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中国中老年人群多种空气污染物混合暴露与肌肉减少症的健康效应。

Health effect of multiple air pollutant mixture on sarcopenia among middle-aged and older adults in China.

机构信息

Public Health Department, Hongqiao International Institute of Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China; School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.

Department of Social Medicine and Health Education, School of Public Health, Peking University, Beijing, PR China.

出版信息

Ecotoxicol Environ Saf. 2024 Aug;281:116634. doi: 10.1016/j.ecoenv.2024.116634. Epub 2024 Jun 25.

Abstract

BACKGROUND

As the global aging process accelerates, the health challenges posed by sarcopenia among middle-aged and older adults are becoming increasingly prominent. However, the available evidence on the adverse effects of air pollution on sarcopenia is limited, particularly in the Western Pacific region. This study aimed to explore relationships of multiple air pollutants with sarcopenia and related biomarkers using the nationally representative database.

METHODS

Totally, 6585 participants aged over 45 years were enrolled from the China Health and Retirement Longitudinal Study (CHARLS) in 2011 and 3443 of them were followed up until 2015. Air pollutants were estimated from high-resolution satellite-based spatial-temporal models. In the cross-sectional analysis, we used generalized linear regression, unconditional logistic regression analytical and restricted cubic spline (RCS) methods to assess the single-exposure and non-linear effects of multiple air pollutants on sarcopenia and related surrogate biomarkers (serum creatinine and cystatin C). Several popular mixture analysis techniques such as Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS) regression, and quantile-based g-computation (Qgcomp) were further used to examinate the combined effects of multiple air pollutants. Logistic regression was used to further analyze the longitudinal association between air pollution and sarcopenia.

RESULTS

Each interquartile range increase in PM, PM and NO was significantly associated with an increased risk of sarcopenia, with adjusted odds ratios (aORs) of 1.09 [95 % confidence interval (CI): 1.01, 1.20], 1.24 (95 % CI: 1.14, 1.35) and 1.18 (95 % CI: 1.08, 1.28), respectively. Our findings also showed that five air pollutants were significantly associated with the sarcopenia index. In addition, employing a mixture analysis approach, we confirmed significant combined effects of air pollution mixtures on sarcopenia risk and associated biomarkers, with PM and PM identified as major contributors to the combined effect. The results of the exposure-response (E-R) relationships, subgroup analysis, longitudinal analysis and sensitivity analysis all showed the unfavorable impact of air pollution on sarcopenia risk and related vulnerable populations.

CONCLUSIONS

Single-exposure and co-exposure to multiple air pollutants were positively associated with sarcopenia among middle-aged and older adults in China. Our study provided new evidence that air pollution mixture was significantly associated with sarcopenia related biomarkers.

摘要

背景

随着全球老龄化进程的加速,中老年人肌肉减少症带来的健康挑战日益凸显。然而,目前关于空气污染对肌肉减少症的不良影响的证据有限,特别是在西太平洋地区。本研究旨在利用全国代表性数据库探讨多种空气污染物与肌肉减少症及相关生物标志物的关系。

方法

共纳入 2011 年中国健康与退休纵向研究(CHARLS)中 6585 名年龄超过 45 岁的参与者,其中 3443 名参与者随访至 2015 年。利用高分辨率卫星时空模型估算空气污染物。在横断面分析中,我们采用广义线性回归、非条件逻辑回归分析和限制立方样条(RCS)方法评估多种空气污染物对肌肉减少症和相关替代生物标志物(血清肌酐和胱抑素 C)的单一暴露和非线性效应。进一步采用贝叶斯核机器回归(BKMR)、加权分位数和(WQS)回归和基于分位数的 g 计算(Qgcomp)等几种流行的混合分析技术,检测多种空气污染物的联合效应。采用逻辑回归进一步分析空气污染与肌肉减少症的纵向关联。

结果

PM2.5、PM10 和 NO 每增加一个四分位距,肌肉减少症的风险均显著增加,调整后的比值比(aOR)分别为 1.09(95%可信区间:1.01,1.20)、1.24(95%可信区间:1.14,1.35)和 1.18(95%可信区间:1.08,1.28)。我们的研究还发现,五种空气污染物与肌肉减少症指数显著相关。此外,采用混合分析方法,我们证实了空气污染混合物对肌肉减少症风险及相关生物标志物的显著联合效应,其中 PM2.5 和 PM10 被确定为联合效应的主要贡献者。暴露-反应(E-R)关系、亚组分析、纵向分析和敏感性分析的结果均表明,空气污染对肌肉减少症风险及相关脆弱人群有不利影响。

结论

单一暴露和多种空气污染物共同暴露与中国中老年人肌肉减少症呈正相关。本研究提供了新的证据,表明空气污染物混合物与肌肉减少症相关生物标志物显著相关。

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