中老年人C-反应蛋白甘油三酯葡萄糖指数与心脏代谢多发病率的关系：来自两项队列研究的证据

摘要(中文译文)

心血管代谢多发病率（CMM）在中老年人中越来越常见，但仍然缺乏能够同时反映炎症和代谢负担的简单风险指标。C-反应蛋白甘油三酯葡萄糖指数（CTI）已被提出作为一种整合胰岛素抵抗和炎症状态的新型生物标志物。本研究旨在评估CTI及其累积暴露与CMM的关系。本研究使用中国健康与退休纵向研究（CHARLS）的2011年基线横断面数据和2011-2020年前瞻性随访数据进行了初步分析，并通过计算CHARLS内2011-2015年的累积CTI进行了纵向补充分析。使用英国老龄化纵向研究（ELSA）的2002-2012年队列进行了外部纵向验证，并使用美国国家健康与营养调查（NHANES）的2001-2010年数据进一步进行了跨人群横断面复制。采用多变量逻辑回归、Cox比例风险模型、Kaplan-Meier曲线和限制性三次样条分析来检验CTI与CMM患病率和事件风险的相关性，并在CHARLS中计算2011年至2015年的累积CTI以进行补充分析；同时，使用受试者操作特征（ROC）曲线来评估CTI对4年CMM发生的预测性能，并进行预先指定的亚组分析来检验发现的稳健性。在CHARLS前瞻性队列中，在10863名基线时没有CMM的参与者中，在大约9年的随访期间发生了1698例CMM病例（15.6%）。在主要模型中，基线CTI每增加1个单位，CMM的风险就会增加71%（HR = 1.71,CTI最高与最低四分位数的风险比为1.33（95%CI 0.94-1.88）；在2015年的基线亚短期中，累积CTI每增加1个单位，HR为1.02（95%CI 1.00-1.05）。CHARLS和NHANES的横断面分析均显示CTI和CMM患病率之间存在显著的正相关关系，并呈剂量反应关系。在将CTI添加到包含传统风险因素的模型中后，4年CMM预测的受试者工作特征曲线下面积（AUC）从0.753增加到0.778。在外部纵向验证中，纳入了来自ELSA队列的3129名参与者，其中406例CMM病例发生在随访期间（13.0%）。在主要模型中，CTI每增加1个单位，HR为1.59（95%CI 0.99-2.55），最高四分位数的参与者比最低四分位数（HR = 2.22,95%置信区间1.06-4.62），具有显著趋势检验（趋势P = 0.027),CTI及其累积暴露水平与CMM的患病率和发病风险密切相关，这些发现得到了独立纵向ELSA队列验证的进一步支持。CTI是从常规测量指标中得出的一个简单的综合指数，可以帮助识别CMM高危人群，并为中老年人群的早期风险分层和干预提供参考。

Abstract

Cardiometabolic multimorbidity (CMM) is increasingly common among middle-aged and older adults, but there remains a lack of simple risk indicators that can simultaneously reflect inflammatory and metabolic burden. The C-reactive protein-triglyceride-glucose index (CTI) has been proposed as a novel biomarker that integrates insulin resistance and inflammatory status. This study aimed to assess the association of CTI and its cumulative exposure with CMM. This study conducted the primary analyses using the 2011 baseline cross-sectional data and the 2011-2020 prospective follow-up data from the China Health and Retirement Longitudinal Study (CHARLS), and additionally performed longitudinal supplementary analyses by calculating cumulative CTI over 2011-2015 within CHARLS. An external longitudinal validation was conducted using the 2002-2012 cohort from the UK English Longitudinal Study of Ageing (ELSA), and cross-population cross-sectional replication was further performed using the 2001-2010 data from the US National Health and Nutrition Examination Survey (NHANES). Multivariable logistic regression, Cox proportional hazards models, Kaplan-Meier curves, and restricted cubic spline analyses were used to examine the associations of CTI with the prevalence and incident risk of CMM, and cumulative CTI from 2011 to 2015 was calculated in CHARLS for supplementary analyses; meanwhile, receiver operating characteristic (ROC) curves were used to evaluate the predictive performance of CTI for 4-year CMM occurrence, and prespecified subgroup analyses were conducted to test the robustness of the findings. In the CHARLS prospective cohort, among 10,863 participants free of CMM at baseline, 1698 incident CMM cases (15.6%) occurred during approximately 9 years of follow-up. In the primary model, each 1-unit increase in baseline CTI was associated with a 71% higher risk of CMM (HR = 1.71, 95% CI 1.39-2.11), and the hazard ratio comparing the highest with the lowest quartile of CTI was 1.33 (95% CI 0.94-1.88); in the 2015 baseline subcohort, each 1-unit increase in cumulative CTI was associated with an HR of 1.02 (95% CI 1.00-1.05). Cross-sectional analyses in CHARLS and NHANES both showed a significant positive association between CTI and CMM prevalence, with a dose-response relationship. After adding CTI to a model containing traditional risk factors, the area under the receiver operating characteristic curve (AUC) for 4-year CMM prediction increased from 0.753 to 0.778. In the external longitudinal validation, 3129 participants from the ELSA cohort were included, among whom 406 incident CMM cases occurred during follow-up (13.0%). In the primary model, each 1-unit increase in CTI was associated with an HR of 1.59 (95% CI 0.99-2.55), and participants in the highest quartile had a higher risk than those in the lowest quartile (HR = 2.22, 95% CI 1.06-4.62), with a significant trend test (P for trend = 0.027), indicating that the direction of the association was consistent with that observed in CHARLS. CTI and its cumulative exposure level are closely associated with both the prevalence and incidence risk of CMM, and these findings were further supported by validation in the independent longitudinal ELSA cohort. As a simple composite index derived from routinely measured indicators, CTI may help identify individuals at high risk of CMM and provide a reference for early risk stratification and intervention in middle-aged and older populations.

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