Milken Institute School of Public Health, George Washington University, 950 New Hampshire Ave, Washington, DC, 20052, USA.
Milken Institute School of Public Health, George Washington University, 950 New Hampshire Ave, Washington, DC, 20052, USA.
Environ Res. 2024 Sep 1;256:119178. doi: 10.1016/j.envres.2024.119178. Epub 2024 May 18.
Reported associations between particulate matter with aerodynamic diameter ≤2.5 μm (PM) and cognitive outcomes remain mixed. Differences in exposure estimation method may contribute to this heterogeneity.
To assess agreement between PM exposure concentrations across 11 exposure estimation methods and to compare resulting associations between PM and cognitive or MRI outcomes.
We used Visit 5 (2011-2013) cognitive testing and brain MRI data from the Atherosclerosis Risk in Communities (ARIC) Study. We derived address-linked average 2000-2007 PM exposure concentrations in areas immediately surrounding the four ARIC recruitment sites (Forsyth County, NC; Jackson, MS; suburbs of Minneapolis, MN; Washington County, MD) using 11 estimation methods. We assessed agreement between method-specific PM concentrations using descriptive statistics and plots, overall and by site. We used adjusted linear regression to estimate associations of method-specific PM exposure estimates with cognitive scores (n = 4678) and MRI outcomes (n = 1518) stratified by study site and combined site-specific estimates using meta-analyses to derive overall estimates. We explored the potential impact of unmeasured confounding by spatially patterned factors.
Exposure estimates from most methods had high agreement across sites, but low agreement within sites. Within-site exposure variation was limited for some methods. Consistently null findings for the PM-cognitive outcome associations regardless of method precluded empirical conclusions about the potential impact of method on study findings in contexts where positive associations are observed. Not accounting for study site led to consistent, adverse associations, regardless of exposure estimation method, suggesting the potential for substantial bias due to residual confounding by spatially patterned factors.
PM estimation methods agreed across sites but not within sites. Choice of estimation method may impact findings when participants are concentrated in small geographic areas. Understanding unmeasured confounding by factors that are spatially patterned may be particularly important in studies of air pollution and cognitive or brain health.
已有研究报告指出,空气动力学直径≤2.5μm 的颗粒物(PM)与认知结果之间存在关联,但结果并不一致。暴露评估方法的差异可能是导致这种异质性的原因之一。
评估 11 种 PM 暴露评估方法之间的 PM 暴露浓度的一致性,并比较 PM 与认知或 MRI 结果之间的关联。
我们使用来自动脉粥样硬化风险社区(ARIC)研究的第 5 次(2011-2013 年)认知测试和脑 MRI 数据。我们使用 11 种方法,从 ARIC 招募地点(北卡罗来纳州福赛斯县、密西西比州杰克逊、明尼苏达州明尼阿波利斯郊区、马里兰州华盛顿县)周围的区域中得出与地址相关的 2000-2007 年平均 PM 暴露浓度。我们使用描述性统计和图表评估特定方法之间的 PM 浓度的一致性,总体评估和按地点评估。我们使用调整后的线性回归估计特定方法的 PM 暴露估计值与认知评分(n=4678)和 MRI 结果(n=1518)之间的关联,按研究地点进行分层,并使用元分析结合站点特异性估计值来得出总体估计值。我们探索了未测量的空间模式因素对混杂的潜在影响。
大多数方法的暴露估计值在不同地点之间具有高度一致性,但在同一地点之间一致性较低。对于一些方法,其内部暴露的变化是有限的。无论使用哪种方法,PM 与认知结果的关联均未发现一致的阳性结果,这使得无法根据方法对观察到阳性关联的研究结果的潜在影响得出经验性结论。未考虑研究地点会导致一致的、不利的关联,而不论暴露评估方法如何,这表明由于空间模式因素引起的残留混杂可能存在很大的偏差。
PM 估计方法在不同地点之间是一致的,但在同一地点内不一致。当参与者集中在小的地理区域时,选择估计方法可能会影响研究结果。了解由空间模式因素引起的未测量的混杂可能在空气污染与认知或大脑健康的研究中尤为重要。