Zigler Corwin Matthew, Dominici Francesca
Am J Epidemiol. 2014 Dec 15;180(12):1133-40. doi: 10.1093/aje/kwu263. Epub 2014 Nov 15.
The regulatory environment surrounding policies to control air pollution warrants a new type of epidemiologic evidence. Whereas air pollution epidemiology has typically informed policies with estimates of exposure-response relationships between pollution and health outcomes, these estimates alone cannot support current debates surrounding the actual health effects of air quality regulations. We argue that directly evaluating specific control strategies is distinct from estimating exposure-response relationships and that increased emphasis on estimating effects of well-defined regulatory interventions would enhance the evidence that supports policy decisions. Appealing to similar calls for accountability assessment of whether regulatory actions impact health outcomes, we aim to sharpen the analytic distinctions between studies that directly evaluate policies and those that estimate exposure-response relationships, with particular focus on perspectives for causal inference. Our goal is not to review specific methodologies or studies, nor is it to extoll the advantages of "causal" versus "associational" evidence. Rather, we argue that potential-outcomes perspectives can elevate current policy debates with more direct evidence of the extent to which complex regulatory interventions affect health. Augmenting the existing body of exposure-response estimates with rigorous evidence of the causal effects of well-defined actions will ensure that the highest-level epidemiologic evidence continues to support regulatory policies.
围绕空气污染控制政策的监管环境需要一种新型的流行病学证据。空气污染流行病学通常通过估计污染与健康结果之间的暴露-反应关系为政策提供依据,但仅凭这些估计无法支持当前围绕空气质量法规实际健康影响的辩论。我们认为,直接评估具体的控制策略与估计暴露-反应关系不同,并且更加注重估计明确界定的监管干预措施的效果将增强支持政策决策的证据。呼吁对监管行动是否影响健康结果进行类似的问责评估,我们旨在明确直接评估政策的研究与估计暴露-反应关系的研究之间的分析差异,特别关注因果推断的视角。我们的目标不是回顾具体方法或研究,也不是颂扬“因果”证据与“关联”证据的优势。相反,我们认为潜在结果视角可以通过更直接的证据提升当前政策辩论,即复杂的监管干预措施对健康影响的程度。用明确界定行动的因果效应的严格证据补充现有的暴露-反应估计,将确保最高水平的流行病学证据继续支持监管政策。