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. 2021 Dec;12(6):2163-2173.
doi: 10.1002/jcsm.12825. Epub 2021 Oct 4.

Diagnosis of sarcopenia by evaluating skeletal muscle mass by adjusted bioimpedance analysis validated with dual-energy X-ray absorptiometry

Affiliations

Diagnosis of sarcopenia by evaluating skeletal muscle mass by adjusted bioimpedance analysis validated with dual-energy X-ray absorptiometry

Keith Yu-Kin Cheng et al. J Cachexia Sarcopenia Muscle. 2021 Dec.

Abstract

Background: This study aimed to adjust and cross-validate skeletal muscle mass measurements between bioimpedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) for the screening of sarcopenia in the community and to estimate the prevalence of sarcopenia in Hong Kong.

Methods: Screening of sarcopenia was provided to community-dwelling older adults. Appendicular skeletal muscle mass (ASM) was evaluated by BIA (InBody 120 or 720) and/or DXA. Handgrip strength and/or gait speed were assessed. Diagnosis of sarcopenia was based on the 2019 revised Asian Working Group for Sarcopenia cut-offs. Agreement analysis was performed to cross-validate ASM measurements by BIA and DXA. Multiple regression was used to explore contribution of measured parameters in predicting DXA ASM from BIA.

Results: A total of 1587 participants (age = 72 ± 12 years) were recruited; 1065 participants were screened by BIA (InBody 120) with 18 followed up by DXA, while the remaining 522 participants were assessed by the BIA (InBody 720) and DXA. The appendicular skeletal muscle mass index (ASMI) evaluated by BIA showed a mean difference of 2.89 ± 0.38 kg/m2 (InBody 120) and 2.97 ± 0.45 kg/m2 (InBody 720) against DXA gold standard. A significant overestimation of muscle mass was measured by BIA compared with DXA (P < 0.005). BIA data were adjusted using prediction equation and mean difference reduced to -0.02 ± 0.31 kg/m2 in cross-validation. Prevalence of sarcopenia in older adults ≥65 ranged from 39.4% (based on ASMI by DXA) to 40.8% (based on predicted DXA ASMI from BIA). Low ASMI by DXA was found in 68.5% of the older adults screened. The percentage of older adults exhibited low handgrip strength ranged from 31.3% to 56%, while 49% showed low gait speed.

Conclusions: Bioimpedance analysis was found to overestimate skeletal muscle mass compared with DXA. With adjustment equations, BIA can be used as a quick and reliable tool for screening sarcopenia in community and clinical settings with limited access to better options.

Keywords: Bioimpedance analysis (BIA); Diagnosis; Dual-energy X-ray absorptiometry (DXA); Sarcopenia; Skeletal muscle mass.

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Conflict of interest statement

None declared.

