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Background <p>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.</p> Methods <p>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.</p> Results <p>In the CHARLS prospective cohort, among 10,863 participants free of CMM at baseline, 1698 incident CMM cases (15.6%) occurred during approximately 9&#xa0;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.</p> Conclusions <p>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.</p>

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The association of C-reactive protein–triglyceride–glucose index with cardiometabolic multimorbidity in middle-aged and older adults: evidence from two cohort studies

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  • 发表日期：

    2026年2月13日

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  • Yiming Lin,
  • Juan Tao,
  • Haogeng Wang,
  • Hui Guan,
  • Xuhua Liu,
  • Xueyan Dong,
  • Wulin Gao

摘要

Background

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.

Methods

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.

Results

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.

Conclusions

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.