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Characterizing the Long-Term PM2.5 Concentration-Response Function: Comparing the Strengths and Weaknesses of Research Synthesis Approaches

机译：表征长期PM2.5浓度-响应功能：比较研究综合方法的优缺点

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摘要

The magnitude, shape, and degree of certainty in the association between long-term population exposure to ambient fine particulate matter (PM2.5) and the risk of premature death is one of the most intensely studied issues in environmental health. For regulatory risk analysis, this relationship is described quantitatively by a concentration-response (C-R) function that relates exposure to ambient concentrations with the risk of premature mortality. Four data synthesis techniques develop the basis for, and derive, this function: systematic review, expert judgment elicitation, quantitative meta-analysis, and integrated exposure-response (IER) assessment. As part of an academic workshop aiming to guide the use of research synthesis approaches, we developed criteria with which to evaluate and select among the approaches for their ability to inform policy choices. These criteria include the quality and extent of scientific support for the method, its transparency and verifiability, its suitability to the policy problem, and the time and resources required for its application. We find that these research methods are both complementary and interdependent. A systematic review of the multidisciplinary evidence is a starting point for all methods, providing the broad conceptual basis for the nature, plausibility, and strength of the associations between PM exposure and adverse health effects. Further, for a data-rich application like PM2.5 and premature mortality, all three quantitative approaches can produce estimates that are suitable for regulatory and benefit analysis. However, when fewer data are available, more resource-intensive approaches such as expert elicitation may be more important for understanding what scientists know, where they agree or disagree, and what they believe to be the most important areas of uncertainty. Whether implicitly or explicitly, all require considerable judgment by scientists. Finding ways for all these methods to acknowledge, appropriately elicit, and examine the implications of that judgment would be an important step forward for research synthesis.
机译：人群长期暴露于环境细颗粒物（PM2.5）与过早死亡风险之间的关联的大小，形状和确定性是环境健康中研究最广泛的问题之一。对于监管风险分析，此关系通过浓度响应（C-R）函数进行定量描述，该函数将暴露于环境浓度与过早死亡的风险相关联。四种数据合成技术为该功能奠定了基础，并得到了这种功能：系统综述，专家判断引诱，定量荟萃分析和综合暴露-反应（IER）评估。作为旨在指导研究综合方法使用的学术研讨会的一部分，我们制定了评估和选择方法的标准，以告知他们进行政策选择的能力。这些标准包括对该方法的科学支持的质量和程度，其透明度和可验证性，对策略问题的适用性以及应用该方法所需的时间和资源。我们发现这些研究方法既互补又相互依存。对多学科证据的系统评价是所有方法的起点，为PM暴露与不良健康影响之间关联的性质，合理性和强度提供了广泛的概念基础。此外，对于像PM2.5和过早死亡这样的数据丰富的应用程序，所有三种定量方法都可以产生适用于监管和收益分析的估计值。但是，当可获得的数据较少时，诸如专家启发之类的资源密集型方法对于理解科学家所知道的知识，他们同意或不同意的地方以及他们认为不确定性最重要的领域可能更为重要。无论是隐含的还是显式的，所有这些都需要科学家做出相当大的判断。为所有这些方法寻找方法，以确认，适当地引出和检验该判断的含义，将是研究综合性迈出的重要一步。

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