2 enacted a statewide smoke-free air law in July 2003 banning smoking in all workplaces and restaurants, but exempting free-standing bars. Florida had no county-level compre- hensive smoke-free air laws in place before the statewide law was enacted. New York also passed a statewide smoke- free air law in July 2003, covering free-standing bars in addition to workplaces and restaurants. New York’s 2003 comprehensive law followed signiﬁcant local-level smoke- free air policy enactment, such that by 2003, 75% of New York’s population was covered by local laws stronger than an earlier state law passed in 1985. The comprehensive local laws in New York included a law banning smoking in all workplaces, restaurants, and bars in New York City that was enacted in March 2003. During the time period covered by this study, Oregon did not have a statewide smoke-free air law. A modest worksite law, enacted in 2001, excluded bars and bar areas within restaurants. Two Oregon localities enacted comprehensive laws during the study period. The cities of Corvallis and Eugene enacted smoke-free air laws in 1998 and 2000, respectively. These ordinances were grandfathered in when the weaker statewide law passed, but preemption barred new comprehensive local laws from being passed after 2001. Oregon has subsequently enacted a statewide workplace, restaurant, and bar smoke-free air law that became eﬀective in January 2009. 2. Methods 2.1. Data. We obtained data on hospital admissions for AMI and stroke from a comprehensive administrative database maintained by the department of health in each state. All nonfederal public and private hospitals certiﬁed for inpatient care are required to submit patient data, including diagnoses, to the central database. We derived admission rates from the diagnosis established at discharge. When AMI or stroke was a secondary diagnosis, it was not used in the calculation of the admission rate. Data from Florida were available on a quarterly basis, whereas data from New York and Oregon were available monthly. The number of years of available data from each state varied from 9 years for Oregon (January 1998–December 2006) to 12 years for New York (January 1995–December 2006) and 17 years for Florida (Quarter 1 1990–Quarter 4 2006). New York data from 1995 to 2004 are the same data used in Juster et al. [9]. An additional 24 months of data from New York are analyzed here. The International Classiﬁcation of Diseases, Ninth Revi- sion, Clinical Modiﬁcation (ICD-9-CM) diagnostic codes 410.00–410.99 identify admissions associated with AMI, and diagnostic codes 430.00–438.99 identify admissions associ- ated with stroke. The number of hospital admissions asso- ciated with AMI and stroke for persons aged 35 or older for the years available was extracted for each county in each state, monthly in New York and Oregon and quarterly in Florida. We combined the number of hospital admis- sions with county population data to calculate the monthly (quarterly in Florida) rate of hospital admissions for each health condition. Rates were age-adjusted to the 2000 U.S. standard population. Age-adjusting the hospital admission Journal of Environmental and Public Health rates controls for diﬀering age distributions of the popula- tions across the three states. Information about local smoking restrictions was pur- chased from the Americans for Nonsmokers’ Rights Foun- dation Local Tobacco Control Ordinance Database (http:// www.no-smoke.org/). The database describes all municipal smoking bans and includes dates of enactment and imple- mentation and speciﬁc restrictions and prohibitions of each. Counties are classiﬁed into one of three mutually exclusive categories based on the strength of the smoking ban in eﬀect in the county in a given month or quarter. A county or state was considered to have a comprehensive smoke-free air law if the law prohibits smoking in all worksites, including restaurants, bars, and other hospitality venues with few or no exceptions. Florida’s 2003 statewide law was considered comprehensive for this analysis despite an exclusion for free- standing bars. Moderate laws were deﬁned as those that restrict smoking in most worksites but provide little or no protection in restaurants and other hospitality venues. A county was considered to have no smoke-free air law if it did not have a moderate or a comprehensive law in place. Counties that had smoke-free air restrictions that applied only to municipal buildings were considered to have no smoke-free air law. Date of enactment for all laws was rounded to the nearest month or quarter. 2.2. Statistical Analyses. Multiple regression analysis was used to model the county-level age-adjusted hospital admis- sion rates for AMI and stroke, separately. All analyses were conducted using Stata 11 [10]. The key explanatory variables in all models are an indicator for comprehensive smoke-free air law, an indicator for moderate smoke-free air law, and interactions of these terms with a linear time trend. The smoke-free air indicators are interpreted as the main eﬀect of comprehensive and moderate smoke-free air laws on hospital admissions, measuring a one-time, immediate increase or decrease in rates at the time the law was enacted. The interaction between the smoke-free air law main eﬀects and the time trend measures continued rate changes following the implementation of the law. Each model also includes an indicator for month (quarter for Florida) to control for seasonal eﬀects. Unobserved, time-invariant county-level factors that are correlated with rates of cardiovascular disease risk and other conditions were controlled for by county indicator variables. To control for county-speciﬁc secular changes over time, we included interactions of the county indicator variables with the linear time trend. Estimated regression coeﬃcients were used to predict the number of hospital admissions for AMI and stroke averted as a result of implementation of comprehensive smoke-free air laws. We ﬁrst predicted monthly (or quarterly for Florida) rates of hospital admissions using the full model; this is the baseline case. We then set the comprehensive smoke-free air law indicator and comprehensive law-time interaction coeﬃcients equal to zero beginning the month (or quarter) when a comprehensive smoke-free air law went into eﬀect in each county and repredicted hospitalization rates; this is the counterfactual case. Because the regression coeﬃcients for the comprehensive law main and interaction eﬀects