Key result
Higher CTI linked to ~57% greater odds of cardiometabolic multimorbidity per SD.
Why the study?
Cardiometabolic multimorbidity poses a major public health challenge, but its associations with novel adiposity indices in Chinese adults needed investigation.
Cross-Sectional (n=10,383)
Yes
Odds Ratio: 1.57 (95% CI 1.49–1.65)
p-value: p=<0.001
Novel adiposity indices, particularly CTI, LAP, and AIP, are significantly associated with cardiometabolic multimorbidity in Chinese adults, though their discriminative ability as standalone screening tools remains modest.
CTI, LAP, and AIP were associated with cardiometabolic multimorbidity; hypothesis-generating and requires prospective validation before any clinical use.
Cardiometabolic multimorbidity (CMM) poses a major public health challenge. This study aimed to investigate the associations between seven novel adiposity indices and CMM prevalence in Chinese adults. In this cross-sectional analysis, we included 10,383 participants from the China Health and Retirement Longitudinal Study (CHARLS). CMM was defined as the presence of at least two of the following: hypertension, diabetes, coronary heart disease, or stroke. We assessed the Lipid Accumulation Product (LAP), Visceral Adiposity Index (VAI), Body Roundness Index (BRI), Atherogenic Index of Plasma (AIP), C-reactive protein triglyceride glucose index (CTI), Conicity Index (CI), and Residual Cholesterol (RC). Associations were examined using multivariable logistic regression and non-linear association analysis. All indices showed significant positive associations with CMM in the fully adjusted model. After standardization to a per-1-SD increase, CTI showed the strongest association (OR = 1.57, 95% CI: 1.49–1.65), followed by LAP (OR = 1.49) and AIP (OR = 1.44). Significant non-linear relationships with inflection points were identified for LAP, VAI, BRI, AIP, RC, and CI, whereas CTI showed a linear association. In an exploratory variance decomposition analysis, CTI accounted for 26.50% to 43.13% of the statistical variance shared among LAP, CI, BRI, and CMM. This estimate is purely descriptive of shared statistical variance and reflects only the associations observed in this cross-sectional sample. CTI and LAP showed the highest discriminative performance (AUC = 0.669 and 0.668, respectively), though still modest, and significantly outperformed most other indices (DeLong P < 0.01). All AUCs were below 0.70, suggesting limited utility as standalone screening tools. In this cross-sectional study, several novel adiposity indices—particularly CTI, LAP, and AIP—were significantly associated with prevalent CMM in Chinese adults, with evidence of non-linear relationships. In the variance decomposition analysis, CTI statistically accounted for a substantial portion of the shared variance between other adiposity indices and CMM. These findings are hypothesis-generating and do not support immediate clinical translation. They suggest that these indices may warrant further investigation in prospective cohorts to evaluate their predictive utility. However, they are purely associational findings, and validation in independent studies is required before any clinical use can be considered.
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Guo et al. (2026) conducted a cross-sectional in Cardiometabolic multimorbidity (CMM) (n=10,383). C-reactive protein triglyceride glucose index (CTI) vs. Per 1-SD increase was evaluated on Prevalence of cardiometabolic multimorbidity (CMM) (OR 1.57, 95% CI 1.49-1.65, p=<0.001). A per-1-SD increase in the C-reactive protein triglyceride glucose index (CTI) was significantly associated with higher odds of cardiometabolic multimorbidity (OR 1.57) in Chinese adults.