Lipids in Health and Disease· 2026Q1
Dynamic associations of the cholesterol, high-density lipoprotein, and glucose index and its obesity-related indices with the incidence and progression of cardiometabolic multimorbidity: evidence from the CHARLS and ELSA cohorts
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- Q1SCImago
- 2026year
Short summary
Cumulative exposure to cholesterol, HDL, and glucose (CHG) indices, particularly those combined with central obesity measures (CuCHG-WHtR, CuCHG-WC), showed stronger associations with incident cardiometabolic multimorbidity (CMM) (HR=1.68 and 1.65, respectively) than baseline measures. Another index, CuCHG-CVAI, was linked to higher progression risks (32-39%).
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Key points
- Cumulative exposure to CHG indices combined with central obesity measures (CuCHG-WHtR, CuCHG-WC) were strongly associated with incident CMM (HR=1.68, 1.65).
- CuCHG-CVAI showed a prominent association with CMM progression, increasing transition risks by 32% (no to first CVD) and 39% (first CVD to CMM).
- Findings were consistent across the CHARLS (n=5,355) and ELSA (n=2,096) cohorts.
- A risk prediction model using CHG-WHtR achieved good predictive capacity for incident CMM with a 5-year AUC of 0.811.
AI-generated from the title and abstract; the full text is not read.
Abstract
Cardiometabolic multimorbidity (CMM) is a major global public health challenge associated with metabolic dysregulation and obesity. Cholesterol, high-density lipoprotein cholesterol, and glucose (CHG) is an emerging metabolic risk index; however, the associations of CHG combined with obesity-related indices with the incidence and progression of CMM remain unclear. This study aimed to assess these associations and compare the predictive performance of eight CHG-related indices. This study included participants from the China Health and Retirement Longitudinal Study (CHARLS, 2011–2020; n = 5,355) and the English Longitudinal Study of Ageing (ELSA, 2008–2018; n = 2,096). Cumulative exposure and longitudinal exposure patterns of CHG-related indices were derived from repeated measurements. Cox regression models, multi-state Markov models, and time-dependent Receiver Operating Characteristic (ROC) curve analyses were used to assess associations and discrimination, with cross-cohort replication in ELSA. Exploratory pathway analyses were used to evaluate the potential roles of blood pressure and glucose-lipid metabolism in CMM progression. An RSF model was further developed using the CHG-related index to predict CMM risk. During a median follow-up of 5.0 and 6.0 years in the CHARLS and ELSA cohorts, respectively, 433 (8.09%) and 85 (4.06%) incident CMM cases occurred. All CHG-related indices were associated with CMM onset and progression, with cumulative exposure and exposure patterns yielding higher HRs compared to baseline measures. Among them, CuCHG-WHtR (HR = 1.68, 95% CI: 1.52–1.85) and CuCHG-WC (HR = 1.65, 95% CI: 1.49–1.81) showed stronger associations with incident CMM. CuCHG-CVAI showed a relatively prominent association with progression, with 32% and 39% higher transition risks from no cardiometabolic disease (NCMD) to first cardiometabolic disease (FCMD) and from FCMD to CMM, respectively. Findings were replicated in ELSA. Exploratory pathway analyses showed stage-specific metabolic pathways, with glycated hemoglobin and blood pressure mainly involved in early progression and dyslipidemia in advanced progression. For the RSF model incorporating CHG-WHtR, the 5-year AUC for predicting incident CMM was 0.811 (95% CI: 0.806–0.816), indicating good predictive capacity. All eight cumulative CHG-related indices were positively associated with both incident CMM and its progression, and cumulative CHG-related central obesity indices (CuCHG-WHtR and CuCHG-WC) and CuCHG-CVAI may serve as valuable indicators of incident CMM and CMM progression, respectively. Dynamic metabolic assessment may facilitate risk stratification, and stage-specific metabolic contributions may support tailored prevention strategies during CMM progression.
The authors' abstract, as published at the source. Lipids in Health and Disease, 2026 · DOI ↗
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Field: Endocrinology, Diabetes and Metabolism
Endocrinology, Diabetes and MetabolismMedicine