PDF(Pubmed)
Abstract：
Chronic diseases contribute to 68% of global mortality, highlighting the importance of early detection and management of conditions such as metabolic syndrome. Effective lifestyle interventions, particularly through mobile health (mHealth), have shown potential in promoting health and reducing cardiometabolic risk. This study utilized mHealth data from public health centers in South Korea, targeting adults with risk factors for metabolic syndrome. The Intervention-Motivation-Behavioral skills (IMB) theoretical model was applied to categorize participants\' practice patterns over time using the Group-Based Trend Model (GBTM). And the Generalized Estimating Equations (GEE) methodology was applied to confirm the effective practice patterns for improving metabolic syndrome. Data were collected over 24 weeks. The dataset encompasses life-log data capable of capturing changes in intervention, self-report surveys, and clinical measurements, all linked to personal identification keys and thereby integrated. Participants demonstrated improved health behaviors, with the healthy eating score increasing from 5.0 to 6.4 and physical activity rates rising from 41.5% to 59%. Health risk factors decreased significantly, with the mean number of risk factors dropping from 2.4 to 1.4. The percentage of subjects with three or more metabolic syndrome components decreased from 42.3% in the initial period to 19.2% in the final period. Practice patterns by IMB components were classified into three categories: continuous type, late decline type, and early decline type. Improvements in health behavior and metabolic syndrome were observed in the continuous type of each IMB component. The mHealth interventions were confirmed to be positively associated with improved health behavior and management of metabolic syndrome in the continuous practice patterns of IMB.
摘要：
慢性病占全球死亡率的68%。强调早期发现和管理代谢综合征等疾病的重要性。有效的生活方式干预，特别是通过移动健康(mHealth)，已显示出促进健康和降低心脏代谢风险的潜力。这项研究利用了韩国公共卫生中心的mHealth数据，针对具有代谢综合征危险因素的成年人。干预-动机-行为技能（IMB）理论模型用于使用基于群体的趋势模型（GBTM）对参与者的实践模式进行分类。并应用广义估计方程（GEE）方法证实了改善代谢综合征的有效实践模式。在24周内收集数据。该数据集包含能够捕获干预变化的生活日志数据，自我报告调查，和临床测量，所有链接到个人识别键，从而集成。参与者表现出改善的健康行为，健康饮食评分从5.0分提高到6.4分，体力活动率从41.5%提高到59%。健康危险因素显著下降,风险因素的平均数量从2.4降至1.4。具有三种或更多种代谢综合征成分的受试者的百分比从最初阶段的42.3％下降到最后阶段的19.2％。按IMB组件划分的实践模式分为三类：连续型，晚期下降型，早期衰退型。在每种IMB组分的连续型中观察到健康行为和代谢综合征的改善。在IMB的持续实践模式中，mHealth干预措施被证实与改善健康行为和代谢综合征管理呈正相关。
