当前位置: X-MOL 学术Environ. Health Perspect. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Association of Gaseous Ambient Air Pollution and Dementia-Related Neuroimaging Markers in the ARIC Cohort, Comparing Exposure Estimation Methods and Confounding by Study Site.
Environmental Health Perspectives ( IF 10.1 ) Pub Date : 2024-06-26 , DOI: 10.1289/ehp13906
Katie M Lynch 1 , Erin E Bennett 1 , Qi Ying 2 , Eun Sug Park 3 , Xiaohui Xu 4 , Richard L Smith 5, 6 , James D Stewart 7 , Duanping Liao 8 , Joel D Kaufman 9 , Eric A Whitsel 7, 10 , Melinda C Power 1
Affiliation  

BACKGROUND Evidence linking gaseous air pollution to late-life brain health is mixed. OBJECTIVE We explored associations between exposure to gaseous pollutants and brain magnetic resonance imaging (MRI) markers among Atherosclerosis Risk in Communities (ARIC) Study participants, with attention to the influence of exposure estimation method and confounding by site. METHODS We considered data from 1,665 eligible ARIC participants recruited from four US sites in the period 1987-1989 with valid brain MRI data from Visit 5 (2011-2013). We estimated 10-y (2001-2010) mean carbon monoxide (CO), nitrogen dioxide (NO2), nitrogen oxides (NOx), and 8- and 24-h ozone (O3) concentrations at participant addresses, using multiple exposure estimation methods. We estimated site-specific associations between pollutant exposures and brain MRI outcomes (total and regional volumes; presence of microhemorrhages, infarcts, lacunes, and severe white matter hyperintensities), using adjusted linear and logistic regression models. We compared meta-analytically combined site-specific associations to analyses that did not account for site. RESULTS Within-site exposure distributions varied across exposure estimation methods. Meta-analytic associations were generally not statistically significant regardless of exposure, outcome, or exposure estimation method; point estimates often suggested associations between higher NO2 and NOx and smaller temporal lobe, deep gray, hippocampal, frontal lobe, and Alzheimer disease signature region of interest volumes and between higher CO and smaller temporal and frontal lobe volumes. Analyses that did not account for study site more often yielded significant associations and sometimes different direction of associations. DISCUSSION Patterns of local variation in estimated air pollution concentrations differ by estimation method. Although we did not find strong evidence supporting impact of gaseous pollutants on brain changes detectable by MRI, point estimates suggested associations between higher exposure to CO, NOx, and NO2 and smaller regional brain volumes. Analyses of air pollution and dementia-related outcomes that do not adjust for location likely underestimate uncertainty and may be susceptible to confounding bias. https://doi.org/10.1289/EHP13906.

中文翻译:


ARIC 队列中气态环境空气污染与痴呆相关神经影像学标志物的关联,比较暴露估计方法和研究地点的混杂。



背景 将气态空气污染与晚年大脑健康联系起来的证据好坏参半。目的 我们探讨了社区动脉粥样硬化风险 (ARIC) 研究参与者暴露于气态污染物与脑磁共振成像 (MRI) 标志物之间的关联,并关注暴露估计方法的影响和各地点的混杂。方法 我们考虑了 1987-1989 年期间从四个美国站点招募的 1,665 名合格 ARIC 参与者的数据以及第 5 次访问 (2011-2013) 的有效脑部 MRI 数据。我们使用多种暴露估计方法估计了参与者地址的 10 年 (2001-2010 年) 平均一氧化碳 (CO) 、二氧化氮 (NO2)、氮氧化物 (NOx) 以及 8 小时和 24 小时臭氧 (O3) 浓度。我们使用调整后的线性和 logistic 回归模型估计了污染物暴露与脑部 MRI 结果(总体积和区域体积;存在微出血、梗死、腔隙和严重白质高信号)之间的局部特异性关联。我们将荟萃分析结合的部位特异性关联与不考虑部位的分析进行了比较。结果 场内暴露分布因暴露估计方法而异。无论暴露、结局或暴露估计方法如何,荟萃分析关联通常不具有统计学意义;点估计通常表明较高的 NO2 和 NOx 与较小的颞叶、深灰色、海马、额叶和阿尔茨海默病特征感兴趣区域体积之间的关联,以及较高的 CO 与较小的颞叶和额叶体积之间的关联。不考虑研究地点的分析通常会产生显著的关联,有时会产生不同的关联方向。 讨论 估计空气污染浓度的局部变化模式因估计方法而异。尽管我们没有发现强有力的证据支持气态污染物对 MRI 可检测到的大脑变化的影响,但点估计表明 CO、NOx 和 NO2 暴露量较高与区域脑容量较小之间存在关联。不对位置进行调整的空气污染和痴呆相关结局的分析可能低估了不确定性,并且可能容易受到混杂偏倚的影响。https://doi.org/10.1289/EHP13906。
更新日期:2024-06-26
down
wechat
bug