Associations of sleep quality with the skeletal muscle strength in patients with type 2 diabetes with poor glycemic control

睡眠质量与血糖控制不佳的2型糖尿病患者骨骼肌力量的相关性

阅读:1

Abstract

AIMS/INTRODUCTION: Patients with type 2 diabetes mellitus are reported to be at a high risk for sarcopenia, and are known to have a poorer sleep quality. However, the association between sleep quality and skeletal muscle in patients with type 2 diabetes mellitus is not yet precisely understood. MATERIALS AND METHODS: A total of 110 inpatients with type 2 diabetes mellitus aged 40-90 years were enrolled. The sleep quality was assessed using the Pittsburgh sleep quality index (PSQI). Skeletal muscle mass was measured using bioelectrical impedance analysis. Muscle strength was evaluated by measuring the grip strength. We also performed dietary surveys and measurements of the plasma amino acid levels. RESULTS: A high total score on the PSQI was significantly associated with reduced muscle strength, and the association persisted even after adjustments for confounders. On the other hand, adjusted analysis did not reveal any significant associations between the PSQI total score and the skeletal muscle mass. In regard to the associations with subscores of the PSQI, the scores for sleep latency, sleep efficiency, and daytime dysfunction were significantly negatively associated with the muscle strength. Although poor sleep quality was associated with a high confectionery intake and low plasma arginine, citrulline, and ornithine levels, neither confectionery intake levels nor the plasma levels of these amino acids was associated with the muscle strength. CONCLUSIONS: Our study revealed a significant association between the sleep quality and muscle strength in patients with type 2 diabetes mellitus. These results suggest that poor sleep quality is an important risk factor for sarcopenia in patients with type 2 diabetes mellitus.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。