KM Data Division, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Yuseong-gu, Daejeon, 34054, Republic of Korea.
National Science and Technology Data Division, Korea Institute of Science and Technology Information, Daejeon, 34141, Republic of Korea.
Sci Rep. 2024 Oct 12;14(1):23865. doi: 10.1038/s41598-024-74619-7.
Metabolic syndrome increases the risks of cardiovascular diseases, type 2 diabetes, and certain cancers. The early detection of metabolic syndrome is clinically relevant, as it enables timely and targeted interventions. In the current study, we aimed to investigate the association between metabolic syndrome and heart rate measured using wearable devices in a real-world setting and compare this association with that for clinical resting heart rate. Data from 564 middle-aged adults who wore wearable devices for at least 7 days with a minimum daily wear time of 20 h were analyzed. The results showed significantly elevated all-day, sleeping, minimum, and inactive heart rates in men with pre-metabolic or metabolic syndrome compared with those in normal individuals, whereas sleeping heart rate and heart rate dips were significantly increased and decreased, respectively, in women with metabolic syndrome. After adjusting for confounders, every 10-beats-per-minute increment in all-day, sleeping, minimum, and inactive heart rates in men corresponded to odds ratios of 2.80 (95% confidence interval 1.53-5.44), 3.06 (1.57-6.40), 4.21 (1.87-10.47), and 3.09 (1.64-6.29), respectively, for the presence of pre-metabolic or metabolic syndrome. In women, the association was significant only for heart rate dips (odds ratio = 0.49 [95% confidence interval 0.25-0.96] for every 10% increment). Models incorporating inactive or minimum heart rate in men and heart rate dip in women demonstrated better fits, as indicated by lower Akaike information criterion values (170.3 in men and 364.9 in women), compared with models that included clinical resting heart rate (173.4 in men and 369.1 in women). These findings suggest that the heart rate indices obtained from wearable devices may facilitate early identification of metabolic syndrome.
代谢综合征会增加心血管疾病、2 型糖尿病和某些癌症的风险。在临床实践中，代谢综合征的早期检测具有重要意义，因为它可以实现及时和有针对性的干预。在本研究中，我们旨在探讨在真实环境中使用可穿戴设备测量的心率与代谢综合征之间的关联，并将这种关联与临床静息心率进行比较。分析了 564 名至少佩戴可穿戴设备 7 天且每日佩戴时间至少 20 小时的中年人的数据。结果显示，与正常个体相比，患有前代谢综合征或代谢综合征的男性全天、睡眠、最小和不活动心率显著升高，而患有代谢综合征的女性睡眠心率和心率下降分别显著升高和降低。调整混杂因素后，男性全天、睡眠、最小和不活动心率每增加 10 次/分钟，患前代谢综合征或代谢综合征的几率分别为 2.80（95%置信区间 1.53-5.44）、3.06（1.57-6.40）、4.21（1.87-10.47）和 3.09（1.64-6.29）。在女性中，这种关联仅在心率下降时具有显著性（每增加 10%，心率下降的几率为 0.49[95%置信区间 0.25-0.96]）。在男性中纳入不活动或最小心率以及女性中纳入心率下降的模型显示出更好的拟合度，因为它们的 Akaike 信息准则值较低（男性为 170.3，女性为 364.9），而纳入临床静息心率的模型的 Akaike 信息准则值较高（男性为 173.4，女性为 369.1）。这些发现表明，可穿戴设备获得的心率指标可能有助于早期识别代谢综合征。
