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Current Methods and Challenges for Epidemiological Studies of the Associations Between Chemical Constituents of Particulate Matter and Health

机译:颗粒物化学成分与健康之间关联的流行病学研究的当前方法和挑战

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摘要

Epidemiological studies have been critical for estimating associations between exposure to ambient particulate matter (PM) air pollution and adverse health outcomes. Because total PM mass is a temporally and spatially varying mixture of constituents with different physical and chemical properties, recent epidemiological studies have focused on PM constituents. Most studies have estimated associations between PM constituents and health using the same statistical methods as in studies of PM mass. However, these approaches may not be sufficient to address challenges specific to studies of PM constituents, namely assigning exposure, disentangling health effects, and handling measurement error. We reviewed large, population-based epidemiological studies of PM constituents and health and describe the statistical methods typically applied to address these challenges. Development of statistical methods that simultaneously address multiple challenges, for example, both disentangling health effects and handling measurement error, could improve estimation of associations between PM constituents and adverse health outcomes.
机译:流行病学研究对于估计暴露于周围颗粒物(PM)空气污染与不良健康后果之间的关联至关重要。由于总PM量是具有不同物理和化学性质的成分在时间和空间上的混合,因此最近的流行病学研究集中在PM成分上。大多数研究使用与PM量研究相同的统计方法估算了PM成分与健康之间的关联。然而,这些方法可能不足以解决特定于PM成分研究的挑战,即分配暴露,消除健康影响和处理测量误差。我们回顾了以人群为基础的关于PM成分和健康的流行病学研究,并描述了通常用于应对这些挑战的统计方法。发展同时解决多种挑战(例如消除健康影响和处理测量误差)的统计方法,可以改善对PM成分与不良健康结果之间关联的估计。

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