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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Arch Intern Med. Author manuscript; available in PMC 2013 November 26.
Published in final edited form as:
PMCID: PMC3615114
NIHMSID: NIHMS436541

Myocardial Infarction and Sudden Cardiac Death in Olmsted County, Minnesota, Before and After Smoke-Free Workplace Laws

Abstract

Background

Reductions in admissions for myocardial infarction (MI) have been reported in locales where smoke-free workplace laws have been implemented, but no study has assessed sudden cardiac death (SCD). In 2002, a smoke-free restaurant ordinance was implemented in Olmsted County, Minnesota, and in 2007, all workplaces including bars became smoke free.

Methods

To evaluate the population impact of smoke-free laws, we measured, through the Rochester Epidemiology Project, the incidence of MI and SCD in Olmsted County during the 18-month period before and after implementation of each smoke-free ordinance. All MIs were continuously abstracted and validated using rigorous standardized criteria relying on biomarkers, cardiac pain, and Minnesota coding of the electrocardiogram. SCD was defined as out-of-hospital deaths assigned to coronary disease.

Results

Comparing the 18 months before the implementation of the smoke-free restaurant ordinance to the 18 months after the implementation of the smoke-free workplace law, the incidence of MI declined by 33% (P<0.01) from 150.8 to 100.7 per 100,000 population, and the incidence of SCD declined by 17% (P=0.13) from 109.1 to 92.0 per 100,000 population. During the same period, the prevalence of smoking declined while that of hypertension, diabetes, hypercholesterolemia, and obesity either remained constant or increased.

Conclusions

A substantial decline in the incidence of MI was observed after smoke-free laws were implemented, the magnitude of which is not explained by community co-interventions or changes in cardiovascular risk factors with the exception of smoking prevalence. As trends in other risk factors do not appear explanatory, smoke-free workplace laws seem ecologically related to these favorable trends. Secondhand smoke (SHS) exposure should be considered a modifiable risk factor for MI. All people should avoid SHS to the extent possible, and people with known coronary heart disease should have no exposure to SHS.

INTRODUCTION

Secondhand smoke (SHS) exposure is associated with coronary heart disease (CHD) in nonsmokers, and a nonlinear dose relationship exists such that SHS exposure has a larger than expected adverse effect at low levels of exposure.1 Research suggests that the cardiovascular effects of SHS are nearly as large as active smoking.1 Indeed, the magnitude of endothelial dysfunction in nonsmokers approaches that noted in active smokers2 and may only be partially reversible.3 The 2006 U.S. Surgeon General’s Report underscored the negative impact of SHS stating that “exposure to SHS has immediate effects on the cardiovascular system.”4 An estimated 46,000 nonsmoking Americans die annually from cardiovascular events related to SHS.5 Eliminating smoking in public places holds potential for improving public health and reducing cardiovascular events beyond the expected impact of the reduction in active smoking.6 Finding additional scientific data in support of smoke-free policies will help ensure their continuation and encourage locales without such laws to consider them.

Several studies described a decline in admissions for myocardial infarction (MI) after implementation of smoke-free legislation,714 and a meta-analysis of 17 published studies reported a 10% reduction in admissions for MI after the implementation of such legislation.15 An expert committee from the Institute of Medicine concluded: “That there is a causal relationship between smoking bans and decreases in acute coronary events,” but the committee did not determine the magnitude of the decrease in relative risk.16 The 10-member committee concluded that none of the reports to date were of ideal design. In order to evaluate the population effect of the implementation of smoke-free laws on cardiovascular events, we examined data from the Rochester Epidemiology Project (REP) including individual patient data for MI cases validated using rigorous epidemiological criteria and sudden cardiac death (SCD) in Olmsted County, Minnesota, before and after implementation of smoke-free workplace laws.

