Yasuharu Tabara1, Tome Ikezoe2, Kazuya Setoh3, Ken Sugimoto4, Takahisa Kawaguchi3, Shinji Kosugi5, Takeo Nakayama6, Noriaki Ichihashi2, Tadao Tsuboyama7, Fumihiko Matsuda3. 1. Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto 606-8507, Japan. Electronic address: tabara@genome.med.kyoto-u.ac.jp. 2. Department of Physical Therapy, Human Health Sciences, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto 606-8507, Japan. 3. Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto 606-8507, Japan. 4. Department of Geriatric and General Medicine, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan. 5. Department of Medical Ethics and Medical Genetics, Kyoto University School of Public Health, Sakyo-ku, Kyoto 606-8501, Japan. 6. Department of Health Informatics, Kyoto University School of Public Health, Sakyo-ku, Kyoto 606-8501, Japan. 7. Department of Physical Therapy, Human Health Sciences, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto 606-8507, Japan; School of Health Sciences, Bukkyo University, Chukyo-ku, Kyoto 604-8418, Japan.
Abstract
BACKGROUNDS: Sarcopenia in older adults is a risk factor for age-related morbidity and mortality. This study aimed to clarify the diagnostic significance of the revised diagnostic algorithm for sarcopenia from Asian Working Group for Sarcopenia by comparing physical and clinical characteristics of individuals diagnosed with sarcopenia by the initial and revised algorithms. METHODS: Study participants were 2061 older community residents. Skeletal muscle mass was measured by bioimpedance analysis. Handgrip strength and physical function required for the diagnosis of sarcopenia were measured by conventional methods. Carotid intima-media thickness was used as a marker of atherosclerosis in a large artery. RESULTS: Using the initial algorithm, 60 of the participants were diagnosed with sarcopenia, but based on the revised algorithm, 89 had sarcopenia and 21 severe sarcopenia. The higher frequency of sarcopenia was attributed to changes in the cut-off values for slow gait speed and the addition of the 5-time chair-stand test as part of the assessment of physical performance. Physical characteristics of individuals diagnosed with sarcopenia by either algorithm did not differ markedly, but those with severe sarcopenia had significantly poorer physical performance even with a muscle mass similar to those with sarcopenia. There was a linear correlation between the severity of sarcopenia and carotid intima-media thickness (no sarcopenia: 0.94 ± 0.31, sarcopenia: 1.04 ± 0.41, and severe sarcopenia: 1.07 ± 0.55 mm, P = 0.003). CONCLUSION: The revised diagnostic algorithm was superior to the initial version at identifying individuals with sarcopenia and severe sarcopenia with a worse cardiovascular profile.
BACKGROUNDS: Sarcopenia in older adults is a risk factor for age-related morbidity and mortality. This study aimed to clarify the diagnostic significance of the revised diagnostic algorithm for sarcopenia from Asian Working Group for Sarcopenia by comparing physical and clinical characteristics of individuals diagnosed with sarcopenia by the initial and revised algorithms. METHODS: Study participants were 2061 older community residents. Skeletal muscle mass was measured by bioimpedance analysis. Handgrip strength and physical function required for the diagnosis of sarcopenia were measured by conventional methods. Carotid intima-media thickness was used as a marker of atherosclerosis in a large artery. RESULTS: Using the initial algorithm, 60 of the participants were diagnosed with sarcopenia, but based on the revised algorithm, 89 had sarcopenia and 21 severe sarcopenia. The higher frequency of sarcopenia was attributed to changes in the cut-off values for slow gait speed and the addition of the 5-time chair-stand test as part of the assessment of physical performance. Physical characteristics of individuals diagnosed with sarcopenia by either algorithm did not differ markedly, but those with severe sarcopenia had significantly poorer physical performance even with a muscle mass similar to those with sarcopenia. There was a linear correlation between the severity of sarcopenia and carotid intima-media thickness (no sarcopenia: 0.94 ± 0.31, sarcopenia: 1.04 ± 0.41, and severe sarcopenia: 1.07 ± 0.55 mm, P = 0.003). CONCLUSION: The revised diagnostic algorithm was superior to the initial version at identifying individuals with sarcopenia and severe sarcopenia with a worse cardiovascular profile.