Composite C-reactive protein-triglyceride-glucose adiposity indices and incident cardiovascular-liver-metabolic multimorbidity: a prospective cohort study.

During approximately four years of follow-up, 6.2% of participants met criteria for the surrogate-defined cardiovascular-liver-metabolic multimorbidity (CLMM) phenotype.

• 406 out of 6,534 participants met the surrogate-defined CLMM criteria
• The study drew from the China Health and Retirement Longitudinal Study (CHARLS)
• All participants had full baseline records
• CLMM was operationalized as a surrogate-defined composite phenotype rather than clinically confirmed CLMM, due to heterogeneous ascertainment methods across component conditions

CTI-BMI and CTI-CVAI showed the strongest associations with the surrogate-defined CLMM phenotype in fully adjusted models.

• CTI-BMI Q4 odds ratio (OR) = 3.46 (P < 0.001)
• CTI-CVAI Q4 OR = 2.37 (P < 0.001)
• Both associations remained statistically significant after full covariate adjustment
• Most other CTI-derived adiposity indicators were also significantly associated with elevated odds of the phenotype

CTI-ABSI and CTI-WWI were not independently associated with the surrogate-defined CLMM phenotype after full adjustment.

• Of the nine CTI-derived adiposity indices evaluated, CTI-ABSI and CTI-WWI showed null associations after full covariate adjustment
• The nine indices included: CTI, CTI-BMI, CTI-WC, CTI-WHtR, CTI-BRI, CTI-WWI, CTI-CVAI, CTI-ABSI, and CTI-CI
• All other indices remained significantly associated after full adjustment

Restricted cubic spline analyses revealed significant nonlinear exposure-response relationships for all CTI-derived indices except CTI itself.

• RCS modeling was used to examine potential nonlinear relationships between each index and the CLMM phenotype
• All indices except CTI demonstrated statistically significant nonlinear relationships
• Two-piece segmented regression analyses were also performed to further characterize these nonlinear patterns

CTI-BMI had the highest AUC among evaluated CTI-derived indices but did not materially outperform BMI alone.

• CTI-BMI AUC = 0.638 (95% CI 0.611–0.664)
• BMI alone AUC = 0.638; DeLong P = 0.924 for comparison with CTI-BMI
• IDI for CTI-BMI versus BMI was only 0.02%
• NRI was positive despite the negligible IDI improvement

Adding CTI-BMI to the fully adjusted baseline model produced only a minimal improvement in discrimination.

• AUC increased from 0.617 to 0.627 when CTI-BMI was added to the fully adjusted baseline model
• NRI = 28.63% (95% CI 18.63–38.64%), suggesting improved reclassification
• IDI = 0.03% (95% CI 0.01–0.06%), indicating minimal improvement in average discrimination
• The authors characterize the absolute discriminatory ability of CTI-BMI as 'modest'

Participants with low CTI and high BMI had similarly elevated odds of the surrogate-defined CLMM phenotype as those with both high CTI and high BMI, compared to those with low CTI and low BMI.

• Low CTI and high BMI: OR = 2.49 (95% CI 1.80–3.48)
• High CTI and high BMI: OR = 2.53 (95% CI 1.87–3.45)
• The two effect estimates were numerically similar
• No statistically significant multiplicative or additive interaction was observed between CTI and BMI

Significant effect modification of the CTI-BMI and surrogate-defined CLMM phenotype association was observed by sex, smoking status, and drinking status.

• Stronger associations were identified in men, current smokers, and current drinkers
• All interaction P-values < 0.001
• Subgroup and sensitivity analyses were performed to assess stability of findings

Sensitivity analyses showed CTI-BMI remained significantly associated with the surrogate-defined phenotype after additional adjustment for baseline CLM component status, though with a reduced effect estimate.

• Findings were 'generally directionally consistent' across sensitivity analyses
• Additional adjustment for baseline CLM component status attenuated but did not eliminate the association
• The reduction in effect estimate after this adjustment was noted by the authors

The CLMM phenotype in this study was operationalized as a surrogate-defined composite, with CVD ascertained from self-report and MASLD inferred from the lipid accumulation product rather than imaging or clinical adjudication.

• CVD was identified primarily from self-reported physician diagnoses
• MASLD was inferred using the lipid accumulation product (LAP) rather than imaging, histology, or clinical adjudication
• Because component conditions were ascertained using different methods and levels of diagnostic accuracy, the authors caution that findings 'should not be interpreted as estimates of the risk of clinically confirmed CLMM'
• The authors explicitly acknowledge potential misclassification of component conditions