Natural and Unnatural Experiments in Epidemiology

buildings in a neighborhoodIn the past 1-2 decades, the use of natural experiments to produce more rigorous estimates of the effects of various risk factors on health has proliferated. Natural experiments have the potential to build a rich and convincing evidence base about the effects of neighborhood characteristics and other social factors, help guide interventions to improve the wellbeing of vulnerable populations writes Rita Hamad, MD, PhD, in a recent Epidemiology article.
Natural experiments, which encompass different study designs and involve any number of analytic techniques, generally aim to take advantage of natural-or in many cases, unnatural-variation in an exposure that may otherwise be challenging to randomize. The goal is to overcome confounding more robustly than standard correlational analyses of observational data by identifying some event that resulted in an element of randomness (or quasi-randomness) in the exposure of interest. Although virtually all natural experiments are flawed in some way, rather than dismissing the findings of natural experiments in which the circumstances of the randomization are less than ideal, the results of different types of studies can be considered holistically to provide a more comprehensive understanding of risk factors for poor health.
The use of natural experiments holds particular appeal for social epidemiologists like Dr. Hamad, because social factors are often exceptionally difficult to randomize due to ethical reasons or feasibility. Estimating the effects of neighborhood-level and other place-based characteristics is notoriously thorny, given the potential for selection of unhealthy individuals into less desirable neighborhoods and the rarity of opportunities to randomize individuals' place of residence. 
For example, in a recently published study* funded by NIA, Dr. Hamad and colleagues at UCSF and Aarhus University Denmark took advantage of a natural experiment in which incoming refugees were arbitrarily assigned to neighborhoods across Denmark. This meant that the refugees were exposed to essentially random levels of neighborhood disadvantage, which Dr. Hamad and her colleagues then used to examine the effects of neighborhood disadvantage on cardiovascular disease. In other studies, researchers have leveraged the occurrence of the 2011 earthquake and tsunami in Japan, in which the displacement of families resulted in changes in neighborhood exposures that might affect health.
Using evidence from multiple types of natural experiments like these, researchers can "triangulate" evidence from multiple studies using different study designs, data sources, analytic approaches, and contexts, to converge on a more holistic understanding of the causal effects of neighborhoods and other social factors on health.

Rita Hamad, MD, PhD

Dr. Hamad’s research focuses on the pathways linking poverty and education with health disparities across the life course. She is the director of the Social Policies for Health Equity Research Program and the Associate Director of the Center for Health Equity. She is also a member of the steering committee of the UCSF Population Health Data Initiative, serving as the Faculty Lead for the development of data infrastructure to advance population health research on campus. She serves on the communications committee of the Interdisciplinary Association for Population Health Science.





Natural and Unnatural Experiments in Epidemiology, Hamad R. Epidemiology. 2020 Nov;31(6):768-770. Doi: 10.1097/EDE.0000000000001242.

*Hamad R, Öztürk B, Foverskov E, et al. Association of Neighborhood Disadvantage With Cardiovascular Risk Factors and Events Among Refugees in Denmark. JAMA Netw Open. 2020;3(8):e2014196. doi:10.1001/jamanetworkopen.2020.14196.