The importance of science-informed policy and what the data really tell us about e-cigarettes

A possible future end-game for cigarettes is explored in the context of the historical progress made to date by tobacco control. Despite good progress, there remains an urgent need to increase the use of proven tobacco control policies and practices for prevention and cessation. The problem is worse than previously thought and the 50(th) anniversary United States Surgeon General’s report indicates the overwhelming majority of avoidable deaths are caused by combusting of tobacco, primarily cigarettes. The report highlights for the first time the addition of a harm minimization strategy to enhance proven tobacco control efforts and thus much more rapidly speed the obsolescence of cigarettes. Harm minimization can be two pronged. First, it can boost proven tobacco control polices to make cigarettes more expensive and less appealing and accessible to maximize the fact that cigarettes are orders of magnitude the most harmful of all tobacco delivery systems. Second, harm minimization can support use of substantially less harmful but appealing alternatives to substitute for lethal cigarettes for those users who are unable or unwilling to quit smoking. A future end-game might prudently manage emerging new products like e-cigarettes to help boost the difference in harm between them and lethal cigarettes. Harm minimization could help to accelerate the end of the century-long dominance of the cigarette in what has been called “the golden holocaust”. Rather than these emerging delivery devices being used to replace lethal cigarettes in what might be termed a David versus Goliath strategy to disrupt the status quo, there is also legitimate concern that these new products could undermine historically successful tobacco control efforts, especially youth prevention, if allowed free reign. What can the data really tell us about the potential for e-cigarettes to be helpful or harmful? The emerging but limited scientific evidence and the inherent methodological constraints in study designs, points to the need for caution in prematurely interpreting results in a manner that could mislead policymakers.