/m²), and heart, lung and liver transplant patients (213 men, BMI of 24.6±4.4 kg/m²; 113 women, BMI 23.0±5.2 kg/m²) were measured by BIA (Xitron Technologies) and DEXA (Hologic QDR 4500). A BIA equation to predict ASMM (kg) that included height²/resistance, weight, gender, age and reactance, was developed by means of multiple regressions.

Results:	Men		Women
ASMM (kg)	DEXA	BIA	DEXA	BIA
Volunteers	25.8±3.6	25.7±3.4	17.3±2.5	17.2±2.4
Patients	22.1±2.8	22.6±3.5^*	15.2±2.8	15.2±3.0
Mean±SD, paired t-test between BIA and DXA ^* P<0.01

Mean difference (Bland-Altman) for volunteers was 0.1±1.1 kg, r =0.95, SEE 1.12 kg and for patients −0.4±1.5 kg, r =0.91, SEE 1.5 kg.Best fitted multiple regression equation was −4.211 + (0.267×height2 / resistance) + (0.095×weight)+(1.909×sex (men = 1, women = 0)) + (−0.012×age) + (0.058×reactance).

Conclusions: BIA permits the prediction of ASMM in healthy volunteers and patients between 22 and 94 years of age. A slightly larger, though clinically not significant, error was noted in patients.

Introduction

Aging is associated with a gradual loss of skeletal muscle mass or sarcopenia. Wasting diseases and many health related conditions also result in decreases in skeletal muscle mass (1). Appendicular (or limb) skeletal muscle mass (ASMM) accounts for>75% of total skeletal muscle (2) and is the primary portion of skeletal muscle involved in ambulation and physical activity. In the elderly, skeletal muscle mass loss may be masked by weight stability resulting from a corresponding increase in total body fat mass (1). Cross-sectional data suggest that the loss of ASMM is greater with aging than the loss on non-skeletal muscle mass (3). Thus, the evaluation of ASMM can contribute important information to the assessment of nutritional status because it reflects the body protein mass. A major impediment to determining ASMM is the lack of suitable, easy and non-invasive methods for estimating ASMM.

Earlier studies support the validity of DXA estimates of ASMM 4., 5.. However, DXA is not a ‘portable’ method and measurement cost and technician skill limit its use in field studies. Bioelectrical impedance analysis (BIA) has been used to determine the fat-free mass (6). Recent studies indicate good correlation between limb electrical resistance, measured at 50 kHz, and ASMM by DXA 7., 8.. This observation suggests that limb skeletal muscle can be estimated from BIA-measured resistance.

Janssen et al. (9) recently developed a BIA equation, validated against magnetic resonance imaging (MRI) that provides valid estimates of total skeletal mass in healthy adults varying in age and adiposity. Lee et al. (10) developed anthropometric prediction models to estimate total body skeletal muscle mass, using skinfold and limb circumferences. Baumgartner et al. (11) estimated ASMM from anthropometric parameters, including hip circumference and grip strength in elderly subjects. Pietrobelli et al. (8) found BIA to be valid for estimating arm and leg skeletal muscle mass. Estimation of regional muscle mass by segmental BIA measurements, compared to MRI 12., 13., 14., requires further validation before it can be applied in clinical settings.

Currently there are no BIA-determined prediction equations to estimate ASMM. The purpose of this study was to validate, against dual-energy X-ray absorptiometry (DXA), a BIA equation to predict ASMM to be used in volunteers and patients.

Section snippets

Volunteers

Four hundred and forty-four healthy ambulatory Caucasians (246 men and 198 women) aged 22 –94 years (Table 1) were included in this study. Subjects were non-randomly recruited through advertisement in local newspapers and invitations to participate in the study sent to members of elderly leisure clubs. Although subjects were non-randomly selected, statistical analysis revealed no difference in height, weight and body mass index (BMI) between subjects in this study and age-matched healthy men

Results

A total of 444 healthy volunteers between ages 22 and 94 years and 326 patients were included. Table 1 shows their anthropometric and bioelectrical impedance analysis characteristics. The weight was significantly higher in volunteers than patients. The resistance and height²/resistance were significantly higher and the reactance significantly lower in patients than volunteers. The reactance was significantly lower in volunteers and patients>55 year than in those < 55 years.

The prediction

Discussion

The aim of the study was to develop and cross-validate a prediction equation for estimating ASMM from BIA measurements. Our findings indicate that DXA-measured ASMM was strongly correlated to the BIA-derived resistance, normalized for height, (ht²/R) and that the BIA method is a valid method for estimating ASMM in healthy volunteers and patients. The error (SEE) for predicting ASMM was 1.1 kg (5%) in volunteers and 1.5 kg (7.6%) in patients.

Resistance index (height²/R) had an r² value of 0.92 and

Conclusions

The study validated a BIA equation to predict ASMM. BIA permits the prediction of ASMM in healthy volunteers between 22 and 94 years and patients between 18 and 70 years. A slightly larger, though clinically not significant, error was noted in patients.

Acknowledgements

We thank the Foundation Nutrition 2000Plus for its financial support.

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