ArticleFrontiers in public health2026
Independent association of the CHG index with cardiometabolic multimorbidity: real-world evidence from community and clinical datasets.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Cardiometabolic multimorbidity (CMM) is an increasing public health challenge in aging populations. The cholesterol-high-density lipoprotein-glucose (CHG) index is an emerging metabolic marker, but its association with prevalent CMM has not been sufficiently evaluated across community and hospitalized populations. This study examined the association between CHG and CMM using clinical and China Health and Retirement Longitudinal Study (CHARLS) data. Methods: This cross-sectional study included 5,544 hospitalized patients from the First Affiliated Hospital of Xinjiang Medical University and 11,221 community-dwelling participants from CHARLS. CMM was defined as the presence of at least two of heart disease, stroke, and diabetes mellitus. Multivariable logistic regression was used to assess associations between CHG and CMM after adjustment for demographic, lifestyle, and clinical factors. Restricted cubic spline analyses assessed nonlinearity, while receiver operating characteristic curves evaluated discriminative performance. Subgroup and sensitivity analyses were also performed. Results: Each SD increase in CHG was associated with higher odds of prevalent CMM in both the clinical dataset (OR = 1.96, 95% CI: 1.74-2.21) and CHARLS (OR = 4.14, 95% CI: 3.46-4.94). Significant J-shaped nonlinear associations were observed in both datasets. Adding CHG to the basic model improved discrimination, with AUCs of 0.690 and 0.834 in the clinical and CHARLS datasets, respectively. A nominal smoking interaction in the clinical dataset ( Conclusion: Higher CHG was independently associated with prevalent CMM in hospitalized and community-dwelling middle-aged and older Chinese adults. Nonlinear associations were observed in both datasets, and no subgroup interaction remained significant after multiple-testing correction. CHG may provide a simple, accessible indicator of cardiometabolic burden, with potential value for risk stratification and population-level identification of individuals with greater cardiometabolic disease burden. Derived from routinely available laboratory measures, CHG may complement established cardiometabolic assessment and support population health and integrated chronic disease management in aging populations.
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