METHODS

Study Setting

Olmsted County, located in southeastern Minnesota, has a population of 144,248 (86% white, 51% female).17 Only a few providers (chiefly Mayo Clinic and Olmsted Medical Center) deliver nearly all medical care to county residents. Medical records used by each provider capture information for all encounters and can be retrieved from indices based on all diagnoses and procedures maintained by Mayo Clinic.18 This results in the linkage of medical records from all sources of care, providing a unique infrastructure to analyze disease occurrence and outcomes at the population level. Potential cases identified through the REP can then be validated by applying standardized methods appropriate for each disease entity. This process has been implemented for extensive cardiovascular disease epidemiology research.1922

In Olmsted County. a smoke-free restaurant law which did not include bars or other workplaces (Ordinance 1) was implemented on January 1, 2002, and on October 1, 2007, all workplaces (including bars) became smoke-free (Ordinance 2).

Ascertainment of Myocardial Infarction

Potential cases included patients admitted to Olmsted County hospitals who were assigned the International Classification of Disease, Ninth Revision code 410 (acute MI). Infarctions were validated after manual data collection of relevant information and using algorithms integrating cardiac pain, electrocardiographic (ECG) and biomarker data (creatine kinase [CK] and MB fraction of creatine kinase [CKMB]).23, 24 Biomarker values were recorded for up to three measurements on each of the first three days following admission or infarction onset, if the patient was already hospitalized.25, 26 All biomarkers were measured with a sandwich electrochemiluminescence immunoassay on the Elecsys 2010 (Roche Diagnostics Corporation; Indianapolis, IN), in the certified laboratories of the Department of Laboratory Medicine and Pathology at Mayo Clinic in Rochester, MN, with robust quality control in place. Three ECGs per episode were coded using the Minnesota Code Modular ECG Analysis System.27 Only first ever MIs were considered as incident. All MIs were continuously abstracted for the entire duration of this study. These methods have been used in our coronary disease surveillance work for more than a decade with excellent reliability.23, 25, 28

Ascertainment of Sudden Cardiac Death

Our methods of ascertaining SCD have been previously published.22, 29 In brief, SCD was defined as out-of-hospital deaths with the primary cause of death classified as coronary heart disease on the death certificate (International Classification of Diseases, Ninth Revision codes 410–414).29

Clinical Data

Baseline demographic and clinical characteristics were collected from the medical records by nurse abstractors at the time of MI diagnosis or SCD. Clinicians’ diagnoses were used to define hypertension, hyperlipidemia, diabetes, familial CHD, and smoking status. Body mass index (BMI) (kg/m2) was calculated using height and weight.

Smoking Prevalence and Other Cardiovascular Risk Factors

We utilized Behavioral Risk Factor Surveillance System (BRFSS) data from Minnesota adults for self-reported current smoking prevalence, hypercholesterolemia, diabetes, hypertension, and obesity (BMI ≥ 30).30 The BRFSS is a state-based system of health surveys collecting information on health risk behaviors, preventive health practices, and health care access primarily related to chronic disease and injury. Telephone interviews are conducted with more than 350,000 adults in all 50 states, the District of Columbia, and US territories.31 No Olmsted County-specific data for these risk factors exist.

Statistical Analysis

Unadjusted and age- and sex-adjusted incidence rates of MI and SCD were calculated for the 18 months before and 18 months after the implementation of each smoking law. The counts of events were used as the numerators and the denominators were the Olmsted County population as determined by census data for the years 1990, 2000, and 2010 with linear interpolation for intercensal years. Adjusted rates were directly standardized to the age and sex distribution of the 2000 US population. Standard errors and 95% confidence intervals (CI) were calculated based on the Poisson error distribution. Differences in incidence in the 18 months before and after each law were assessed with Poisson regression adjusting for age and sex and using an indicator variable with a value of 0 or 1 for the 18 months before and after the law, respectively. Specific counts for each time period, age, and sex were used as the unit of observation with the time period-, age- and sex-specific Olmsted County population as the offset. Interactions between age and time period were assessed to determine whether changes in incidence rates were dependent on age, and in all cases, no significant interactions were detected.

Cause of death was missing for 128 (3.7%) of the 3480 persons who died out-of-hospital during the 18 months before and after each smoke-free ordinance. To account for these missing data, multiple imputation methodology was used to create 5 complete imputed datasets.32 Analyses were performed for each imputed dataset, and the results were combined using Rubin’s rules.33 Nonlinear trends over time were explored using data from all years from 1995 to 2009. For these analyses, Poisson regression models were generated with the use of generalized additive models34 with calendar year as a smoothed term.

