Digital health management models improve the metabolism, sleep, and gut microbiota in patients with metabolic disorders

数字健康管理模式可改善代谢紊乱患者的新陈代谢、睡眠和肠道菌群。

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Abstract

OBJECTIVE: This study aimed to explore the effects of lifestyle interventions based on a digital health management (DHM) model on metabolism, sleep, and gut microbiota in patients with metabolic disorders. METHODS: This study enrolled 240 patients aged 18-65 years with at least one metabolic abnormality, who were randomized into the DHM group (n = 120) and control group (n = 120). The DHM group used a closed-loop digital management system consisting of the "Health Assistant" WeChat applet and the Huawei Band 7. This system enabled real-time data synchronization to deliver personalized dietary plans (calorie-targeted, adjusted for baseline metabolic parameters), dynamic exercise prescriptions (heart rate- and activity-adjusted with real-time feedback), and a sleep optimization module (white noise playback and breathing exercise prompts). The control group received conventional health education. The primary endpoint was the change in visceral fat area (VFA) over 12 months; secondary endpoints included the coefficient of variation (CV) of fasting blood glucose, resting energy expenditure (REE), brachial-ankle pulse wave velocity (baPWV) for arterial stiffness, gut microbiota abundance, and sleep quality scores. RESULTS: After 12 months, the DHM group showed a significant reduction in VFA (from 122.9cm(2) to 75.7cm(2)), with lower VFA than the control group at 3, 6, and 12 months (p < 0.05). In the DHM group, the CV of fasting blood glucose decreased to 8.4 ± 1.1% (p < 0.001), REE increased by 167 kcal/d (p < 0.001), baPWV decreased by 348.6 cm/s (p < 0.001), the abundance of butyrate-producing bacteria increased 3.1-fold (p < 0.001), and sleep quality scores improved to 93.1 ± 9.3 points (p < 0.001). All outcomes in the DHM group were significantly superior to those in the control group (all p < 0.05). CONCLUSION: The DHM model effectively improves body composition, glycemic stability, and cardiovascular risk in patients with metabolic abnormalities through multidimensional interventions, providing an evidence-based practical solution to chronic disease prevention.

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