Figures

Figure 1
Figure 1
Definition of sarcopenia used in this study based on the Asian Working Group for Sarcopenia (AWGS) 2019 guidelines, where ‘sarcopenia’ is defined as ‘low appendicular skeletal muscle mass index (ASMI) with either low muscle strength or low physical performance’, while ‘severe sarcopenia’ is defined as ‘low ASMI with low muscle strength and low physical performance’. DXA, dual‐energy X‐ray absorptiometry.
Figure 2
Figure 2
Appendicular skeletal muscle mass index (ASMI, kg/m2) evaluated by (BIA) and dual‐energy X‐ray absorptiometry (DXA). Top and bottom lines indicate ±1.96 SD. (A) BIA (InBody 120) ASMI vs. age in Dataset120 (n = 1065). (B) BIA (InBody 720) ASMI vs. age in Dataset720 (n = 522). (C) DXA ASMI vs. age in Dataset120 (n = 18). (D) DXA ASMI vs. age in Dataset720 (n = 522). (E) Correlation between DXA and BIA ASMI in Dataset120 (r 2 = 0.867, n = 18, P < 0.05). (F) Correlation between DXA and BIA ASMI in Dataset720 (r 2 = 0.893, n = 522, P < 0.05).
Figure 3
Figure 3
Appendicular skeletal muscle mass (ASMI, kg/m2) as evaluated by dual‐energy X‐ray absorptiometry (DXA). Top and bottom lines on (C) and (D) indicate ±1.96 SD. (A) Flow chart showing the breakdown of different tests and number of subjects in each dataset. (B) ASMI vs. age coloured by gender (n = 540). (C) Male DXA ASMI vs. age (n = 299). (D) Female DXA ASMI vs. age (n = 241). BIA, bioimpedance analysis.
Figure 4
Figure 4
Handgrip strength measured by dynamometer in kilograms (kg) and gait speed by 6 m walk test measured in seconds (s) plotted against age separated by gender. Top and bottom lines indicate ±1.96 SD. (A) Female handgrip strength by age (n = 1160). (B) Male handgrip strength by age (n = 427). (C) Six metre walk time for female gait speed by age (n = 226). (D) Six metre walk time for male gait speed by age (n = 296).
Figure 5
Figure 5
Bland–Altman plot comparing appendicular skeletal muscle mass (ASM) and appendicular skeletal muscle mass index (ASMI) measured between bioimpedance analysis (BIA) and dual‐energy X‐ray absorptiometry (DXA) in Dataset120 (n = 18) and Dataset720 (n = 522). Top and bottom reference lines indicate 95% confidence interval. (A) ASM mean difference = 6.77 ± 1.24 kg, limits of agreement = 4.35, 9.20. (B) ASM mean difference = 8.25 ± 1.80 kg, limits of agreement = 4.73, 11.77. (C) ASMI mean difference = 2.89 ± 0.38 kg/m2, limits of agreement = 2.15, 3.63. (D) ASMI mean difference = 3.11 ± 0.45 kg/m2, limits of agreement = 2.22, 4.00.
Figure 6
Figure 6
Bland–Altman plot comparing predicted appendicular skeletal muscle mass (ASM) and appendicular skeletal muscle mass index (ASMI) vs. actual dual‐energy X‐ray absorptiometry (DXA) measurements in one‐third (n = 174) of Dataset720 after deriving regression model with the remaining two‐thirds. Top and bottom reference lines indicate 95% confidence interval. (A) ASM mean difference = −0.04 ± 0.82, limits of agreement = 1.57, −1.65. (B) ASMI mean difference = −0.02 ± 0.31, limits of agreement = 0.58, −0.61.
Figure 7
Figure 7
Recommended application workflow of bioimpedance analysis (BIA) for sarcopenia screening. (A) Skeletal muscle mass (SMM) can be taken directly from the report of a commercially available BIA device (InBody 120 or 720) and used as the appendicular skeletal muscle mass (ASM) as defined by European Working Group on Sarcopenia in Older People or Asian Working Group for Sarcopenia. (B, C) The SMM or ASM measured by BIA can be substituted into the relevant equations along with other parameters of weight, height, gender, or body mass index for the estimation of predicted ASM (which is the expected ASM from a DXA measurement). (B) Prediction equation from InBody 120 measurement. (C) Prediction equation from InBody 720 measurement. (D) This predicted ASM (ASMpredicted) can be directly compared with the DXA cut‐off values defined by the European Working Group on Sarcopenia in Older People or Asian Working Group for Sarcopenia for male or female for the diagnosis of low muscle mass content. Suggested BIA application for muscle mass evaluation in community settings.

References

    1. Cruz‐Jentoft AJ, Sayer AA. Sarcopenia. Lancet 2019;393:2636–2646. - PubMed
    1. Cao L, Morley JE. Sarcopenia is recognized as an independent condition by an International Classification of Disease, Tenth Revision, Clinical Modification (ICD‐10‐CM) code. J Am Med Dir Assoc 2016;17:675–677. - PubMed
    1. Cruz‐Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010;39:412–423. - PMC - PubMed
    1. Cruz‐Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyere O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 2019;48:16–31. - PMC - PubMed
    1. Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, et al. Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc 2014;15:95–101. - PubMed

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