These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Skeletal muscle mass obtained by anthropometric equation and presence of sarcopenia in postmenopausal women.
    Author: Felipe TL, Grili PPDF, Vidigal CV, Albergaria BH, da Cruz GF, Marques-Rocha JL, Guandalini VR.
    Journal: Rev Bras Ginecol Obstet; 2024; 46():. PubMed ID: 38765537.
    Abstract:
    OBJECTIVE: To analyze the amount of muscle and the presence of sarcopenia in postmenopausal women using different methods, verifying the agreement between them as to skeletal muscle mass (SMM). METHODS: This cross-sectional observational study was conducted with postmenopausal women aged ≥ 50 years. SMM was obtained from a predictive equation, Bioelectrical Impedance (BIA), and Dual Energy X-Ray Absorptiometry (DXA). The skeletal muscle mass index (SMI) and the appendicular skeletal muscle mass index (ASMI) were calculated. The cut-off point of SMI was determined for the population itself. The agreement between the SMI obtained using the different methods was verified. Sarcopenia was diagnosed according to the criteria proposed by the European Working Group on Sarcopenia in Older People 2 (EWGSOP2). The significance level adopted for all tests was 5.0%. RESULTS: A total of 112 women were evaluated, with an average age of 66.1 ± 5.65 years. Among them, 51.8% were sufficiently active and 43.8% were overweight and obese. The SMI cut-offs were 6.46 kg/m2 for the predictive equation and 7.66 kg/m2 for BIA, with high sensitivity and specificity. There was an excellent agreement in the identification of SMM by the predictive equation (0.89 [0.824-0.917], p < 0.001) and BIA (0.92 [0.883-0.945], p < 0.001), in reference to DXA. The prevalence of sarcopenia was 0.9%, 1.8%, and 2.7% according to BIA, DXA, and the predictive equation, respectively. CONCLUSION: The predictive equation showed the expected agreement in estimating skeletal muscle mass in postmenopausal women, offering a viable and accurate alternative.
    [Abstract] [Full Text] [Related] [New Search]