Associations of the hs-CRP/HDL-C ratio with cardiovascular metabolic multimorbidity: a large cross-sectional study

Globally, cardiovascular metabolic multimorbidity (CMM) is an import contributor to both illness burden and mortality. Identifying reliable biomarkers to facilitate early prevention is of significant clinical importance. 8665 subjects were eligible in the survey. Multiple logistic regression models were employed to assess the association between the hs-CRP/HDL-C ratio and the likelihood of developing CMM. An analysis of mediation was employed to assess the effect of glycated hemoglobin A1c (HbA1c) on the relationship between the two. The CMM group had greater levels of white blood cells, platelets, total cholesterol, uric acid, HbA1c, hs-CRP, and hs-CRP/HDL-C ratio, alongside reduced levels of HDL-C (P < 0.001). After adjusting covariates, each one-unit increase in hs-CRP/HDL-C was related to a 138.3% increase in the risk of CMM (OR = 2.383, 95% CI: 1.744-3.256, P < 0.001). Participants in the highest quartile group were at the highest risk of CMM events as compared to those in the lowest quartile group (OR = 3.414, 95% CI: 2.830-4.119, P < 0.001). Approximately 54.79% of the relationship between hs-CRP/HDL-C and CMM is mediated through HbA1c. The greater hs-CRP/HDL-C levels are independent risk factors for CMM, and HbA1c partially mediated the association. These findings suggest that improving inflammation, lipid, and glucose levels may help reduce the risk of CMM.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-03-13
DOI
https://doi.org/10.1038/s41598-026-43849-2
Primary Topic
Diabetes, Cardiovascular Risks, and Lipoproteins
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Associations of the hs-CRP/HDL-C ratio with cardiovascular metabolic multimorbidity: a large cross-sectional study

Xiaojun Cai, Wei Wu, Tianwei Meng, B Z Chen et al.
Scientific Reports
Diabetes, Cardiovascular Risks, and Lipoproteins
article

Associations of the hs-CRP/HDL-C ratio with cardiovascular metabolic multimorbidity: a large cross-sectional study

Xiaojun Cai, Wei Wu, Tianwei Meng, B Z Chen, Baochun Luo, Lichao Han, Rui Wang, Yijia Ma
article en

Abstract

Globally, cardiovascular metabolic multimorbidity (CMM) is an import contributor to both illness burden and mortality. Identifying reliable biomarkers to facilitate early prevention is of significant clinical importance. 8665 subjects were eligible in the survey. Multiple logistic regression models were employed to assess the association between the hs-CRP/HDL-C ratio and the likelihood of developing CMM. An analysis of mediation was employed to assess the effect of glycated hemoglobin A1c (HbA1c) on the relationship between the two. The CMM group had greater levels of white blood cells, platelets, total cholesterol, uric acid, HbA1c, hs-CRP, and hs-CRP/HDL-C ratio, alongside reduced levels of HDL-C (P < 0.001). After adjusting covariates, each one-unit increase in hs-CRP/HDL-C was related to a 138.3% increase in the risk of CMM (OR = 2.383, 95% CI: 1.744-3.256, P < 0.001). Participants in the highest quartile group were at the highest risk of CMM events as compared to those in the lowest quartile group (OR = 3.414, 95% CI: 2.830-4.119, P < 0.001). Approximately 54.79% of the relationship between hs-CRP/HDL-C and CMM is mediated through HbA1c. The greater hs-CRP/HDL-C levels are independent risk factors for CMM, and HbA1c partially mediated the association. These findings suggest that improving inflammation, lipid, and glucose levels may help reduce the risk of CMM.

Scientific Reports
Heilongjiang University of Chinese Medicine (CN), Heilongjiang Provincial Hospital (CN)
Good health and well-being
Openalex Percentile: Top 25%
Diabetes, Cardiovascular Risks, and Lipoproteins
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.