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Background: There are several markers for the suspicion, identification, and confirmation of sarcopenia., Objectives: To analyse the importance of several markers for assessing sarcopenia by classifying phenotypes based on five domains: symptomatology, muscle function, muscle mass, physical performance, and physical function., Methods: A cross-sectional study analysing 312 older adults (72.6±7.8 yrs) was conducted in Novo Aripuanã, Amazonas, Brazil. Symptoms of sarcopenia were determined with the SARC-Calf; muscle function was assessed using the 30-Chair Stand test (CST), 30-CST power, and handgrip strength (HGS) with and without normalisation for body mass/height; the skeletal muscle mass index (SMMI) was estimated from anthropometry; physical performance was determined through the 4-m gait speed (GS) and 6-min walking test (6MWT); and physical function was determined with the Composite Physical Function Scale (CPF)., Results: Cluster analysis revealed two phenotypes (at risk vs not at risk for sarcopenia) and the contribution of each marker (ranged from 0 to 1). In men, the contribution of each marker was: 1 for SARC-Calf, 0.18 for SMMI, 0.09 for 30-CST power and 0.06 for HGS; in women: 1 for SARC-Calf, 0.25 for 30-CST power, 0.22 for SMMI, 0.06 for GS, 0.04 for HGS, and 0.03 for CPF. Considering the cutoff values proposed by Rikli and Jones (2013) for physical function and Cruz-Jentoft et al. (2019) for the other domains, the risk profile for sarcopenia was characterized by: high SARC-Calf in both sexes (men:51.8 vs 3.6%, p<0.001; women:71.2 vs 1.1%, p<0.001), low SMMI (men:73.2 vs 44.6%, p<0.002; women:44.1 vs 23.6%, p = 0.002); in women, low GS (38.7 vs 12.4%, p<0.001) and low CPF (29.7 vs 15.7%, p = 0.020), and no differences in HGS between groups in both sexes., Conclusions: SARC-Calf, SMMI, and 30-CST were more relevant markers for sarcopenia risk in older adults of both sexes, GS and CPF played also an important role in women., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 de Lima et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background and Aim: Sarcopenia is primarily a disease in older people characterized by reduced muscle mass and strength. Nevertheless, sarcopenia may, at least partially, have pediatric origins. The study aimed to identify risk phenotypes for sarcopenia in healthy young people using clustering analysis procedures based on body composition and musculoskeletal fitness., Methods: We conducted a cluster cross-sectional analysis of data from 529 youth aged 10-18 yr. Body composition was assessed using whole-body dual-energy x-ray absorptiometry (DXA), determining: lean body mass index (LBMI, kg/m 2 ), fat body mass index (FBMI, kg/m 2 ), abdominal FBMI (kg/m 2 ), and lean body mass/fat body mass ratio (LBM/FBM); body mass index was also calculated (BMI, kg/m 2 ). Musculoskeletal fitness was assessed using handgrip strength (kg) and vertical jump power (W) tests. Results were presented as absolute values and adjusted by body mass. Plank endurance (s) was also assessed. All variables were sex and age in years standardized (Z-score). LBMI or LBM/FBM ratio ≤ -1 SD were used to identify participants at risk for sarcopenia. Maturity was estimated as the years of distance from the peak height velocity (PHV) age., Results: Using the Z-score means for body composition and musculoskeletal fitness and having LBMI or LBM/FBM ratio as the categorical variables (at risk vs. not at risk), the cluster analyses indicated three homogeneous groups (phenotypes, P): P1, risk body composition and unfit; P2, non-risk body composition and non-fit, and P3, non-risk body composition and fit. With the LBMI as a categorical variable, the ANOVA models showed that the body composition and absolute values of musculoskeletal fitness were in P1 < P2 < P3 and the estimated PHV age of P1 > P3 in both sexes (p < 0.001). Having the LBM/FBM as a categorical variable, higher values of BMI, FBMI, and abdominal FBMI, and lower values of handgrip strength and vertical jump power both adjusted for body mass and plank endurance were observed in P1 than in P2 and/or P3 and the P2 than in the P3 in boys and girls (p < 0.001)., Conclusions: Two risk phenotypes for sarcopenia were identified in apparently healthy young people: I. a low LBMI phenotype with low BMI and II. a low LBM to FBM phenotype with high BMI and FBMI. In both risk phenotypes I and II, musculoskeletal fitness was low. For screening, we suggest using absolute measures of handgrip strength and vertical jump power in phenotype I and body mass adjusted measures of these markers, as well as the plank endurance time in phenotype II., Competing Interests: Conflicts of interest The authors declare that they have no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

This study examined the predictive validity of musculoskeletal fitness tests for identifying sarcopenia in youth. The sample was 529 participants age 10 to 18 years. Indices included: total lean body mass (LBM) normalized for height (LBM index, LBMI, kg/m2), appendicular LBMI (aLBMI, kg/m2), and LBM to fat body mass (FBM) ratio (LBM/FBM). Lean and fat tissue were measured via DXA. The cutoff value for sarcopenia was – 2.0 standard deviations ≤ mean for age and sex. Fitness was assessed using handgrip, plank, and vertical jump tests. Variables were standardized using the lambda-mu-sigma (LMS) method. By sex, analysis included the area under the curve (AUC), sensitivity (Se), and specificity (Sp). The ROC curves for aLBMI was highly accurate (AUCs ≥ 0.90, Se and Sp = 86–88%) for vertical jump and moderately accurate for handgrip (AUCs = 0.87–0.88, Se and Sp = 71–75%). Fitness tests can be used to identify pediatric sarcopenia. [ABSTRACT FROM AUTHOR]