Association between the C-reactive protein–triglyceride–glucose Index and risks of all-cause and cardiovascular mortality in USA adults: a prospective cohort study

INTRODUCTION: The C-reactive protein-triglyceride-glucose index (CTI) is an emerging composite biomarker reflecting insulin resistanceand systemic inflammation. Research regarding the relationship between CTI and risks of all-cause and cardiovascular mortality remainslimited and inconsistent. MATERIAL AND METHODS: Data from 9,264 USA adults aged ≥ 20 years were obtained from the National Health and Nutrition Examination Survey (1999-2010). Mortality status was determined through linkage to the National Death Index through 31 December 2019. Hazardratios (HRs) for all-cause and cardiovascular mortality were estimated using weighted Kaplan-Meier methods, restricted cubic spline(RCS) models, and multivariable Cox proportional hazards regression models. Prespecified subgroup analyses and sensitivity analyseswere conducted to assess the robustness of the findings. RESULTS: Over a median follow-up of 12.8 years, 2,644 deaths occurred, including 2,009 attributable to all causes and 635 to cardiovascular causes. After adjustment for potential confounders, each one-unit increment in CTI was associated with a 26% higher risk of all-causemortality [HR, 1.26; 95% confidence interval (CI), 1.15-1.38; p < 0.001) and a 25% higher risk of cardiovascular mortality (HR, 1.25; 95% CI,1.03-1.51; p = 0.021). Participants in the highest CTI quartile demonstrated a 33% higher risk of all-cause mortality compared with thosein the lowest quartile (HR, 1.33; 95% CI, 1.07-1.64; p = 0.010). RCS analyses indicated a nonlinear association between CTI and all-causemortality (p for nonlinearity = 0.018), with an inflection point at a CTI value of 9.25, whereas a linear association was observed for cardiovascular mortality (p for nonlinearity = 0.072). No statistically significant interactions were identified across prespecified subgroups. The results remained consistent after exclusion of early deaths (≤ 2 years) and after exclusion of participants with neoplasms. CONCLUSIONS: Higher CTI levels were independently associated with increased risks of all-cause and cardiovascular mortality among USA adults. These findings suggest that CTI may serve as a clinically relevant biomarker for early identification of individuals at elevated mortality risk, with potential implications for risk stratification, targeted prevention strategies, and healthcare resource allocation.

Authors

Institutions

Publication Details

Journal
Endokrynologia Polska
Published
2026-07-17
DOI
https://doi.org/10.5603/ep.111545
Primary Topic
Adipokines, Inflammation, and Metabolic Diseases
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Association between the C-reactive protein–triglyceride–glucose Index and risks of all-cause and cardiovascular mortality in USA adults: a prospective cohort study

Qinghua Han, Li Li, Xia Jing, Chunxia Li et al.
Endokrynologia Polska
Adipokines, Inflammation, and Metabolic Diseases
article

Association between the C-reactive protein–triglyceride–glucose Index and risks of all-cause and cardiovascular mortality in USA adults: a prospective cohort study

Qinghua Han, Li Li, Xia Jing, Chunxia Li, Lisha Guo
article en

Abstract

INTRODUCTION: The C-reactive protein-triglyceride-glucose index (CTI) is an emerging composite biomarker reflecting insulin resistanceand systemic inflammation. Research regarding the relationship between CTI and risks of all-cause and cardiovascular mortality remainslimited and inconsistent. MATERIAL AND METHODS: Data from 9,264 USA adults aged ≥ 20 years were obtained from the National Health and Nutrition Examination Survey (1999-2010). Mortality status was determined through linkage to the National Death Index through 31 December 2019. Hazardratios (HRs) for all-cause and cardiovascular mortality were estimated using weighted Kaplan-Meier methods, restricted cubic spline(RCS) models, and multivariable Cox proportional hazards regression models. Prespecified subgroup analyses and sensitivity analyseswere conducted to assess the robustness of the findings. RESULTS: Over a median follow-up of 12.8 years, 2,644 deaths occurred, including 2,009 attributable to all causes and 635 to cardiovascular causes. After adjustment for potential confounders, each one-unit increment in CTI was associated with a 26% higher risk of all-causemortality [HR, 1.26; 95% confidence interval (CI), 1.15-1.38; p < 0.001) and a 25% higher risk of cardiovascular mortality (HR, 1.25; 95% CI,1.03-1.51; p = 0.021). Participants in the highest CTI quartile demonstrated a 33% higher risk of all-cause mortality compared with thosein the lowest quartile (HR, 1.33; 95% CI, 1.07-1.64; p = 0.010). RCS analyses indicated a nonlinear association between CTI and all-causemortality (p for nonlinearity = 0.018), with an inflection point at a CTI value of 9.25, whereas a linear association was observed for cardiovascular mortality (p for nonlinearity = 0.072). No statistically significant interactions were identified across prespecified subgroups. The results remained consistent after exclusion of early deaths (≤ 2 years) and after exclusion of participants with neoplasms. CONCLUSIONS: Higher CTI levels were independently associated with increased risks of all-cause and cardiovascular mortality among USA adults. These findings suggest that CTI may serve as a clinically relevant biomarker for early identification of individuals at elevated mortality risk, with potential implications for risk stratification, targeted prevention strategies, and healthcare resource allocation.

Endokrynologia Polska
Shanxi Medical University (CN), First Hospital of Shanxi Medical University (CN), Hypertension Institute (US), Shanxi Academy of Medical Sciences (CN), Taiyuan University of Technology (CN)
Chinese People’s Liberation Army, Shanxi Provincial Key Research and Development Project
Good health and well-being
Openalex Percentile: Top 8%
Adipokines, Inflammation, and Metabolic Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.