ArticleVascular health and risk management2025
Association of 24 Conventional and Unconventional Anthropometric Indicators with Pre-Hypertension or Hypertension: A Population-Based Cross-Sectional Study in Chinese Population.
Article in Vascular health and risk management, 2025. 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.
- The Triglyceride-Glucose Index and Its Combination with C-Reactive Protein and Anthropometric Indicators as Biomarkers for Hypertension Among Saudi Adults: A Cross-Sectional Survey.Journal of clinical medicine · 2026Article
- Depletion ofFrontiers in microbiology · 2026Article
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9 authors.
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Abstract
Background: Anthropometric indicators are known to be closely related to pre-hypertension and hypertension. This study aimed to explore the association of conventional and unconventional anthropometric indicators with pre-hypertension and hypertension. Methods: About 8787 adults (aged ≥18 years) who joined in the Chinese Residents Cardiovascular Disease and Risk Factors Surveillance Project (2020) were included. Twenty-four anthropometric indicators were measured and calculated, including conventional anthropometric indicators [eg, weight, fat mass (FM), body mass index (BMI), height-adjusted weight (HtaW), fat mass index (FMI), fat-free mass index (FFMI)] and unconventional anthropometric indicators [eg, atherogenic index of plasma (AIP), triglyceride-glucose index (TyG)]. LASSO regressions were used to identify key anthropometric indicators associated with pre-hypertension/hypertension. Multivariate logistic regression model, RCS regression analysis, subgroup analyses and sensitivity analyses were conducted to explore the association between anthropometric indicators and pre-hypertension/hypertension. ROC and AUC were also utilized to evaluate the performance of anthropometric indicators in identifying pre-hypertension/ hypertension. Results: After adjustment for potential confounders, multivariate logistic regression showed that weight, BMI, HtaW, FMI, FFMI, AIP, and TyG were significantly associated with pre-hypertension, while FM, AIP, and TyG were significantly associated with hypertension. ROC analysis showed that conventional anthropometric indicators were slightly superior to unconventional anthropometric indicators in identifying pre-hypertension and hypertension. RCS models suggested that weight, FMI, FFMI, AIP, and TyG had linear dose-response relationships with pre-hypertension risk, while BMI and HtaW were nonlinearly associated with pre-hypertension risk; FM, AIP and TyG had nonlinear dose-response relationships with hypertension risk ( Conclusion: As one of the first comprehensive comparisons of 24 anthropometric indicators in a large Chinese population, this study found that BMI and TyG were the best anthropometric indicators for identifying pre-hypertension, while TyG showed a significantly stronger association with hypertension.
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