美国成人血浆动脉粥样硬化指数与高血压合并糖尿病的关系:2011 - 2016年NHANES调查分析

IF 2.8 3区 医学 Q3 ENVIRONMENTAL SCIENCES
Xiuqing Chen, Qinyi Li, Zhoufei Fang, Linjing Huang, Peiwen Wu
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引用次数: 0

摘要

导论:观察性研究表明,高血压(HTN)和糖尿病(DM)患者往往表现出血浆动脉粥样硬化指数(AIP)升高,定义为log(甘油三酯[TG]/高密度脂蛋白胆固醇(HDL-C))。然而,这些因素之间的确切关系尚不清楚。本研究旨在探讨HTN、DM和AIP之间的相关性。方法:数据来自国家健康与营养检查调查(NHANES;2011-2016年),分析了一个具有全国代表性的样本,以评估AIP与美国成年人HTN和DM共存之间的关系。AIP作为暴露变量,对28个协变量进行调整。采用基线特征、相关分析、分层分析和非线性模型来阐明这些关联。采用极限梯度增强(XGBoost)机器学习算法评估各种变量对HTN和DM存在的预测价值,并进行受试者工作特征(ROC)曲线分析以评估AIP对HTN和DM的诊断准确性。结果:基线特征显示HTN和DM个体的平均AIP值较高(0.39)。饮酒、肥胖或代谢综合征的参与者更有可能同时出现这两种情况。AIP与HTN合并DM存在显著正相关(模型1:比值比[OR] = 5.93, 95%可信区间[CI] = 3.84-9.16, P)结论:本横断面研究表明AIP与HTN合并DM存在显著相关性,强调其作为诊断工具的潜力。这些发现为未来的预防和治疗方法提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Association between atherogenic index of plasma and hypertension combined with diabetes mellitus in United States adults: an analysis of the NHANES surveys from 2011 to 2016.

Association between atherogenic index of plasma and hypertension combined with diabetes mellitus in United States adults: an analysis of the NHANES surveys from 2011 to 2016.

Association between atherogenic index of plasma and hypertension combined with diabetes mellitus in United States adults: an analysis of the NHANES surveys from 2011 to 2016.

Association between atherogenic index of plasma and hypertension combined with diabetes mellitus in United States adults: an analysis of the NHANES surveys from 2011 to 2016.

Introduction: Observational studies have indicated that individuals with hypertension (HTN) and diabetes mellitus (DM) tend to exhibit elevated plasma atherogenic index of plasma (AIP), defined as log (triglyceride [TG]/high-density lipoprotein cholesterol (HDL-C)). However, the precise relationship between these factors remains unclear. This study aimed to examine the correlations among HTN, DM, and AIP.

Methods: Data from the National Health and Nutrition Examination Survey (NHANES; 2011-2016), a nationally representative sample, were analyzed to assess the relationship between AIP and the coexistence of HTN and DM in United States (US) adults. AIP served as the exposure variable, adjusted for 28 covariates. Baseline characteristics, correlation analysis, stratified analysis, and non-linear modeling were employed to elucidate these associations. The Extreme Gradient Boosting (XGBoost) machine learning algorithm was utilized to evaluate the predictive value of various variables for the presence of HTN and DM. Receiver operating characteristic (ROC) curve analysis was performed to assess AIP's diagnostic accuracy for detecting HTN and DM.

Results: Baseline characteristics revealed that individuals with HTN and DM had higher mean AIP values (0.39). Participants with alcohol use, obesity, or metabolic syndrome were more likely to present with both conditions. A significant positive correlation between AIP and the coexistence of HTN and DM was found (model 1: odds ratio [OR] = 5.93, 95% confidence interval [CI] = 3.84-9.16, P < 0.001; model 2: OR = 6.78, 95% CI = 4.14-11.1, P < 0.001; model 3: OR = 3.95, 95% CI = 1.66-9.39, P = 0.005), as confirmed by stratified analysis and smoothing curve analysis. The XGBoost algorithm identified AIP as an important predictor of HTN and DM. ROC curve analysis demonstrated AIP's relatively high accuracy in predicting these conditions. Smoothing curve analysis further supported the positive associations among AIP, HTN, and DM.

Conclusion: This cross-sectional study highlights AIP was significantly associated with HTN combined with DM, underscoring its potential as a diagnostic tool. These findings provide valuable insights for future preventive and therapeutic approaches.

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来源期刊
Journal of Health, Population, and Nutrition
Journal of Health, Population, and Nutrition 医学-公共卫生、环境卫生与职业卫生
CiteScore
2.20
自引率
0.00%
发文量
49
审稿时长
6 months
期刊介绍: Journal of Health, Population and Nutrition brings together research on all aspects of issues related to population, nutrition and health. The journal publishes articles across a broad range of topics including global health, maternal and child health, nutrition, common illnesses and determinants of population health.
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