肌萎缩
医学
随机对照试验
摄入
内科学
物理疗法
阻力训练
作者
Yasunobu Tokuda,Hiroyasu Mori
出处
期刊:Journal of the American Nutrition Association
日期:2022-02-23
卷期号:42 (3): 255-262
被引量:12
标识
DOI:10.1080/07315724.2022.2025546
摘要
Objective: Tea catechins (TCCs) have gained significant attention owing to their health effects. However, evidence is limited regarding the benefit of TCC and essential amino acids (EAAs) ingestion plus that of TCC ingestion after resistance exercise (RE) among older individuals with sarcopenia. We aimed to evaluate whether a 24-week nutritional program involving EAA and TCC supplementation after RE improved skeletal muscle mass (SMM) among older adults with sarcopenia.Methods: We conducted an open-label, pilot, randomized controlled trial among older adults with sarcopenia at the Harima Care Center or community in Hyogo, Japan. Participants were allocated to RE (n = 18), RE with EAA supplementation (RE + EAA, n = 18), or RE with EAA and TCC supplementation (RE + EAA + TCC, n = 18) groups. Sarcopenia was defined using the Asian Working Group for Sarcopenia 2019 criteria. A 24-week resistance exercise program was carried out twice weekly, with an intake of 3,000 mg and 540 mg of EAA and TCC supplements, respectively. SMM was the primary outcome parameter. Results: The mean adherence rate to exercise and supplementation intake over the 24-week intervention period was 86.8% in the RE + EAA + TCC group, 86.4% in the RE + EAA group, and 85.4% in the RE group. A significant group-by-time interaction was identified for SMM (p = 0.010). The pre- to post-intervention increase in SMM was significantly higher in the RE + EAA + TCC group than in the RE group (p = 0.010). Conclusions: These results suggest that supplementation with EAA and TCC after RE, compared to RE only, improves SMM in older people with sarcopenia. To the best of our knowledge, our study is the first pilot randomized controlled trial to evaluate the effect of TCC supplementation on SMM in older people with sarcopenia.Supplemental data for this article is available online at http://dx.doi.org/10.1080/07315724.2022.2025546
科研通智能强力驱动
Strongly Powered by AbleSci AI