Predictive value of the combined cholesterol, high-density lipoprotein, glucose and frailty indices for cardiometabolic multimorbidity incidence: evidence from a national prospective cohort study

医学 前瞻性队列研究 内科学 糖尿病 比例危险模型 接收机工作特性 队列研究 血管病学 回顾性队列研究 队列 试验预测值 冲程(发动机) 代谢综合征 急诊医学 预测值 心力衰竭 疾病 纵向研究 英国前瞻性糖尿病研究 心脏病学 混淆 流行病学 2型糖尿病 物理疗法 体质指数 危险系数 空腹血糖值 曲线下面积
作者
Huanqiong Fan,Guosong Jiang,Jun Cheng,Hengfa Chen
出处
期刊:Cardiovascular Diabetology [BioMed Central]
标识
DOI:10.1186/s12933-026-03213-0
摘要

BACKGROUND: The cholesterol, high-density lipoprotein, and glucose (CHG) is a surrogate of insulin resistance, while frailty reflects cumulative physiological decline, yet their combined utility for cardiometabolic multimorbidity (CMM) is underexplored. We evaluated a combined CHG-frailty index (CHG-FI) for incident heart disease, stroke, diabetes, and CMM. METHODS: We conducted a retrospective cohort study of 6812 Chinese adults aged ≥ 45 years enrolled in the 2011-2020 waves of the China Health and Retirement Longitudinal Study (CHARLS). Participants with baseline lipid and fasting glucose measurements were included and followed prospectively for incident heart disease, stroke, diabetes, and cardiometabolic multimorbidity (≥ 2 conditions). FI was calculated using the cumulative deficit approach, and CHG was incorporated according to established procedures. Multivariable Cox regression estimated associations; CHG-FI interaction was assessed on multiplicative and additive scales. Incremental predictive utility of CHG, FI, TYG‑FI, and CHG‑FI was compared using receiver operating characteristic (ROC) curves, net reclassification improvement (NRI), and decision curve analysis (DCA). Stratified and sensitivity analyses evaluated robustness. RESULTS: Over a median follow‑up of 9.0 years, we observed 1,304 heart disease events, 554 strokes, 932 diabetes cases, and 467 CMM cases. Each 1-unit increase in CHG-FI was associated with higher risk: heart disease (HR 1.34, 95% CI 1.23-1.45), stroke (HR 1.85, 95% CI 1.65-2.06), diabetes (HR 1.29, 95% CI 1.17-1.42), and CMM (HR 1.79, 95% CI 1.58-2.04). Associations showed dose-response patterns and nonlinearity. The multiplicative interaction between CHG and FI for CMM was 0.54 (95% CI 0.35-0.83), reflecting a "risk saturation" or ceiling effect. Despite this, the combined CHG -FI index offered superior predictive performance for CMM relative to individual components: AUC 0.652 (95% CI 0.627-0.678), with significant improvement in reclassification (NRI 0.329, 95% CI 0.236-0.423) and discrimination (IDI 0.011, 95% CI 0.008-0.015). CHG -FI and TyG -FI showed broadly comparable performance across outcomes. CONCLUSION: The combined CHG-frailty index was significantly associated with incident cardiometabolic multimorbidity and its individual components, demonstrating predictive performance comparable to established combined indices. As an accessible tool integrating routine metabolic and physiologic reserve measures, CHG-FI offers a practical alternative approach for risk stratification.
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