Work

Visceral lipid accumulation and lipid accumulation product outperform insulin resistance score for metabolic syndrome prediction in Northern Chinese adults: validation through AUC comparison and decision curve analysis

Year: 2025

Type: article

Abstract: BACKGROUND: Metabolic syndrome (MetS) significantly elevates the risk of diabetes and cardiovascular disease. While insulin resistance (IR) underpins MetS pathogenesis, practical biomarkers for population screening remain limited. The metabolic score for IR (METS-IR), lipid accumulation product (LAP) and visceral adiposity index (VAI) are highly sensitive and specific biomarkers of IR, which require comparative validation. OBJECTIVE: To compare LAP, VAI, and METS-IR index for predicting MetS with sex-stratified analysis. METHODS: The physiological characteristics and blood biochemistry data collected from 2821 patients during an annual health check-up were analyzed. Participants were assigned to MetS group (≥3 MetS conditions), pre-Mets group (1-2 Mets components) or control group (0 component) based on IDF/AHA/NHLBI 2009 criteria and were further stratified by sex. The predictive value and clinical usefulness of the LAP, VAI, and METS-IR were evaluated by receiver operating characteristic (ROC) curve and decision curve analysis (DCA). RESULTS: LAP, VAI, and METS-IR levels were significantly elevated in the MetS group (P < 0.05) and strongly correlated with MetS components. ROC analysis revealed LAP as the superior predictor in the total cohort (AUC: 0.904 [95% CI: 0.888-0.920]) and females (AUC: 0.949 [95% CI: 0.921-0.976]), while VAI performed best in males (AUC: 0.863 [95% CI: 0.840-0.886]). DCA confirmed the superior clinical utility of LAP and VAI over METS-IR across subgroups. CONCLUSION: This large-scale validation establishes LAP and VAI as superior, sex-specific predictors of MetS compared to METS-IR. LAP is optimal overall and in women, while VAI is optimal in men. Their reliance on standard clinical measurements establishes them as practical tools for metabolic risk stratification.

Source: BMC Endocrine Disorders

DOI: 10.1186/s12902-025-02086-w

Authors: Qing Liu, Xing Guan, Li-Jun Wang, Zheng Wang, Han Zhang, Yu-Qiang Zuo

Institutions: Hebei Medical University, Second Hospital of Hebei Medical University, First Hospital of Shijiazhuang

Language: English

Topic: Diabetes, Cardiovascular Risks, and Lipoproteins

Subfield: Endocrinology, Diabetes and Metabolism

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,190