He Jiarong, Zhang Wen, Zhao Fang, Wang Ming, Wang Zhuo, Liang Chen, Pan Jing, Jia Jiaoying, Zhang Mingming
Department of Neurosurgery, The Second Xiangya Hospital, Central South University, Changsha, Hunan, P. R. China.
Department of Nephrology, Yiyang Central Hospital, University of South China, Yiyang, Hunan, P. R. China.
BMC Public Health. 2024 Dec 18;24(1):3474. doi: 10.1186/s12889-024-21000-y.
The adverse effects of environmental toxic metal exposure on human health are well-documented. However, the specific influence of heavy metal exposure on stroke prevalence remains underexplored.
This study utilized data from the National Health and Nutrition Examination Survey (NHANES) spanning from 2011 to 2018 to investigate the association between blood metal concentrations and the incidence of stroke. Four analytical approaches-logistic regression, Restricted Cubic Splines (RCS), Weighted Quantile Sum regression (WQS), and Bayesian Kernel Machine Regression (BKMR)-were employed to assess the relationship, with a mediation analysis conducted to explore the role of inflammatory markers in Pb exposure-induced stroke.
Among the 9,399 participants in this project, 421 (4.4%) were diagnosed with stroke. After adjusting for covariates, a multivariable logistic regression model identified a positive association between the logarithmic concentration of Pb and the incidence of stroke. Besides, the analysis conducted using both WQS and BKMR methodologies found a consistent positive association between the composite exposure to heavy metals and the frequency of stroke cases, with Pb emerging as the predominant factor in this relationship. An evident saturation phenomenon was noted in the correlation between lead exposure and the risk of stroke. Additionally, the interplay between Pb exposure and stroke manifestation was found to be partially mediated by inflammatory markers, which were responsible for 6.9% of the observed effect (95%CI:0.01, 0.24, P = 0.03).
These findings indicate a notable contribution of Pb exposure to stroke risk, highlighting inflammation as a significant intermediary mechanism in the Pb exposure-stroke association.
环境有毒金属暴露对人类健康的不良影响已有充分记录。然而，重金属暴露对中风患病率的具体影响仍未得到充分探索。
本研究利用2011年至2018年国家健康与营养检查调查（NHANES）的数据，调查血金属浓度与中风发病率之间的关联。采用四种分析方法——逻辑回归、受限立方样条（RCS）、加权分位数和回归（WQS）以及贝叶斯核机器回归（BKMR）——来评估这种关系，并进行中介分析以探讨炎症标志物在铅暴露诱发中风中的作用。
在该项目的9399名参与者中，421人（4.4%）被诊断为中风。在调整协变量后，多变量逻辑回归模型确定铅的对数浓度与中风发病率之间存在正相关。此外，使用WQS和BKMR方法进行的分析发现，重金属复合暴露与中风病例频率之间存在一致的正相关，铅是这种关系中的主要因素。在铅暴露与中风风险之间的相关性中发现了明显的饱和现象。此外，发现铅暴露与中风表现之间的相互作用部分由炎症标志物介导，炎症标志物占观察到的效应的6.9%（95%CI：0.01，0.24，P = 0.03）。
这些发现表明铅暴露对中风风险有显著贡献，突出了炎症作为铅暴露与中风关联中的重要中介机制。
