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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

Wei Guo, Yuan Wang, Yanqiu Huang, Liwei Zhang et al.

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