暴露于环境空气污染的个性化估计和在伦敦居住的老年人认知功能纵向队列分析中的应用。

IF 4.1 3区 医学 Q2 ENVIRONMENTAL SCIENCES
Dylan Wood, Dimitris Evangelopoulos, Nutthida Kitwiroon, Gregor Stewart, Tuan Vu, James Smith, Sean Beevers, Klea Katsouyanni
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引用次数: 0

摘要

背景:很难获得个人暴露于环境空气污染的准确估计,流行病学研究通常依赖于监测网络或模型得出的基于住所的估计,在空间和时间上平均。很少有流行病学研究比较个人接触和基于居住地的估计对健康的相关影响。目的:评估空气污染暴露与认知功能之间的关系,使用考虑移动性和位置的暴露估计。方法:对768名参加英国老龄化纵向研究的伦敦居民进行了基于住所的环境NO2、PM10和PM2.5的分散模型估计。实施伦敦混合暴露模型来调整每种污染物的估计值,以反映每个参与者基于年龄和居住地点的估计时间-活动模式。在长达15年的随访期内,单一污染物线性混合效应模型适用于两种暴露评估方法,以调查指定污染物浓度与认知功能之间的关系。结果:长期暴露于基于居住地的环境NO2 (IQR: 11.10µg/m3)、PM10(2.35µg/m3)和PM2.5(2.50µg/m3)的增加与复合记忆评分分别下降-0.10 [95% CI: -0.20, 0.00]、-0.07[-0.11,-0.02]和-0.14[-0.21,-0.06]相关。执行功能评分也出现类似下降(分别为-0.38[-0.58,-0.18],-0.11[-0.20,-0.02]和-0.14[-0.29,0.01])。当应用明显较低的个性化暴露估计值时,观察到每个IQR的综合记忆评分也有类似的下降,但执行功能评分的不利影响略有增加的一致模式很明显。影响声明:本研究构建了一个框架,通过该框架,来自代表性样本的时间-活动信息可以应用于流行病学队列研究中分配给个人的环境空气污染浓度的估计,目的是调整常用的基于住所的估计,以反映人口流动性和在各种微环境中花费的时间。考虑到时间活动,暴露估计值明显较低,这可能是因为欧洲人口的大部分时间都在室内度过,在室内,他们对环境空气污染的暴露可能会通过渗透减少,这在基于住宅的环境估计中没有考虑到。对这些方法的进一步研究可以深入了解个性化暴露估计的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Personalised estimation of exposure to ambient air pollution and application in a longitudinal cohort analysis of cognitive function in London-dwelling older adults.

Background: Accurate estimates of personal exposure to ambient air pollution are difficult to obtain and epidemiological studies generally rely on residence-based estimates, averaged spatially and temporally, derived from monitoring networks or models. Few epidemiological studies have compared the associated health effects of personal exposure and residence-based estimates.

Objective: To evaluate the association between exposure to air pollution and cognitive function using exposure estimates taking mobility and location into account.

Methods: Residence-based dispersion model estimates of ambient NO2, PM10 and PM2.5 were assigned to 768 London-dwelling participants of the English Longitudinal Study of Ageing. The London Hybrid Exposure Model was implemented to adjust estimates per pollutant to reflect the estimated time-activity patterns of each participant based on age and residential location. Single pollutant linear mixed-effects models were fit for both exposure assessment methods to investigate the associations between assigned pollutant concentrations and cognitive function over a follow-up period of up to 15 years.

Results: Increased long-term exposures to residence-based ambient NO2 (IQR: 11.10 µg/m3), PM10 (2.35 µg/m3), and PM2.5 (2.50 µg/m3) were associated with decreases of -0.10 [95% CI: -0.20, 0.00], -0.07 [-0.11, -0.02] and -0.14 [-0.21, -0.06], respectively, in composite memory score. Similar decreases were observed for executive function scores (-0.38 [-0.58, -0.18], -0.11 [-0.20, -0.02] and -0.14 [-0.29, 0.01], respectively). When applying personalised exposure estimates, which were substantially lower, similar decreases were observed for composite memory score per IQR, but a consistent pattern of slightly more adverse effects with executive function score was evident.

Impact statement: The present study constructed a framework through which time-activity information derived from a representative sample could be applied to estimates of ambient air pollution concentrations assigned to individuals in epidemiological cohort studies, with the intention of adjusting commonly used residence-based estimates to reflect population mobility and time spent in various microenvironments. Estimates of exposure were markedly lower when incorporating time-activity, likely because people in European populations spend a large proportion of their time indoors, where their exposure to ambient air pollution may be reduced through infiltration, which is not taken into account in residence-based ambient estimates. Further work into such methods could provide insights into the efficacy of personalising exposure estimates.

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来源期刊
CiteScore
8.90
自引率
6.70%
发文量
93
审稿时长
3 months
期刊介绍: Journal of Exposure Science and Environmental Epidemiology (JESEE) aims to be the premier and authoritative source of information on advances in exposure science for professionals in a wide range of environmental and public health disciplines. JESEE publishes original peer-reviewed research presenting significant advances in exposure science and exposure analysis, including development and application of the latest technologies for measuring exposures, and innovative computational approaches for translating novel data streams to characterize and predict exposures. The types of papers published in the research section of JESEE are original research articles, translation studies, and correspondence. Reported results should further understanding of the relationship between environmental exposure and human health, describe evaluated novel exposure science tools, or demonstrate potential of exposure science to enable decisions and actions that promote and protect human health.
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