Related Experiment Video
Updated: Jun 28, 2026
Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos
Published on: March 21, 2021
Prevalence of Sarcopenia in Community-Dwelling Older Adults According to Simplified Algorithms for Sarcopenia
Hee-Kyung Chang1, Ji-Yeon Lee2,3, Cho-Rong Gil3
1College of Nursing, Senior Health Research Center of the Health & Science Institute, Gyeongsang National University, Jinju, Gyeongnam-do, South Korea.
Purpose:
This study sought to identify the prevalence of sarcopenia in community-dwelling Korean older adults and validate two simplified diagnostic algorithms based on the Asian Working Group for Sarcopenia (AWGS) algorithm for identifying sarcopenia.
Patients And Methods:
Patients (n = 338) aged ≥65 years participated in this cross-sectional study. Muscle strength was measured by hand grip strength, physical performance by gait speed, and muscle mass by the skeletal muscle mass index (SMI). Sarcopenia was assessed using the AWGS-recommended algorithm and two simplified algorithms (A and B). Algorithms A and B were validated with respect to the AWGS-recommended algorithm using the chi-square test, and the sensitivity and specificity were obtained.
Results:
Sarcopenia prevalence, determined using the AWGS-recommended algorithm, was 40.3% and 41.3% in men and women, respectively. The overall prevalence of sarcopenia was 41.0% by the AWGS-recommended algorithm, 37.6% by algorithm A, and 37.6% by algorithm B; 111 participants were diagnosed with sarcopenia using all three methods (p = 0.157).
Conclusion:
We established sarcopenia prevalence among rural community-dwelling adults in Korea and confirmed that the simplified algorithms were suitable for the identification of sarcopenia in rural community-dwelling older adults in Korea. Further studies are needed to assess whether these simplified algorithms are applicable to older Asian adults with functional and/or cognitive impairment and nursing home residents.
