Am J Epidemiol. 2023 Nov 3;192(11):1835-1841. doi: 10.1093/aje/kwac142.
In this commentary, invited for the 100th anniversary of the Journal, we discuss the addition of randomized experiments, along with natural experiments that emulate randomized trials using observational data, as designs in the social epidemiologist's toolbox. These approaches transform the way we define and ask questions about social exposures. They compel us to ask questions about how well-defined interventions change a social exposure that might lead to changes in health. As such, experiments are of unique public health and policy significance. We argue that they are a powerful approach to advance our understanding of how well-defined changes in social exposures impact health, and how credible social policy reforms may be instrumental to address health inequalities. We focus on two research designs. The first is a "pure" randomized controlled trial (RCT) in which the investigator defines and randomly assigns the intervention. The second is a natural experiment, which exploits the fact that policies or interventions in the real world often involve an element of random assignment, emulating an RCT. To give the reader our bottom line: While acknowledging their limits, we continue to be very excited about the promise of RCTs and natural experiments to advance social epidemiology.
在这篇评论中，我们应邀为该期刊创刊 100 周年而撰写，讨论了将随机实验与使用观察数据模拟随机试验的自然实验作为社会流行病学家工具包中的设计方法。这些方法改变了我们定义和提出社会暴露问题的方式。它们迫使我们提出关于干预措施如何改变可能导致健康状况发生变化的社会暴露的问题。因此，实验具有独特的公共卫生和政策意义。我们认为，它们是一种有力的方法，可以增进我们对明确的社会暴露变化如何影响健康以及可信的社会政策改革如何可能有助于解决健康不平等问题的理解。我们重点讨论了两种研究设计。第一种是纯粹的随机对照试验 (RCT)，其中研究者定义并随机分配干预措施。第二种是自然实验，它利用了现实世界中的政策或干预措施通常涉及随机分配的事实，模拟 RCT。为了给读者一个概括：我们承认它们的局限性，但我们仍然对 RCT 和自然实验在推进社会流行病学方面的前景感到非常兴奋。
