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Environmental Determinants of Cognitive Aging in the WHI Memory Study

Environmental Determinants of Cognitive Aging in the WHI Memory Study
WHI 记忆研究中认知衰老的环境决定因素
批准号:
8643556
负责人:
Jiu-Chiuan Chen
金额:
$56.93万
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-03-15 至 2017-02-28

项目摘要

项目成果

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中文摘要
翻译
项目描述(由申请人提供):该项目的长期目标是更好地了解环境对大脑衰老的影响以及随之而来的认知障碍和痴呆的风险。具体而言,我们将调查晚年暴露于环境空气污染物作为老年妇女易感人群认知衰老的新环境决定因素。在过去十年中,科学研究一再表明,环境空气污染会增加心血管疾病(CVD)的风险和死亡率。先前的研究发现,老年人,尤其是女性,对空气污染物对健康的不利影响更为敏感。虽然心血管疾病是导致认知障碍和痴呆的主要因素,但很少有人关注环境空气污染对老年人认知健康的潜在影响。在暴露于臭氧的动物模型中已经证明了记忆障碍。神经毒理学数据表明,暴露于环境空气污染物会引起大脑多个区域的氧化应激和神经炎症,尤其是海马和前额叶区。空气污染的毒性病理学研究也发现了加速犬脑老化的证据(例如,2-淀粉样蛋白积累伴或不伴营养不良性神经炎)。人体解剖研究和横断面流行病学分析分别将环境空气污染与脑老化或认知障碍的神经病理学联系起来。然而,关于环境空气污染是否以及如何导致人类大脑衰老以及随后的认知障碍和痴呆风险的令人信服的队列研究仍然缺乏。因此,拟议的研究旨在通过以下具体目标,以一种具有成本效益的方式解决这一关键的知识差距:(1)研究晚年暴露于空气污染是否会预测认知功能(全球;特定领域)的下降;(2)调查长期接触空气污染是否会增加痴呆的风险;(3)阐明空气污染暴露与认知障碍的可能机制;(4)确定人群对空气污染神经认知影响易感性的临床决定因素。本应用程序利用了在特征明确的妇女健康倡议记忆研究(WHIMS)队列(N=7479,年龄65-80岁)中收集的高质量纵向结果数据。基于每个WHIMS参与者的居住地理编码,将通过时空建模方法估计颗粒物和臭氧暴露,该方法将美国环保署监测系统的空气样本测量与空气质量模型的数据输出相结合。将使用多变量调整Cox模型、多水平混合效应模型和潜在曲线结构模型对数据进行分析。从这项研究中获得的知识将有助于国家更好地了解环境对认知健康的影响,解决环境神经学新兴领域的关键知识缺口,并为环境公共卫生政策提供信息。
英文摘要
DESCRIPTION (provided by applicant): The long-term goal of this project is to better understand the environmental influence on brain aging and subsequent risk of cognitive impairment and dementia. Specifically, we will investigate later-life exposure to ambient air pollutants as novel environmental determinants of cognitive aging in a susceptible population of older women. Over the last decade, scientific research has repeatedly shown that ambient air pollution increases cardiovascular disease (CVD) risk and mortality. Previous studies have found that older people, especially women, are more sensitive to these adverse health effects of air pollutants. Although CVD is a major contributor to cognitive impairment and dementia, little attention has been directed to the potential impact of ambient air pollution on cognitive health of the elderly. Memory impairments have been demonstrated in animal models exposed to ozone. Neurotoxicological data have shown that exposures to ambient air pollutants induce oxidative stress and neuroinflammation in multiple brain regions, especially in hippocampus and prefrontal region. Air pollution toxicopathological studies also found evidence of accelerated brain aging (e.g., 2-amyloid accumulation with or without dystrophic neuritis) in canines. Human autopsy studies and cross-sectional epidemiologic analyses have related ambient air pollution to neuropathology of brain aging or cognitive impairment, respectively. Convincing cohort studies on whether and how ambient air pollution contributes to brain aging and subsequent risk of cognitive impairment and dementia in humans, however, are still lacking. The proposed study is thus designed in a cost-efficient manner to address this critical knowledge gap, through the following specific aims: (1) to examine whether later-life exposure to air pollution predicts declines in cognitive function (global; specific domains); (2) to investigate whether long-term air pollution exposure increases the risk of dementia; (3) to elucidate the possible mechanisms linking cognitive impairment with exposure to air pollution; and (4) to identify the clinical determinants of population susceptibility to the neurocognitive effects of air pollution. This application leverages the high-quality longitudinal outcome data collected in the well-characterized Women's Health Initiative Memory Study (WHIMS) cohort (N=7479; aged 65-80 years). Based on residential geocode of each WHIMS participant, exposures to particulate matter and ozone will be estimated by a spatiotemporal modeling approach, which integrates air-sample measurements from the U.S. EPA monitoring system with the data outputs of air quality models. Multivariable-adjusted Cox models, multilevel mixed-effect models, and latent curve structural models will be used to analyze the data. The knowledge gained from this study will contribute to national efforts to better understand the environmental influence on cognitive health, address a critical knowledge gap in the emerging area of environmental neurology, and inform the environmental public health policies.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Bayesian Maximum Entropy Integration of Ozone Observations and Model Predictions: A National Application.
臭氧观测和模型预测的贝叶斯最大熵积分:全国应用。
DOI: 10.1021/acs.est.6b00096
发表时间: 2016
期刊: Environmental science & technology
影响因子: 11.4
作者: [Xu,Yadong, Serre,MarcL, Reyes,Jeanette, Vizuete,William]
通讯作者: Vizuete,William
Urban Air Pollution and Alzheimer's Disease: Risk, Heterogeneity, and Mechanisms
  • 批准号:
    10216922
  • 项目类别:
  • 资助金额:
    $224.03万
  • 财政年份:
    2018
  • 负责人:
    Jiu-Chiuan Chen
  • 依托单位:
Traffic-Related Air Pollutants and Alzheimer's Disease: Risk, Susceptibility and Mechanisms in Women
  • 批准号:
    10216926
  • 项目类别:
  • 资助金额:
    $39.33万
  • 财政年份:
    2018
  • 负责人:
    Jiu-Chiuan Chen
  • 依托单位:
Urban Air Pollution and Alzheimer's Disease: Risk, Heterogeneity, and Mechanisms
  • 批准号:
    10456747
  • 项目类别:
  • 资助金额:
    $226.45万
  • 财政年份:
    2018
  • 负责人:
    Jiu-Chiuan Chen
  • 依托单位:
Traffic-Related Air Pollutants and Alzheimer's Disease: Risk, Susceptibility and Mechanisms in Women
  • 批准号:
    10456752
  • 项目类别:
  • 资助金额:
    $44.02万
  • 财政年份:
    2018
  • 负责人:
    Jiu-Chiuan Chen
  • 依托单位:
海外基金