Publication: Relationship between calf circumference and skeletal muscle index among community-dwelling thai elderly
Issued Date
2021-11-01
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01252208
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2-s2.0-85120613150
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Mahidol University
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SCOPUS
Bibliographic Citation
Journal of the Medical Association of Thailand. Vol.104, No.11 (2021), 1814-1820
Suggested Citation
Apichaya Tannirandorn, Watsachon Pangkanon, Aree Prachansuwan, Pisit Isarashewawat Relationship between calf circumference and skeletal muscle index among community-dwelling thai elderly. Journal of the Medical Association of Thailand. Vol.104, No.11 (2021), 1814-1820. doi:10.35755/jmedassocthai.2021.11.13031 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/77697
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Title
Relationship between calf circumference and skeletal muscle index among community-dwelling thai elderly
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Abstract
Background: A strong association between calf circumference (CC) and skeletal muscle index (SMI) has been established worldwide in the elderly, however, these data in the Thai population are lacking. Objective: To evaluate the relationship between CC and SMI, as well as to identify the important predictors of SMI among the community-dwelling Thai elderly. Materials and Methods: The present study was an analytic cross-sectional study performed in 110 community-dwelling adults aged 60 years and older who lived in Sriracha, Chonburi, Thailand. Weight, height, and the maximum CC were measured in standing position. Body composition was measured using the bioelectrical impedance analysis (BIA) and the SMI was calculated as the appendicular skeletal muscle mass (ASM) divided by the height squared ). Pearsons correlation was used to indicate the relationship between CC and SMI. Multiple linear regression was developed to predict SMI. Results: The prevalence of low muscle mass in men and women were 23.5% and 33.3%, respectively. CC had a positive correlation with SMI (r=0.75; p<0.001). The cut-off values for predicting low muscle mass using CC were 34.0 cm (sensitivity 85.5%, specificity 71.8%, AUC 0.895) in women, and 33.4 cm (sensitivity 75.0%, specificity 92.3%, AUC 0.925) in men. Multiple linear regression analysis revealed age, gender, weight, and CC as the key predictors for SMI with adjusted r of the model equal to 0.80. CC and weight had a direct effect on SMI. On the other hand, age was inversely related to SMI. Women had lower SMI than men. Conclusion: CC was positively associated with SMI, and it could be used as a screening tool to identify the community-dwelling Thai elderly with low muscle mass in the field settings. Important predictors of SMI were age, gender, weight, and CC.