ArticlePloS one2023
Risk phenotype for sarcopenia in older adults from Amazonas, Brazil; a cross-sectional study.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- The Effects of Social Dance on Muscular Fitness and Longevity-Related Circulating Biomarkers in the Elderly.Journal of functional morphology and kinesiology · 2026Article
- Physical behaviour profiles and their associations with fitness and function in older adults: a cross-sectional latent profile analysis.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2026Article
- Translation, cross-cultural adaptation and validation of the composite physical function scale in Chinese community-dwelling older adults.BMC geriatrics · 2025Article
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Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere are several markers for the suspicion, identification, and confirmation of sarcopenia.
objectivesTo 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.
methodsA 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).
resultsCluster 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.
conclusionsSARC-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.
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