As I discussed over a year ago (here ), claims that smoking bans result in enormous declines in hospitalizations for heart attacks (acute myocardial infarction, AMI) are largely based on selective data from small communities. In addition, these studies rarely control for the virtually continuous decline in heart attack incidence and mortality in the U.S. for the past 50 years.
Yet another far-fetched claim has been published: researchers at the Mayo Clinic, led by Dr. Richard Hurt from the Nicotine Dependence Center, believe that smoking bans in 2002 and 2007 in Olmsted County, Minnesota were responsible for a whopping 33% decline in AMI incidence (abstract here ). I previously detailed misinformation about smokeless tobacco emanating from that organization ( here ). Dr. Michael Siegel at Boston University has expertly critiqued the scientific credibility of this study in two blog posts ( here and here ). No other commentary is necessary.
In contrast to cherry-picked data from tiny communities with no adjustment for declining AMIs, a recent study of 6 million Medicare enrollees from 387 counties in 9 states was conducted by Christopher D. Barr and colleagues at Harvard University and the University of Southern California (abstract here ). They noted that “One particularly challenging issue is to carefully estimate the effect of a ban in the context of the ongoing trend of declining cardiovascular disease morbidity and mortality. If adequate adjustment is not made for the secular trend, the estimated health effects associated with the smoking ban may be biased.” They used the term “biased,” but “grossly exaggerated” would have been more accurate.
Barr and colleagues note that “the mean AMI rate across states dropped about 28% during the years 1999-2008.” They show that studies claiming that a smoking ban leads to fewer AMIs must account for this declining AMI incidence. Although some investigators have tried to make adjustment for the decline, they have assumed that it is a linear phenomenon. Barr writes that “National data show a curvilinear decline during the years of this study,…” which is not a straight-line (or linear) trend.
Barr and colleagues concluded that “the estimated effect [of smoking bans] was attenuated to nearly zero when the assumption of linearity in the underlying trend was relaxed.” In other words, when the effect of smoking bans was effectively adjusted for the underlying decline in AMI, “…the estimated ban effect, pooled across states, is indistinguishable from zero…”