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甘油三酯葡萄糖-腰围身高比指数与中国中老年人心血管代谢多种合并症之间的关联:一项全国性前瞻性队列研究

The association between triglyceride glucose-waist height ratio index and cardiometabolic multimorbidity among Chinese middle-aged and older adults: a national prospective cohort study.

作者信息

Lv Longyan, Zhang Ping, Chen Xuerui, Gao Yan

机构信息

First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province 250355, China.

Department of General Medicine, the 960th Hospital of People's Liberation Army Joint Logistics Support Force, NO.25 Shifan Road, Jinan, Shandong 250031, People's Republic of China.

出版信息

Cardiovasc Diabetol. 2025 Sep 2;24(1):358. doi: 10.1186/s12933-025-02919-x.

DOI:10.1186/s12933-025-02919-x
PMID:40898229
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12406543/
Abstract

BACKGROUND

Cardiometabolic multimorbidity (CMM) imposes a progressively severe health burden worldwide. Triglyceride-glucose (TyG) index and waist-to-height ratio (WHtR), as indicators of insulin resistance and central adiposity, respectively, have been shown to be strongly associated with CMM. However, there is currently a lack of research combining the two for CMM risk assessment. This study aims to investigate the relationship between TyG-WHtR index and CMM.

METHODS

This prospective cohort study analyzed data from Chinese adults aged ≥ 45 years participating in the 2011-2020 waves of the China Health and Retirement Longitudinal Study (CHARLS). We employed the Kaplan-Meier curves, multivariable Cox regression analysis, and restricted cubic spline (RCS) to examine the relationship between the TyG-WHtR index and the risk of CMM. Time-dependent receiver operating characteristic (ROC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) analyses were utilized to evaluate predictive performance. Additionally, subgroup analyses and sensitivity tests were conducted to assess the robustness of the findings.

RESULTS

During a median follow-up of 9 years, 413 (9.4%) of the 4393 participants developed CMM. Multivariable Cox regression analysis revealed progressively higher risks of CMM across increasing TyG-WHtR quartiles. Compared to participants in the lowest quartile (Q1) of the TyG-WHtR index, the hazard ratios (HRs) and 95% confidence intervals (CIs) for those in quartiles Q2, Q3, and Q4 were 1.75 (1.18-2.6), 2.33 (1.58-3.43), and 3.13 (2.08-4.7), respectively. Consistently, elevated cumulative TyG-WHtR independently increased CMM risk. The RCS analysis indicated a positive linear relationship between the TyG-WHtR index and the incidence of CMM. Moreover, both baseline and cumulative TyG-WHtR significantly improved reclassification metrics (NRI/IDI) and discriminative ability (AUC). Sensitivity analyses corroborated these primary findings.

CONCLUSION

This study suggests that TyG-WHtR independently predicts CMM risk. The linear dose-response relationship highlight the potential utility of TyG-WHtR in early risk assessment and prevention strategies for CMM.

摘要

背景

心脏代谢合并症(CMM)在全球范围内造成的健康负担日益严重。甘油三酯-葡萄糖(TyG)指数和腰高比(WHtR)分别作为胰岛素抵抗和中心性肥胖的指标,已被证明与CMM密切相关。然而,目前缺乏将两者结合用于CMM风险评估的研究。本研究旨在探讨TyG-WHtR指数与CMM之间的关系。

方法

这项前瞻性队列研究分析了参加2011-2020年中国健康与养老追踪调查(CHARLS)的45岁及以上中国成年人的数据。我们采用Kaplan-Meier曲线、多变量Cox回归分析和限制性立方样条(RCS)来检验TyG-WHtR指数与CMM风险之间的关系。利用时间依赖性受试者工作特征(ROC)、净重新分类改善(NRI)和综合判别改善(IDI)分析来评估预测性能。此外,进行了亚组分析和敏感性测试以评估研究结果的稳健性。

结果

在中位随访9年期间,4393名参与者中有413名(9.4%)发生了CMM。多变量Cox回归分析显示,随着TyG-WHtR四分位数的增加,CMM风险逐渐升高。与TyG-WHtR指数最低四分位数(Q1)的参与者相比,四分位数Q2、Q3和Q4参与者的风险比(HR)和95%置信区间(CI)分别为1.75(1.18-2.6)、2.33(1.58-3.43)和3.13(2.08-4.7)。同样,累积TyG-WHtR升高独立增加CMM风险。RCS分析表明TyG-WHtR指数与CMM发病率之间存在正线性关系。此外,基线和累积TyG-WHtR均显著改善了重新分类指标(NRI/IDI)和判别能力(AUC)。敏感性分析证实了这些主要发现。

结论

本研究表明TyG-WHtR独立预测CMM风险。线性剂量反应关系突出了TyG-WHtR在CMM早期风险评估和预防策略中的潜在效用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c6e/12406543/cd72d2ed050b/12933_2025_2919_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c6e/12406543/a6c16813f426/12933_2025_2919_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c6e/12406543/cd72d2ed050b/12933_2025_2919_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c6e/12406543/a6c16813f426/12933_2025_2919_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c6e/12406543/6c4450869eaf/12933_2025_2919_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c6e/12406543/b46468bb0352/12933_2025_2919_Fig3_HTML.jpg
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