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Life sciences · Journal article
Theoretical and Natural Science · September 29, 2026
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Metabolic diseases are driven partly by modifiable behaviors, yet conventional lifestyle programs often lack continuous monitoring, sustained engagement, and individualized adjustment. Wearable technologies may address these limitations by capturing behavioral and physiological data in everyday settings and translating them into timely preventive support. This paper synthesizes evidence on wearable-driven individualized lifestyle interventions for the primary prevention of obesity, type 2 diabetes, metabolic syndrome, and cardiovascular disease. It examines physical activity, dietary, sleep, and multicomponent interventions, together with their mechanisms, limitations, and implementation requirements. Evidence indicates that wearable-supported programs consistently increase physical activity, particularly when self-monitoring is combined with goal setting, feedback, consultation, or coaching. Improvements in weight, BMI, waist circumference, and HbA1c are generally modest, while effects on blood pressure and other cardiometabolic markers remain inconsistent. Continuous glucose monitoring and multimodal platforms may enable more responsive dietary guidance, although short follow-up periods, observational designs, uncertain targets in people without diabetes, and burdensome food recording limit causal interpretation. Sleep-focused evidence is comparatively weak, and few studies evaluate incident metabolic disease; declining engagement, heterogeneous definitions of personalization, proprietary algorithms, measurement error, privacy concerns, and digital inequality further constrain translation. Wearables therefore represent an enabling infrastructure rather than an independent preventive treatment. Their public-health value will depend on transparent, validated, professionally supervised, affordable, culturally appropriate, and interoperable systems that sustain adaptive support in primary care and community settings.