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Although traditional risk factors such as hypertension, dyslipidemia, diabetes, and smoking have been well established, new research evidence indicates that inflammation, environmental exposure, psychological and social stress, gut microbiota, and genetic susceptibility play a crucial role in shaping the risk profile of CVDs. This review comprehensively summarizes the epidemiology, pathophysiological mechanisms, screening strategies, prevention, and treatment interventions of CVDs throughout the disease development process. Special emphasis is placed on the integration of multiomics methods, artificial intelligence (AI), and digital health technologies (including wearable devices and AI\u2010enhanced electrocardiograms), which are transforming risk prediction and personalized prevention approaches. We also summarize current preclinical and clinical evidence, including ongoing trials, and discuss implementation differences in different socioeconomic environments. Despite significant progress, there are still many challenges in translating new biomarkers and technologies into scalable and equitable clinical applications. This review identifies key knowledge gaps and proposes future directions toward precision cardiovascular medicine, aiming to combine mechanistic insights with practical applications, ultimately reducing the burden of CVDs globally.<\/jats:p>","DOI":"10.1002\/mco2.70869","type":"journal-article","created":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T07:03:39Z","timestamp":1784271819000},"source":"Crossref","is-referenced-by-count":0,"title":["Risk Factors for Cardiovascular Disease: Epidemiology, Screening, Prevention, and Therapeutic Interventions"],"prefix":"10.1002","volume":"7","author":[{"given":"Mowei","family":"Kong","sequence":"first","affiliation":[{"name":"Department of Cardiology The Affiliated Hospital of Southwest Medical University  Luzhou Sichuan Province 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