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城市中青年人群代谢健康指标与心肺适能的关联:一项回顾性横断面研究

Association between metabolic health indicators and cardiorespiratory fitness in urban young and middle-aged population: a retrospective cross-sectional study.

作者信息

Wang Chengshuo, Yang Nan, Zhang Qin, Li Ying, Zhang Linli, Liu Zejian, Zhao Ruoxuan, Qi Jingman, Xiang Aomeng, Fu Yanxin, Xiong Zheyu, Wu Liang, Sun Jie, Huang Dan

机构信息

Beijing Xiaotangshan Hospital, Beijing, China.

Tianjin Key Laboratory of Exercise Physiology and Sports Medicine, Institute of Sport, Exercise and Health, Tianjin University of Sport, Tianjin, China.

出版信息

Front Endocrinol (Lausanne). 2025 May 21;16:1489152. doi: 10.3389/fendo.2025.1489152. eCollection 2025.

DOI:10.3389/fendo.2025.1489152
PMID:40469431
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12133495/
Abstract

BACKGROUND

Cardiorespiratory fitness (CRF) is an established risk factor for cardiovascular diseases (CVD). Compared with traditional clinical risk factors for CVD, CRF can better predict health status and possible adverse events. However, few studies have reported the association between multiple metabolic health indicators and CRF as an indicator of CVD risk. Therefore, this study aims to further understand the association between metabolic health indicators and CRF and to provide a theoretical basis for improving the early prevention strategies of CVD in the urban young and middle-aged population.

METHODS

A retrospective cross-sectional study was conducted on 889 young and middle-aged urban people who underwent health examinations in Beijing Xiaotangshan Hospital from January 2022 to December 2024. Baseline measurements of physical examination, biochemical examination, and cardiopulmonary exercise testing were obtained. The association between metabolic health indicators and CRF was analyzed. A multiple linear regression analysis was performed to assess the association between each metabolic health indicator and CRF and determine which metabolic health indicators may serve as useful predictors for assessing CRF.

RESULTS

We investigated the association between metabolic health indicators and CRF by adjusting for covariates (age, smoking status, and drinking status) associated with CRF. In multiple linear regression analysis, waist circumference (WC) ( = -0.196, = 0.010), fasting plasma glucose (FPG) ( = -0.143, < 0.001), and high-density lipoprotein cholesterol (HDL-C) ( = -0.125, = 0.005) were significantly associated with VO in young and middle-aged urban men. WC ( = -0.577, < 0.001) and FPG ( = -0.167, = 0.002) were significantly associated with VO in young and middle-aged urban women. In addition, WC (men: = -0.238, = 0.003; women: = -0.410, < 0.001) and FPG (men: = -0.147, < 0.001; women: = -0.123, = 0.034) were significantly associated with AT in men and women.

CONCLUSION

Our results showed that WC and FPG were significantly associated with CRF in young and middle-aged urban men and women. This suggests that WC and FPG may serve as useful predictors for assessing CRF within this population.

摘要

背景

心肺适能(CRF)是心血管疾病(CVD)公认的危险因素。与传统的心血管疾病临床危险因素相比,CRF能更好地预测健康状况和可能的不良事件。然而,很少有研究报道多种代谢健康指标与作为心血管疾病风险指标的CRF之间的关联。因此,本研究旨在进一步了解代谢健康指标与CRF之间的关联,为完善城市中青年人群心血管疾病的早期预防策略提供理论依据。

方法

对2022年1月至2024年12月在北京小汤山医院进行健康体检的889名城市中青年进行回顾性横断面研究。获取体格检查、生化检查和心肺运动测试的基线测量值。分析代谢健康指标与CRF之间的关联。进行多元线性回归分析,以评估每个代谢健康指标与CRF之间的关联,并确定哪些代谢健康指标可作为评估CRF的有用预测指标。

结果

我们通过调整与CRF相关的协变量(年龄、吸烟状况和饮酒状况)来研究代谢健康指标与CRF之间的关联。在多元线性回归分析中,腰围(WC)(β = -0.196,P = 0.010)、空腹血糖(FPG)(β = -0.143,P < 0.001)和高密度脂蛋白胆固醇(HDL-C)(β = -0.125,P = 0.005)与城市中青年男性的VO₂显著相关。WC(β = -0.577,P < 0.001)和FPG(β = -0.167,P = 0.002)与城市中青年女性的VO₂显著相关。此外,WC(男性:β = -0.238,P = 0.003;女性:β = -0.410,P < 0.001)和FPG(男性:β = -0.147,P < 0.001;女性:β = -0.123,P = 0.034)与男性和女性的无氧阈(AT)显著相关。

结论

我们的结果表明,WC和FPG与城市中青年男性和女性的CRF显著相关。这表明WC和FPG可能作为该人群中评估CRF的有用预测指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556c/12133495/f0cdde728581/fendo-16-1489152-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556c/12133495/a26463a2077c/fendo-16-1489152-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556c/12133495/f0cdde728581/fendo-16-1489152-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556c/12133495/a26463a2077c/fendo-16-1489152-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/556c/12133495/f0cdde728581/fendo-16-1489152-g002.jpg

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