长期暴露于交通相关的空气污染和噪音以及青春期的动态大脑连接。

IF 10.1 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES
Environmental Health Perspectives Pub Date : 2025-05-01 Epub Date: 2025-05-05 DOI:10.1289/EHP14525
Mónica López-Vicente, Michelle Kusters, Anne-Claire Binter, Sami Petricola, Henning Tiemeier, Ryan Muetzel, Mònica Guxens
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引用次数: 0

摘要

背景:与交通相关的暴露,如空气污染和噪音,显示出与儿童和青少年大脑改变的长期联系。使用静息状态功能磁共振成像(rs-fMRI)的静态方法(即扫描过程中各区域之间的平均连通性)研究了与功能连通性的关联。目的:我们的目的是研究交通空气污染和噪音在怀孕和童年期间与青春期功能连接的长期关系,采用动态方法,在扫描过程中捕捉不同的连接模式。方法:我们使用的数据来自基于R世代人口的出生队列。我们估计了孕期和儿童期家庭住址的14种空气污染物和交通噪音水平。我们在10岁和14岁时获得了rs-fMRI数据。我们在至少一次就诊中纳入了具有rs-fMRI数据的参与者,其中包括空气污染数据(n=3,588)或噪声数据(n=2,642)。我们使用k-means聚类来识别5种连接模式,称为“状态”,随着时间的推移,在不同的主题和访问中反复出现。我们计算了每个参与者在每个州和访问的平均时间。我们进行了多种和单一污染物混合效应模型,调整了社会经济和生活方式变量,包括个体随机效应,以测试暴露与每个州平均花费时间之间的关联。结果:在多污染物和单一污染物模型中,暴露于氮氧化物、颗粒物(PM)和道路交通噪声与连接状态所花费的时间差异有关。例如,怀孕期间较高的pmrough (PM2.5-PM10)和童年时期较高的噪音与在默认模式网络(与自我参照过程和走神相关)显示高连通性的状态下花费的时间有关。讨论:交通相关暴露可能与青少年大脑功能网络组织的长期改变有关。进一步的研究应该探索这些差异对认知和精神病理的潜在影响。https://doi.org/10.1289/EHP14525。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Long-Term Exposure to Traffic-Related Air Pollution and Noise and Dynamic Brain Connectivity across Adolescence.

Background: Traffic-related exposures, such as air pollution and noise, show long-term associations with brain alterations in children and adolescents. The associations with functional connectivity have been studied using static approaches of resting-state functional magnetic resonance imaging (rs-fMRI) (i.e., average connectivity between regions across the scanning session).

Objectives: Our aim was to investigate the long-term association of traffic air pollution and noise during pregnancy and childhood with functional connectivity across adolescence using a dynamic approach, which captures different connectivity patterns across the scanning session.

Methods: We used data from the Generation R population-based birth cohort. We estimated levels of 14 air pollutants and traffic noise at home addresses during pregnancy and childhood. We acquired rs-fMRI data at the age-10 y and age-14 y visits. We included participants with rs-fMRI data in at least one visit and either air pollution data (n=3,588) or noise data (n=2,642). We used k-means clustering to identify five connectivity patterns, called "states," that reoccur over time and across subjects and visits. We calculated the mean time spent in each state for each participant and visit. We performed multi- and single-pollutant mixed effects models adjusted for socioeconomic and lifestyle variables, including the individual as random effect to test the associations between the exposures and the mean time spent in each state.

Results: Exposure to nitrogen oxides, particulate matter (PM), and road-traffic noise was related to differences in the time spent in the connectivity states, both in the multi- and single-pollutant models. For instance, higher levels of exposure to PM with aerodynamic diameter between 2.5μm and 10μm (PMCOARSE) during pregnancy and higher noise exposure during childhood were associated with more time spent in a state in which the default-mode network, related to self-referential processes and mind-wandering, shows high connectivity.

Discussion: Traffic-related exposures might be related to long-term alterations in brain functional network organization in adolescents. Further research should explore the potential impact of these differences on cognition and psychopathology. https://doi.org/10.1289/EHP14525.

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来源期刊
Environmental Health Perspectives
Environmental Health Perspectives 环境科学-公共卫生、环境卫生与职业卫生
CiteScore
14.40
自引率
2.90%
发文量
388
审稿时长
6 months
期刊介绍: Environmental Health Perspectives (EHP) is a monthly peer-reviewed journal supported by the National Institute of Environmental Health Sciences, part of the National Institutes of Health under the U.S. Department of Health and Human Services. Its mission is to facilitate discussions on the connections between the environment and human health by publishing top-notch research and news. EHP ranks third in Public, Environmental, and Occupational Health, fourth in Toxicology, and fifth in Environmental Sciences.
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