A community-driven digital health intervention for cardiovascular risk factor control: a cluster randomized controlled Trial

Background Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of morbidity and mortality in China. Despite the critical importance of controlling modifiable risk factors such as blood pressure (BP), blood glucose, and lipids, control rates remain suboptimally low due to resource constraints and limited patient adherence. While mobile health (mHealth) tools like WeChat show promise in patient management, high-quality evidence regarding their effectiveness in achieving comprehensive, multi-factor control in high-risk populations remains scarce. Purpose To evaluate the effectiveness of the Community-Driven Digital Health Program (CDDHP), an integrated management model designed to synergize specialist expertise, community resources, and mHealth tools, in improving the comprehensive control of cardiovascular risk factors among high-risk individuals. Methods A cluster-randomized controlled trial was conducted at 12 community health centers in China (8 intervention, 4 control). Patients aged 40 years or older with established ASCVD or intermediate-to-high 10-year cardiovascular risk (China-PAR score ≥ 10%) and at least one uncontrolled risk factor were enrolled and followed for 24 months. The control group received routine community-based care alone. The intervention group received routine care plus the CDDHP, which included individualized risk management goals set by cardiovascular specialists and personalized digital health guidance (monthly text messages and weekly WeChat health education articles). The primary endpoint was the change in the composite control rate of BP, fasting blood glucose (FBG), and low-density lipoprotein cholesterol (LDL-C) from baseline to the 24-month follow-up. Secondary outcomes included the change in individual control rates and mean changes in risk factors. Between-group differences were analyzed using generalized estimating equations and linear mixed-effects models. Results Of the 1,859 participants enrolled (mean age, 68.25 ± 6.22 years; 44.54% men), 1,245 were in the intervention group and 614 in the control group. At 24 months, the intervention group achieved a significantly higher composite control rate than the control group (47.48% vs. 35.89%; odds ratio [OR], 1.80; 95% confidence interval [CI], 1.30 – 2.49). Specifically, the intervention significantly improved control rates for BP in hypertensive participants (OR, 8.28; 95% CI, 2.48 – 27.66) and FBG in diabetic patients (OR, 3.93; 95% CI, 1.76 – 8.76). A greater reduction in systolic BP was observed in the intervention group (difference: -5.67 mmHg; 95% CI, -9.57 to -1.76). No significant between-group differences were observed in LDL-C control rates or mean levels of FBG, diastolic BP, and LDL-C. Conclusion The CDDHP, leveraging specialist expertise, community resources, and mHealth tools, significantly improved the comprehensive control of cardiovascular risk factors in a high-risk population.