数字化健康干预对中老年心血管危险因素管理效果的Meta分析

Meta-Analysis of the Effects of Digital Health Interventions on Cardiovascular Risk Factor Management in Middle-Aged and Elderly Adults

摘要: 目的：系统评价数字化健康干预对中老年人群(≥50岁)心血管危险因素的管理效果。方法：系统检索PubMed、Embase、Cochrane Library、Web of Science、中国知网、万方数据库，检索时限为建库至2024年12月。纳入数字化健康干预对中老年心血管危险因素影响的随机对照试验(RCT)。采用RevMan 5.4软件进行Meta分析，效应量采用均数差(MD)或标准化均数差(SMD)及95%置信区间(CI)表示。结果：共纳入18项随机对照试验，包含4892例受试者。Meta分析显示，数字化健康干预在统计学上降低收缩压(MD = −2.66 mmHg, 95% CI: −3.81~−1.52, P < 0.001)、舒张压(MD = −1.26 mmHg, 95% CI: −1.92~−0.60, P < 0.001)、低密度脂蛋白胆固醇(SMD = −0.18, 95% CI: −0.29~−0.07, P = 0.002)、体重(MD = −1.34 kg, 95% CI: −2.08~−0.60, P < 0.001)和糖化血红蛋白(MD = −0.13%, 95% CI: −0.21%~−0.05%, P = 0.001)，并提高体力活动水平(SMD = 0.24, 95% CI: 0.12~0.36, P < 0.001)。亚组分析显示，移动健康应用和短期干预(≤3个月)的效果相对更明显。结论：数字化健康干预可能在中短期内对中老年人群心血管危险因素产生小至中等程度的改善效果，可作为常规心血管风险管理的补充；但现有证据主要来自医疗服务和数字技术基础较好的地区，长期效果及对心血管事件等硬终点的影响仍需进一步验证。

Abstract: Objective: To systematically evaluate the effect of digital health interventions on cardiovascular risk factor management in middle-aged and elderly populations (≥50 years). Methods: PubMed, Embase, Cochrane Library, Web of Science, CNKI, and Wanfang databases were searched from inception to December 2024. Randomized controlled trials (RCTs) on digital health interventions for cardiovascular risk factors in middle-aged and elderly populations were included. RevMan 5.4 was used for Meta-analysis, with effect sizes expressed as mean difference (MD) or standardized mean difference (SMD) and 95% confidence interval (CI). Results: A total of 18 RCTs with 4892 participants were included. Meta-analysis showed that digital health interventions significantly reduced systolic blood pressure (MD = −2.66 mmHg, 95% CI: −3.81 to −1.52, P < 0.001), diastolic blood pressure (MD = −1.26 mmHg, 95% CI: −1.92 to −0.60, P < 0.001), LDL-C (SMD = −0.18, 95% CI: −0.29 to −0.07, P = 0.002), body weight (MD = −1.34 kg, 95% CI: −2.08 to −0.60, P < 0.001), and HbA1c (MD = −0.13%, 95% CI: −0.21% to −0.05%, P = 0.001), and increased physical activity levels (SMD = 0.24, 95% CI: 0.12 to 0.36, P < 0.001). Subgroup analyses showed that mHealth applications and short-term interventions (≤3 months) had better effects. Conclusion: Digital health interventions may have small-to-moderate short- to medium-term effects on improving cardiovascular risk factors in middle-aged and elderly populations, and may serve as a supplement to usual cardiovascular risk management. The applicability of these findings is mainly supported for settings with relatively well-developed healthcare services and digital technology infrastructure; long-term effects and impacts on hard cardiovascular outcomes require further confirmation.