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

被引:8
作者
Abdalla, Pedro Pugliesi [1 ,7 ]
da Silva, Leonardo Santos Lopes [1 ]
Venturini, Ana Claudia Rossini [1 ,2 ]
Tasinafo Jr, Marcio Fernando
Schneider, Guilherme [2 ]
dos Santos, Andre Pereira [1 ,2 ]
Gomide, Euripedes Barsanulfo Goncalves [1 ,2 ,3 ]
Carvalho, Anderson dos Santos [4 ]
Bohn, Lucimere [5 ,6 ]
机构
[1] Univ Sao Paulo, Sch Phys Educ & Sport Ribeirao Preto, Study & Res Grp Anthropometry Training & Sport GEP, Ribeirao Preto, SP, Brazil
[2] Univ Sao Paulo, Ribeira Preto Coll Nursing, Ribeira Preto, SP, Brazil
[3] Claretiano Univ Ctr, Batatais, SP, Brazil
[4] Univ Paulista, Phys Educ, Sao Jose Do Rio Preto, SP, Brazil
[5] Lusofona Univ Porto, Fac Psychol Educ & Sport, Porto, Portugal
[6] Univ Porto, Res Ctr Phys Act Hlth & Leisure CIAFEL, Fac Sports, Porto, Portugal
[7] Ave Bandeirantes 3900, Ribeira Preto, SP, Brazil
关键词
Appendicular lean soft tissue; Lean limb mass; Segmental lean mass; Skeletal muscle mass; LEAN SOFT-TISSUE; ASIAN WORKING GROUP; SKELETAL-MUSCLE; PREDICTION EQUATIONS; CROSS-VALIDATION; SARCOPENIA; MODELS; CONSENSUS; MEN; CONCORDANCE;
D O I
10.1016/j.archger.2023.104972
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
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 (r2), 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.
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页数:9
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