Estimation of Whole-Body and Appendicular Lean Mass from Spine and Hip Dual Energy X-ray Absorptiometry: A Cross-Sectional Study.
Calcif Tissue Int
; 110(3): 341-348, 2022 03.
Article
em En
| MEDLINE
| ID: mdl-34643767
Whole-body dual X-ray absorptiometry (DXA) accurately measures lean mass but is not routinely used in clinical practice. Hip and spine DXA are used in the diagnosis of osteoporosis, and with the common co-occurrence of sarcopenia with osteoporosis, regional DXA scans provide an opportunity for assessment of lean mass. The aim of this study is to develop predictive equations for the estimation of whole-body lean mass (WBLM), appendicular lean mass (ALM) and whole-body fat mass (WBFM) from regional DXA scans. A total of 2427 participants (ages 20-96 year; 57.7% men) from the Geelong Osteoporosis Study who underwent both regional and whole-body DXA were included in the analysis. Using forward stepwise multivariable linear regression, percentage fat (spine%fat, hip%fat) values from lumbar spine and femoral neck DXA were used in combination with clinical data to develop and validate equations for the estimation of WBLM, WBFM and ALM. Mean age was 53.5 year (± 19.2), weight 78.2 kg (± 15.4), height 169.6 cm (± 9.4), WBLM 50.4 kg (± 11.1), ALM 22.8 kg (± 5.4) and WBFM 24.3 kg (± 10.4). Spine%fat (r = 0.21) and hip%fat (r = - 0.34) were correlated with whole-body lean mass (p < 0.001). Final predictive equations included age, sex, weight, height, spine%fat, and hip%fat and possessed high predictive value (Adj R2 0.91-0.94, RMSE 1.60-2.84 kg). K-fold cross-validation methods produced median root mean square error (RMSE) ranging from 1.59 to 2.81 kg for the three models. Regional DXA scans of the spine and hip can be used to estimate whole-body and appendicular lean mass, to assist in the identification of low muscle mass.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Osteoporose
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Composição Corporal
Tipo de estudo:
Observational_studies
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Prevalence_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Adult
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Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article