ArticleBMC geriatrics2026
Serum uric acid-to-HDL-C ratio as an independent predictor of metabolic syndrome in the elderly: diagnostic model optimization and inflammatory mechanism insights.
Article in BMC geriatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Uric Acid-to-HDL Cholesterol Ratio Is Associated with Prediabetes and an Adverse Metabolic Profile: Results from the Genetics of Atherosclerotic Disease (GEA) Study.Diagnostics (Basel, Switzerland) · 2026Article
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8 authors.
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Abstract
objectiveThis study aimed to investigate the independent predictive value of the uric acid-to-HDL-C ratio (UHR) for metabolic syndrome (MS) in the elderly, develop an optimized diagnostic model, and assess whether UHR dynamics reflect inflammatory improvements.
methodsA prospective cohort study was conducted including elderly individuals (n = 1064) undergoing health examinations at two hospitals in 2023. MS was diagnosed according to the International Diabetes Federation (IDF, 2005) criteria (central obesity: waist circumference ≥ 90 cm in men, ≥ 80 cm in women). The association between UHR and MS was evaluated using multivariable logistic regression. Predictive performance was assessed by receiver operating characteristic (ROC) analysis, with the optimal cut-off determined by the Youden index. Model robustness was tested by 1000 bootstrap resamplings and net reclassification improvement (NRI)/integrated discrimination improvement (IDI) analyses. Additional analyses included age- and sex-stratified inflammatory profiling (NLRP3, GDF15, SOD) and a quasi-experimental intervention study in participants with UHR ≥ 14.9% (n = 102), who received a 12-week low-purine diet plus daily exercise.
resultsUHR was identified as an independent risk factor for MS (OR = 1.96, 95% CI: 1.52–2.53, P < 0.001). It also showed significant correlations with key MS components, including waist circumference (r = 0.394) and triglycerides (r = 0.212; both P < 0.001). The AUC of UHR for predicting MS was 0.782 (95% CI: 0.745–0.819), with an optimal cut-off value of 14.9% (sensitivity 75.6%, specificity 72.8%). Incorporating UHR into the Framingham risk model improved the AUC to 0.824 (NRI = 0.24; IDI = 0.07). After intervention, participants with a > 15% reduction in UHR showed marked inflammatory improvement (GDF15 ↓18.0%, NLRP3 ↓27.9%, both P < 0.001). Greater responses were observed in carriers of the SLC2A9 TT genotype (ΔUHR = − 21.3%).
conclusionConclusion: UHR integrates oxidative stress and lipid metabolism pathways. It is a strong predictor of MS in the elderly (AUC = 0.782) and significantly improves the diagnostic performance of traditional models (ΔAUC = 0.092, P < 0.001). Its low cost (< 5 RMB per test) and dynamic responsiveness (ΔUHR reflecting intervention efficacy) support its utility as a primary screening tool in community settings. However, as the intervention was not a randomized controlled trial, these findings should be interpreted as correlational, and causal relationships require confirmation in large multicenter randomized studies.
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