NHC Key Laboratory of Hormones and Development, Chu Hsien-I Memorial Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, No.6 North Huanrui Rd, Beichen District, Tianjin, China.
Tianjin Key Laboratory of Metabolic Diseases, Tianjin Medical University, Tianjin, 300134, China.
Sci Rep. 2024 Mar 18;14(1):6459. doi: 10.1038/s41598-024-57082-2.
Physical activity (PA) is linked to a decreased risk of type 2 diabetes mellitus (T2DM). However, the influence of circadian PA trajectories remains uncertain. This study aims to explore the optimal circadian PA trajectory pattern for reducing the risk of T2DM. Methods: A total of 502,400 participants were recruited from the UK Biobank between 2006 and 2010, and 102,323 participants provided valid accelerometer-captured acceleration data. After excluding individuals with prior T2DM, 99,532 participants were included in the final analysis. We initially investigated the association between PA intensity at 24 hourly time points and T2DM. Subsequently, PA trajectories were identified using K-means cluster analysis. Cox proportional hazard models were employed to estimate hazard ratios (HR). Four distinct PA trajectories were identified: consistently low, single peak, double peak, and intense trajectories. Compared to consistently low, single peak, double peak and intense PA trajectory reduced the risk of T2DM progressively. Sensitivity analyses, further excluding individuals with glycated hemoglobin (HbA1c) ≥ 6.5% or random glucose ≥ 11.1 mmol/L and adjusted for daily average acceleration, yielded consistent results. This confirms that the ideal circadian PA trajectory serves as a protective factor, independently of PA intensity. Subgroup analyses indicated that these effects were more pronounced in men and individuals with eGFR < 60 mL/(min*1.73 m). In conclusion, ideal circadian PA trajectory patterns (especially intense and then double peak) reduced risk of T2DM.
身体活动(PA)与 2 型糖尿病(T2DM)风险降低有关。然而,昼夜节律 PA 轨迹的影响仍不确定。本研究旨在探索降低 T2DM 风险的最佳昼夜节律 PA 轨迹模式。
本研究共纳入了 2006 年至 2010 年间参加英国生物银行的 502400 名参与者,其中 102323 名参与者提供了有效的加速度计捕获的加速度数据。排除有 T2DM 病史的个体后,共有 99532 名参与者纳入最终分析。我们最初研究了 24 小时时间点的 PA 强度与 T2DM 之间的关联。随后,采用 K-均值聚类分析识别 PA 轨迹。采用 Cox 比例风险模型估计风险比(HR)。
共识别出 4 种不同的 PA 轨迹:持续低、单峰、双峰和高强度轨迹。与持续低相比,单峰、双峰和高强度 PA 轨迹可逐步降低 T2DM 的风险。敏感性分析进一步排除糖化血红蛋白(HbA1c)≥6.5%或随机血糖≥11.1mmol/L 的个体,并调整每日平均加速度,结果仍一致。这证实了理想的昼夜节律 PA 轨迹是一种独立于 PA 强度的保护因素。亚组分析表明,这些影响在男性和 eGFR<60ml/(min×1.73m)的个体中更为明显。
理想的昼夜节律 PA 轨迹模式(尤其是高强度和双峰)可降低 T2DM 的风险。