Anthropometric equations to estimate appendicular muscle mass from dual-energy X-ray absorptiometry (DXA): A scoping review. (July 2023)

• Record Type: Journal Article
• Authors: Abdalla, Pedro Pugliesi; da Silva, Leonardo Santos Lopes; Venturini, Ana Claudia Rossini; Júnior, Márcio Fernando Tasinafo; Schneider, Guilherme; dos Santos, André Pereira; Gomide, Eurípedes Barsanulfo Gonçalves; Carvalho, Anderson dos Santos; Bohn, Lucimere
• Is Part Of: Archives of gerontology and geriatrics. Volume 110(2023)
• Publication Date: 2023-07
• Subjects: Appendicular lean soft tissue -- Lean limb mass -- Segmental lean mass -- Skeletal muscle mass; Aging -- Periodicals; Geriatrics -- Periodicals; Gerontology -- Periodicals; Electronic journals; 305.26
• DOI: 10.1016/j.archger.2023.104972
• Languages: English
• ISSNs: 0167-4943

Abstract

Highlights: There are more than one hundred equations to predict appendicular skeletal muscle mass measured by DXA. Some continents (Africa and Antarctica) do not have equations proposed for the local population. Is necessary to propose more equations for specific diseases. Generally, the equations were valid only when applied for locally and specifically. Abstract: Background: Appendicular skeletal muscle mass (ASM) obtained from dual-energy x-ray absorptiometry (DXA) is recommended to quantify sarcopenia, but has limited availability in disadvantaged-income countries, moreover in an epidemiological context. Predictive equations are easier and less costly to apply, but a review of all available models is still lacking in the scientific literature. The objective of this work is to map, with a scoping review, the different proposed anthropometric equations to predict ASM measured by DXA. Methods: Six databases were searched without restriction on publication date, idiom, and study type. A total of 2, 958 studies were found, of which 39 were included. Eligibility criteria involved ASM measured by DXA, and equations proposed to predict ASM. Results: predictive equations ( n = 122) were gathered for 18 countries. The development phase involves sample size, coefficient of determination (r 2 ), and a standard error of estimative (SEE) varying between 15 and 15, 239 persons, 0.39 and 0.98, 0.07 and 3.38 kg, respectively. The validation phase involves a sample size, accuracy, and a SEE between 15 and 3, 003 persons, 0.61 and 0.98, 0.09 and 3.65 kg, respectively. Conclusions: The different proposed predictive anthropometric equations of ASM DXA were mapped, including validated pre-existing equations, offering an easy-to-use referential article for clinical and research applications. It is necessary to propose more equations for other continents (Africa and Antarctica) and specific health-related conditions (e.g., diseases), once the equations can only have sufficient validity and accuracy to predict ASM generally when applied to the same population.