Association of 24 Conventional and Unconventional Anthropometric Indicators with Pre-Hypertension or Hypertension: A Population-Based Cross-Sectional Study in Chinese Population

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 (Pnonlinear < 0.05). The results from the subgroup analysis and sensitivity analysis basically supported the primary findings. 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.