ArticleBMC endocrine disorders2026
The association between the glucose-lipid metabolism index and the cardiovascular disease prevalence of prediabetes and diabetes participants: evidence from NHANES 2001-2018.
Article in BMC endocrine disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Nonlinear associations between the cholesterol, high-density lipoprotein, and glucose index and type 2 diabetes risk in Chinese prediabetic adults: a cohort study.Scientific reports · 2026Article
- Sex differences in the predictive value of insulin resistance surrogate indicators for prediabetes among Chinese adults aged 18-45 years: a multicenter cohort study.Frontiers in endocrinology · 2026Article
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Abstract
backgroundInsulin resistance (IR) heightens the danger of cardiovascular diseases in the participants with diabetes mellitus (DM) and prediabetes mellitus(preDM). The glucose-lipid metabolism index (GLMI) has emerged as a potential biomarker for IR. The association between GLMI and cardiovascular diseases (CVD) risk in prediabetic and diabetic participants remains unidentified. The purpose of this study was to investigate the relationship between GLMI and CVD prevalence in participants with diabetes and prediabetes.
methodsUsing a cross-sectional design with retrospective analysis of prevalent CVD and follow-up for mortality, this investigation analyzed data from the National Health and Nutrition Examination Survey spanning from 2001 to 2018. The primary cross-sectional analysis included 15,037 eligible participants to assess the association between GLMI and prevalent CVD. The GLMI was calculated as follows: ln [Total triglycerides × Fasting plasma glucose ∕2] ×Body mass index × Total cholesterol ∕ High density lipoprotein cholesterol. CVD was defined as a composite endpoint including self-reported physician diagnosis of coronary heart disease, congestive heart failure, stroke, or angina. Multivariable survey-weighted logistic regression model was employed to assess the association between GLMI and CVD. Subgroup analyses were conducted to explore potential association factors. Multivariable survey-weighted logistic regression analysis was used to assess the association between GLMI and the CVD prevalence.
resultsComparing with control(n = 10152) and preDM(n = 949) participants, the DM participants (n = 3936) showed the higher GLMI level (all P < 0.001) and prevalence of CVD (all P < 0.001). Furthermore, in a fully adjusted survey-weighted model, we observed higher GLMI tertiles were associated with increased CVD prevalence in preDM and DM participants with the lowest GLMI tertile as reference (the middle tertile: 3.12 95% CI: 1.97–4.28; the highest tertile: 5.84,95% CI: 3.05–7.63; all P < 0.001). In addition, GLMI showed positive trends with severe CVD outcomes, including CVD subtypes and mortality. (All P for trend < 0.05). Meanwhile, GLMI demonstrated superior discriminative performance for identifying prevalent CVD compared to TyG index and TG/HDL ratio. Furthermore, the GLMI tertiles–CVD association was significantly stronger in participants with hypertension than in those without hypertension (P for interaction = 0.038). For each 1- standard deviation (SD) increase in GLMI, the CVD prevalence was increased by 23% (OR 1.23, 95% CI 1.09–1.40) after adjustment for confounders.
conclusionsGLMI showed a strong association with CVD and may be an important marker correlated with metabolic health and CVD burden. CLINICAL TRIAL NUMBER : Not applicable
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