Changing the environment to improve population health: a framework for considering exposure in natural experimental studies
Changing the environment to improve population health: a framework for considering exposure in natural experimental studies
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DOI：
10.1136/jech-2015-206381
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发表时间：
2016-09-01
影响因子：
6.3
通讯作者：
Ogilvie, David
中科院分区：
文献类型：
--
作者：
Humphreys, David K.;Panter, Jenna;Ogilvie, David
人们对利用自然实验研究来证明人口健康干预措施的有效性重新感到乐观。自然实验研究利用了环境和政策事件，这些事件改变了对影响健康的某些社会，经济或环境因素的暴露。自然实验研究可用于检查上游决定因素变化的影响，这可能不适合控制实验。然而，虽然自然实验提供了产生证据的机会，但它们往往存在某些概念和方法上的障碍。改变自然或社会环境的人口健康干预措施通常在人口和社区中广泛实施。这些干预措施的广度意味着，接触、吸收和影响方面的差异可能是复杂的。然而，许多自然实验的评价狭隘地集中在确定适当的暴露的“和未暴露的”人口进行比较。在本文中，我们讨论了有关的概念和分析问题，定义和测量暴露于干预措施在这种情况下，包括最近的技术进步如何使研究人员能够更好地了解人口暴露于建筑环境的变化的性质。我们认为，当不清楚人群是否暴露于干预措施时，用调查不同暴露水平的观察方法来补充传统的影响评估可能是有利的。我们认为，更好地了解暴露的变化将有助于调查复杂的自然实验对人群健康的影响。
There is renewed optimism regarding the use of natural experimental studies to generate evidence as to the effectiveness of population health interventions. Natural experimental studies capitalise on environmental and policy events that alter exposure to certain social, economic or environmental factors that influence health. Natural experimental studies can be useful for examining the impact of changes to upstream' determinants, which may not be amenable to controlled experiments. However, while natural experiments provide opportunities to generate evidence, they often present certain conceptual and methodological obstacles. Population health interventions that alter the physical or social environment are usually administered broadly across populations and communities. The breadth of these interventions means that variation in exposure, uptake and impact may be complex. Yet many evaluations of natural experiments focus narrowly on identifying suitable exposed' and unexposed' populations for comparison. In this paper, we discuss conceptual and analytical issues relating to defining and measuring exposure to interventions in this context, including how recent advances in technology may enable researchers to better understand the nature of population exposure to changes in the built environment. We argue that when it is unclear whether populations are exposed to an intervention, it may be advantageous to supplement traditional impact assessments with observational approaches that investigate differing levels of exposure. We suggest that an improved understanding of changes in exposure will assist the investigation of the impact of complex natural experiments in population health.