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绝经后女性尿酸与高密度脂蛋白胆固醇比值(UHR)指数与肥胖之间的关联:基于美国国家健康和营养检查调查(NHANES)的横断面分析

The association between the uric acid to high-density lipoprotein cholesterol ratio (UHR) index and obesity in postmenopausal women: a cross-sectional analysis based on the NHANES.

作者信息

Tian Jing, Huang Yiming, Xiao Zhun, Yuan Shuaipeng, Ma Suping, Zhao Xiaonuo, Liu Yang

机构信息

Department of Digestive Diseases, The First Affiliated Hospital of Henan University of Chinese Medicine, No. 19 Renmin Road, Zhengzhou, 450000, P.R. China.

Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, No. 16, Dongzhimen Nei South Alley, Dongcheng District, Beijing, 100700, P. R. China.

出版信息

Lipids Health Dis. 2025 Sep 5;24(1):277. doi: 10.1186/s12944-025-02715-2.

Abstract

BACKGROUND

Obesity has emerged as a critical global public health challenge. Postmenopausal women experience significantly elevated risks of metabolic disorders and a marked increase in obesity prevalence due to declining estrogen levels. The uric acid to high-density lipoprotein cholesterol ratio (UHR), an emerging biomarker for metabolic syndrome, is gaining clinical recognition. This study systematically investigates the association between the UHR index and obesity in postmenopausal women and evaluates its predictive value.

METHODS

We conducted a cross-sectional analysis of 7,811 postmenopausal women from the 2005-2018 National Health and Nutrition Examination Survey (NHANES). Weighted multivariable logistic regression models, adjusted for sociodemographic characteristics, behavioral patterns, and clinical covariates, were employed to examine the UHR index's association with three obesity indices: body mass index (BMI), waist-to-height ratio (WHtR), and weight-adjusted waist index (WWI). Robustness was assessed through stratified subgroup analyses, interaction tests, restricted cubic spline (RCS) modeling, receiver operating characteristic (ROC) curves, and sensitivity analyses to evaluate nonlinear relationships and predictive performance.

RESULTS

The weighted obesity prevalence was 44.05%. After full adjustment, the highest UHR quartile (Q4) showed significantly elevated obesity risks versus the lowest quartile (Q1): BMI-defined obesity (adjusted OR = 8.08, 95% CI: 6.49-10.09), WHtR-defined obesity (adjusted OR = 29.95, 95% CI: 17.08-52.51), and WWI-defined obesity (adjusted OR = 4.58, 95% CI: 3.70-5.67). Subgroup analyses revealed significant effect modifications by diabetes, cardiovascular disease, and chronic kidney disease status (P for interaction < 0.05 for all three obesity indices). The RCS analysis demonstrated a nonlinear dose-response relationship. ROC analysis indicated superior predictive performance for WHtR-defined abdominal obesity (AUC = 0.795, 95% CI: 0.778-0.813), with sensitivity analyses corroborating the primary findings.

CONCLUSION

The UHR index exhibits a strong, dose-dependent association with obesity risk in postmenopausal women, persisting after comprehensive covariate adjustment. As a metabolic indicator, the UHR index provides clinically meaningful supplementation to conventional obesity assessments, particularly in capturing metabolically driven obesity risk.

摘要

背景

肥胖已成为一项严峻的全球公共卫生挑战。绝经后女性由于雌激素水平下降,代谢紊乱风险显著升高,肥胖患病率也明显增加。尿酸与高密度脂蛋白胆固醇比值(UHR)作为一种新兴的代谢综合征生物标志物,正逐渐获得临床认可。本研究系统地调查了UHR指数与绝经后女性肥胖之间的关联,并评估其预测价值。

方法

我们对2005 - 2018年美国国家健康与营养检查调查(NHANES)中的7811名绝经后女性进行了横断面分析。采用加权多变量逻辑回归模型,对社会人口统计学特征、行为模式和临床协变量进行调整,以检验UHR指数与三种肥胖指数的关联:体重指数(BMI)、腰高比(WHtR)和体重调整腰围指数(WWI)。通过分层亚组分析、交互作用检验、受限立方样条(RCS)建模、受试者工作特征(ROC)曲线和敏感性分析来评估稳健性,以评估非线性关系和预测性能。

结果

加权肥胖患病率为44.05%。经过全面调整后,与最低四分位数(Q1)相比,最高UHR四分位数(Q4)的肥胖风险显著升高:BMI定义的肥胖(调整后的OR = 8.08,95% CI:6.49 - 10.09),WHtR定义的肥胖(调整后的OR = 29.95,95% CI:17.08 - 52.51),以及WWI定义的肥胖(调整后的OR = 4.58,95% CI:3.70 - 5.67)。亚组分析显示,糖尿病、心血管疾病和慢性肾脏病状态对结果有显著的效应修饰作用(所有三种肥胖指数的交互作用P < 0.05)。RCS分析显示存在非线性剂量反应关系。ROC分析表明,WHtR定义的腹部肥胖具有更好的预测性能(AUC = 0.795,95% CI:0.778 - 0.813),敏感性分析证实了主要研究结果。

结论

UHR指数与绝经后女性的肥胖风险呈强剂量依赖性关联,在全面调整协变量后依然存在。作为一种代谢指标,UHR指数为传统肥胖评估提供了具有临床意义的补充,特别是在捕捉代谢驱动的肥胖风险方面。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0c6/12412247/53601d2d7c76/12944_2025_2715_Fig1_HTML.jpg

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