Comprehensive smoking bans and acute myocardial infarction among Medicare enrollees in 387 US counties: 1999-2008

Abstract

Restrictions on smoking in public places have become increasingly widespread in the United States, particularly since the year 2005. National-scale studies in Europe and local-scale studies in the United States have found decreases in hospital admissions for acute myocardial infarction (AMI) following smoking bans. The authors analyzed AMI admission rates for the years 1999-2008 in 387 US counties that enacted comprehensive smoking bans across 9 US states, using a study population of approximately 6 million Medicare enrollees aged 65 years or older. Effects of smoking bans on AMI admissions were estimated by using Poisson regression with linear and nonlinear adjustment for secular trend and random effects at the county level. Under the assumption of linearity in the secular trend of declining AMI, smoking bans were associated with a statistically significant ban-associated decrease in admissions for AMI in the 12 months following the ban. However, the estimated effect was attenuated to nearly zero when the assumption of linearity in the underlying trend was relaxed. This analysis demonstrates that estimation of potential health benefits associated with comprehensive smoking bans is challenged by the need to adjust for nonlinearity in secular trend.

Figure 1.

Monthly acute myocardial infarction (AMI) hospitalization rates per 100,000 Medicare enrollees, averaged across all counties within each US state and all months within each year, 1999–2008. The symbol “x” is used to represent years where greater than 90% of the counties in the state had a simultaneous ban on smoking in restaurants, bars, and workplaces for at least 6 months. AZ, Arizona; DE, Delaware; IL, Illinois; MA, Massachusetts; MN, Minnesota; NJ, New Jersey; NY, New York; OH, Ohio; WA, Washington.

Figure 2.

Four models for the secular trend in monthly acute myocardial infarction (AMI) rates along with the estimated ban effect, using data from Illinois, 1999–2008. A linear model (thick line) and splines with 0, 0.1, 0.3, and 0.5 df/year of data (thin lines) were used to estimate the nonlinear components of the spline; increasing flexible lines correspond to higher degrees of freedom. Lines showing estimated secular trend transition from solid to dashed in the month when comprehensive smoking bans are implemented. Estimated impacts of smoking bans on AMI rates are visible as discontinuities between solid and dashed lines.

Figure 3.

The estimated percent decrease in acute myocardial infarction (AMI) admissions (and 95% confidence interval) associated with smoking bans, pooled across US states, 1999–2008, for 9 models with increasing degrees of smoothness in secular trend. The Akaike Information Criterion (AIC) under each of the 9 models is also shown as connected dots. The AIC scale is shown on the right, vertical axis. These models included adjustments for seasonality, gender, and age group.