Association of baseline and cumulative cholesterol–high-density lipoprotein–glucose index with cardiometabolic multimorbidity: prospective evidence from two cohort studies
TL;DR
It is suggested that CHG, particularly its cumulative exposure, may serve as a potential marker of CMM risk and burden, however, further prospective validation is needed before CHG can be used for clinical risk prediction or to define decision thresholds.
Abstract
Cardiometabolic multimorbidity (CMM) is increasingly common and carries substantial clinical and public-health burden. The cholesterol-high-density lipoprotein-glucose (CHG) index has been linked to adverse cardiometabolic outcomes, but prospective evidence comparing baseline and cumulative exposure and testing external reproducibility under design-appropriate survey methods remains limited. We analyzed a baseline CHG cohort ( n = 7,077) and a cumulative-CHG subcohort ( n = 4,881) from the China Health and Retirement Longitudinal Study (CHARLS), and conducted a supportive external replication analysis in the National Health and Nutrition Examination Survey (NHANES; 1999–2018; n = 23,797). Cox models were used in CHARLS and fasting-subsample survey-weighted logistic models in NHANES. CHG and cumulative CHG were modeled per 1-standard deviation (SD) increment and by tertiles. Restricted cubic spline and threshold analyses characterized dose–response patterns. Sensitivity analyses included a stricter disease-free cumulative CHARLS cohort and additional hypertension adjustment in NHANES. Higher baseline CHG in CHARLS was associated with greater incident CMM risk (adjusted hazard ratio [HR] per 1-SD increase, 1.55; 95% CI, 1.39–1.73); participants in the highest tertile had higher risk than those in the lowest tertile (adjusted HR, 2.93; 95% CI, 2.15–4.00). Associations were stronger for cumulative CHG (adjusted HR per 1-SD increase, 1.75; 95% CI, 1.61–1.89; adjusted HR for T3 vs. T1, 5.46; 95% CI, 3.91–7.63). In weighted NHANES analyses, CHG remained positively associated with prevalent CMM (adjusted odds ratio per 1-SD increase, 1.91; 95% CI, 1.75–2.08; adjusted OR for T3 vs. T1, 3.58; 95% CI, 2.73–4.69). Baseline CHG in CHARLS showed a significant overall association without clear nonlinearity, whereas cumulative CHG in CHARLS and CHG in NHANES showed significant nonlinear patterns. Sensitivity analyses were directionally consistent with the main findings. Higher baseline and cumulative CHG were associated with greater incident CMM risk in the longitudinal CHARLS analyses, with larger effect estimates observed for cumulative CHG. A positive association was also observed between CHG and prevalent CMM in the cross-sectional NHANES analysis. These findings suggest that CHG, particularly its cumulative exposure, may serve as a potential marker of CMM risk and burden. However, further prospective validation is needed before CHG can be used for clinical risk prediction or to define decision thresholds.