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At the turn of the 21st century, University of Bristol epidemiologist George Davey Smith was growing dissatisfied with his field. “I’ve been working in epidemiology for a very long time,” he says. “And I was disillusioned with the conventional approaches to try to establish cause and effect in observational epidemiology.”
Confounding factors plague observational studies, which examine populations of people to identify correlations between environmental conditions or lifestyle factors and disease and therefore cannot draw conclusions about a disease’s cause. Highlighting the approach’s limitations is the fact that randomized controlled trials, widely considered the gold standard for medical evidence, have failed to confirm many observational results or translate them into interventions. Observational epidemiological studies, Davey Smith says, were “obviously getting things wrong.”
So in 2003, he wrote a paper that outlined how to reframe an observational study as a natural experiment by incorporating a dash of ...
