Zhao Weijie, Wang Ziyue, Mi Chuanhao, Wang Yu, Shao Xinxin, Qi Xianghua, Kong Xinru
Department of First Clinical Medical College, Shandong University of Traditional Chinese Medicine, No. 16369, Jingshi Road, Jinan, Shandong, 250014, China.
Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, Beijing, 100000, China.
Postgrad Med J. 2024 Dec 23;101(1191):17-28. doi: 10.1093/postmj/qgae093.
The challenges posed by an aging society are increasingly recognized, particularly regarding the potential impacts of high-fat diets and the trend toward younger ages of disease onset. The purpose of this study was to clarify the relationships between the prevalence of stroke in the general US population and PhenoAge (PA) and PhenoAgeAccel (PAA).
Key methods included a correlation heatmap to explore linear relationships between some of the variables and weighted multivariable logistic regression to assess associations between PA, PAA, and stroke. Restricted cubic spline (RCS) analysis was used to investigate nonlinear relationships and dose-response effects. The ability of the PAA to predict stroke risk was assessed by a nomogram model and a receiver operating characteristic curve.
After adjusting for confounding variables, both continuous and categorical PA and PAA were significantly associated with stroke prevalence. RCS analysis revealed a significant nonlinear relationship between PA and stroke prevalence. Further subgroup RCS analysis indicated that maintaining PA below 31.6 could provide greater benefits across all races and genders, specifically for individuals aged 40-80 years and those who are overweight or obese.
This study highlights the importance of stroke prevention in overweight and obese populations. Monitoring intermediary factors such as high-density lipoprotein cholesterol and waist circumference may reduce stroke risk. Additionally, PA and PAA may serve as novel markers for stroke, offering new directions for health management in an aging society.
老龄化社会带来的挑战日益受到认可，尤其是高脂饮食的潜在影响以及疾病发病年龄趋于年轻化的趋势。本研究的目的是阐明美国普通人群中中风患病率与表型年龄（PA）和表型年龄加速（PAA）之间的关系。
关键方法包括相关热图，以探索部分变量之间的线性关系，以及加权多变量逻辑回归，以评估PA、PAA与中风之间的关联。使用受限立方样条（RCS）分析来研究非线性关系和剂量反应效应。通过列线图模型和受试者工作特征曲线评估PAA预测中风风险的能力。
在调整混杂变量后，连续型和分类型的PA和PAA均与中风患病率显著相关。RCS分析显示PA与中风患病率之间存在显著的非线性关系。进一步的亚组RCS分析表明，将PA维持在31.6以下对所有种族和性别的人群都能带来更大益处，特别是对于40 - 80岁的个体以及超重或肥胖者。
本研究强调了超重和肥胖人群中风预防的重要性。监测高密度脂蛋白胆固醇和腰围等中介因素可能会降低中风风险。此外，PA和PAA可能作为中风的新型标志物，为老龄化社会的健康管理提供新方向。
