Cited by 113Body Composition Measurement TechniquesNutrition and Health in AgingElectrical and Bioimpedance Tomography

Equation models developed with bioelectric impedance analysis tools to assess muscle mass: a systematic review.

Open access
Beaudart, Charlotte, Bruyère, Olivier, Geerinck, Anton, Hajaoui, Manon, Scafoglieri, Aldo, Perkisas, Stany, Bautmans, Ivan, Gielen, Evelien +2 more·2020·Clinical Nutrition ESPEN

Abstract

BACKGROUND & AIMS: This systematic review aims to systematically assess and summarize the equation models developed to estimate muscle mass with bioelectric impedance analysis (BIA) instruments against a reference instrument (DXA, MRI, CT-scan, Ultrasonography), in order to help researchers and clinicians choose the most adapted equation, depending on the device and the population in question. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement was followed. Medline (via Ovid) and Scopus were searched in January 2019 for observational (transversal, longitudinal, retrospective) studies developing an equation prediction model to validate BIA against another reference method for the assessment of muscle mass. Study selection and data extraction was performed independently by two researchers. Methodological quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. RESULTS: 25 studies matched the inclusion criteria and were included in the present systematic review. Among them, 10 studies proposed an equation for subjects aged 65 years and older, 9 for adults, 4 for infants and 2 did not report the age of the population. A large heterogeneity was observed regarding the brand and type of BIA as well as the administration protocol (mode, frequency, number of electrodes, administration position and empty bladder/stomach or not). Most of the studies used DXA as the reference instrument, except 4 that used MRI. In each of the included papers authors provided, through simple or multiple regression, a predictive equation for muscle mass. BIA resistance index, sex, weight, age, BIA reactance and height were most frequently included as predictive variables. The majority of the equations developed explained more than 80% of the variance between both instruments. Out of the 25 equations available, only 9 were also validated in another population within the same paper. CONCLUSION: This systematic review of the literature offers clinicians and researchers the opportunity to verify the existence of a prediction equation when using a BIA device for estimating muscle mass. This will help them to obtain a valid estimation of muscle mass in a specific population and with a specific instrument. If the equation exists and has been validated by a study free of high risk of bias, it's use is recommended because the development of a new equation in the same context seems redundant and undesirable. If a validation has not been carried out for a specific brand of BIA, reference method or population, we recommend the development and cross-validation of a new equation.

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Crossref · 10.1016/j.clnesp.2019.09.012

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  • The equation developed in this study can be used to monitor changes in FFM resulting from growth, dietary programs, and physical exercises.

    “which can be used to monitor changes in FFM resulting from growth, dietary programs, and physical exercises (14, 58, 59).”

    From Development and Cross-Validation of a Predictive Equation for Fat-Free Mass in Brazilian Adolescents by Bioelectrical Impedance (2022) · cites this paper as [14]

    The Development of equations section (p. 55–57) describes BIA equations for estimating muscle or lean mass, and the discussion recommends choosing an equation suited to the population and device. It does not establish that an equation developed in this review can monitor changes in FFM caused by growth, dietary programs, or exercise; the review reports equations developed in other studies. (LLM, conf=0.82)

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  • The use of DXA to derive BIA equations has been widely accepted.

    “Although DXA cannot be considered the gold standard for the determination of FFM at the molecular level, and the four-compartment model (4C) is the most suitable reference method to assess FM and FFM at the molecular level (12), due to the complexity of the technique (13), the use of DXA to derive BIA equations has been widely accepted (14, 15).”
  • Due to the complexity of the 4C technique, the use of DXA to derive BIA equations has been widely accepted.

    “However, due to the complexity of the technique (13), the use of DXA to derive BIA equations has been widely accepted (14, 15).”

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References 60 · Cited by 113

Authors
Beaudart, C., Bruyère, O., Geerinck, A., Hajaoui, M., Scafoglieri, A., Perkisas, S., Bautmans, I., Gielen, E., Reginster, J.-Y., & Buckinx, F.
Affiliations
  • University of Liège (BE)
  • Vrije Universiteit Brussel (BE)
  • University of Antwerp (BE)
  • KU Leuven (BE)
Corresponding author
Beaudart, Charlotte
Venue
Clinical Nutrition ESPEN
Publisher
Elsevier BV
Published
2020-02
Volume
35
Pages
47-62
ISSN
2405-4577 (ISSN-L)
OpenAlex
W2988737732
Cited by
113
References
60
Citations by year
2026: 19 · 2025: 16 · 2024: 28 · 2023: 15 · 2022: 12 · 2021: 17 · 2020: 6
FWCI
1.04
Type
journal article
Language
en
Open access
Locations
  • Clinical Nutrition ESPEN (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • Lirias (KU Leuven) (submittedVersion, other-oa)
  • ORBi (University of Liège) (submittedVersion)
  • VUBIR (Vrije Universiteit Brussel) (submittedVersion)
Topics
  • Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
  • Health Sciences › Medicine › Physiology › Nutrition and Health in Aging
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electrical and Bioimpedance Tomography
Keywords
bioelectrical impedance analysis, muscle mass assessment, prediction equations, equation validation, reference method, dual-energy X-ray absorptiometry, resistance and reactance, older adults, cross-validation
MeSH terms
Body Composition, Female, Humans, Male, Body Mass Index, Databases, Factual, Electric Impedance, Muscle, Skeletal

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