Dynamic Co-Evolution of Obesity-Metabolic-Inflammatory for Cardiovascular Disease Risk Stratification in Middle-Aged and Older Adults: A Data-Driven Joint Trajectory Analysis

IF 2.8 3区医学 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS

Clinical Cardiology Pub Date : 2026-07-29 DOI:10.1002/clc.70429

Qinggao Wang, Yilu Lei, Qingfeng Zhou, Yan Long, Yinjuan Lai

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引用次数: 0

Abstract

Background

Cardiovascular disease (CVD) risk assessment based on single-time-point measurements may inadequately capture the dynamic interplay of obesity, metabolic dysfunction, and chronic inflammation. Understanding their long-term co-evolution may improve CVD risk stratification.

Methods

We conducted a prospective cohort study using data from the China Health and Retirement Longitudinal Study. Participants aged ≥ 45 years with repeated measurements of body mass index (BMI), triglyceride-glucose (TyG) index, and high-sensitivity C-reactive protein (hsCRP) between 2011 and 2015 were included. Joint trajectories of these obesity-metabolic-inflammatory markers were identified using the KmL3D clustering algorithm. Incident CVD (heart disease or stroke) was ascertained during follow-up from 2015 to 2020. Cox proportional hazards models were applied to evaluate associations between trajectory groups and CVD risk after adjustment for demographic, lifestyle, and clinical covariates.

Results

Among 4483 participants (mean age 57.8 years; 52.6% women), four distinct joint trajectory patterns were identified: a sustained low-risk profile (46.8%), an obesity-predominant profile (26.7%), a metabolic–obesity-driven profile (17.1%), and an inflammation-dominant profile (9.4%). During a median follow-up of 5.0 years, 592 incident CVD events occurred. Compared with the low-risk profile, all adverse trajectory groups were associated with significantly higher CVD risk, with hazard ratios ranging from 1.35 to 1.46 after full adjustment. Associations were more pronounced for stroke, particularly among individuals with a metabolic–obesity-driven trajectory. Findings were robust across sensitivity analyses.

Conclusions

Distinct dynamic co-evolution patterns of obesity, metabolic dysfunction, and inflammation identify population subgroups with substantially different risks of incident CVD.

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肥胖-代谢-炎症对中老年人心血管疾病风险分层的动态共同进化：数据驱动的联合轨迹分析

背景：基于单时间点测量的心血管疾病（CVD）风险评估可能无法充分捕捉肥胖、代谢功能障碍和慢性炎症之间的动态相互作用。了解它们的长期共同进化可能会改善心血管疾病的风险分层。方法：我们使用中国健康与退休纵向研究的数据进行前瞻性队列研究。年龄≥45岁的参与者在2011年至2015年期间反复测量体重指数（BMI）、甘油三酯-葡萄糖（TyG）指数和高敏c反应蛋白（hsCRP）。使用KmL3D聚类算法确定了这些肥胖-代谢-炎症标志物的联合轨迹。在2015年至2020年的随访期间确定了CVD（心脏病或中风）的发生率。在调整了人口统计学、生活方式和临床协变量后，应用Cox比例风险模型来评估轨迹组与CVD风险之间的关联。结果：在4483名参与者（平均年龄57.8岁，52.6%为女性）中，确定了四种不同的关节轨迹模式：持续低风险（46.8%），肥胖主导（26.7%），代谢肥胖驱动（17.1%）和炎症主导（9.4%）。在中位随访5.0年期间，发生了592例CVD事件。与低风险组相比，所有不良轨迹组的CVD风险均显著升高，完全调整后的风险比为1.35 ~ 1.46。与中风的关联更为明显，尤其是在代谢肥胖驱动的个体中。敏感性分析的结果是稳健的。结论：肥胖、代谢功能障碍和炎症的不同动态共同进化模式确定了具有显著不同心血管疾病发生风险的人群亚群。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinical Cardiology 医学-心血管系统

CiteScore

5.10

自引率

3.70%

发文量

189

审稿时长

4-8 weeks

期刊介绍： Clinical Cardiology provides a fully Gold Open Access forum for the publication of original clinical research, as well as brief reviews of diagnostic and therapeutic issues in cardiovascular medicine and cardiovascular surgery. The journal includes Clinical Investigations, Reviews, free standing editorials and commentaries, and bonus online-only content. The journal also publishes supplements, Expert Panel Discussions, sponsored clinical Reviews, Trial Designs, and Quality and Outcomes.