Analyses were performed using SAS version 9.2 (SAS Institute Inc, Cary, NC) and R. All aspects of the study were approved by the Mayo Clinic Institutional Review Board.

RESULTS

Patient Characteristics

During the 18 months before and after each smoke-free ordinance, there were a total of 717 incident cases of MI and 514 people who experienced SCD. Demographic and clinical characteristics for the MI and SCD patients are presented in Table 1. No characteristics were found to differ significantly between pre- and post-ordinance time periods except for hyperlipidemia in persons experiencing SCD before and after Ordinance 1 (36.4% versus 54.0%, respectively; P=0.004).

Table 1
Patient Characteristics

Incidence of Myocardial Infarction

The age- and sex-adjusted rate of MI was 150.8 per 100,000 (95% CI, 129.0–172.6) for the 18 months prior to Ordinance 1 and 144.6 per 100,000 (95% CI, 123.6–165.5) for the 18 months after Ordinance 1 (Table 2). The incidence of MI did not significantly decline during this time period (age- and sex-adjusted RR 0.96; 95% CI, 0.78–1.18; P=0.71).

Table 2
Incidence Rates and Relative Risks of MI and SCD 18 Months Pre- and Post-Smoke-free Laws

Conversely, for the time period surrounding Ordinance 2, the incidence of MI adjusted for age and sex declined from 152.3 per 100,000 (95% CI, 131.4–173.3) to 100.7 per 100,000 (95% CI, 83.8–117.5). This equated to a 34% decline over the 18 months before and after the implementation of Ordinance 2 (adjusted RR 0.66; 95% CI, 0.53–0.82; P<0.01).

Over the entire study period comparing 18 months before Ordinance 1 and 18 months after Ordinance 2, we observed a 33% decline in the incidence of MI (adjusted RR 0.67; 95% CI, 0.53–0.83; P<0.01).

The annual unadjusted MI incidence rates from 1995–2009 are presented in Figure 1. A smoothing spline with 95% CI is superimposed on the actual rates. The test for nonlinearity was significant (P<0.01), with an inflection point occurring around year 2005.

Figure 1
Incidence of MI and SCD in Olmsted County, Minnesota, 1995–2009, with smoothing spline and 95% confidence intervals.

Incidence of Sudden Cardiac Death

No decline in SCD was observed for the 18 months before and after Ordinance 1 (adjusted RR 1.01; 95% CI, 0.80–1.27; P=0.96), with the age- and sex-adjusted rates of SCD being 109.1 per 100,000 (95% CI, 91.0–127.2) and 112.7 per 100,000 (95% CI, 94.3–131.0), respectively (Table 2). Similarly, there was not a significant change in rates of SCD 18 months before Ordinance 2 compared to the 18 months after Ordinance 2 (adjusted RR 1.17; 95% CI, 0.91–1.51; P=0.22). The age- and sex-adjusted rate of SCD was 78.8 per 100,000 (95% CI, 64.0–93.5) 18 months before the ordinance and 92.0 per 100,000 (95% CI, 75.7–108.3) 18 months after the ordinance.

There was a 17% decline in the incidence of SCD for the overall study period comparing the 18 months before Ordinance 1 to the 18 months after Ordinance 2 (RR 0.83; 95%CI, 0.65–1.06; P=0.13).

The annual SCD rates from 1995–2009 are presented in Figure 1. A smoothing spline with 95% CI is superimposed on the unadjusted rates. The P value for the test for nonlinearity was 0.086.

Smoking Prevalence and Other Cardiovascular Risk Factors

Based on the Minnesota BRFSS data, the self-reported smoking prevalence among adults decreased from 19.8% in 2000 to 14.9% in 2010 while the prevalence of diabetes and obesity increased and the prevalence of hypertension and hypercholesterolemia remained flat30 (Figures 2 and and33).

Figure 2
Prevalence of Self-Reported Current Smoking in Minnesota, 1995–2010 from Behavioral Risk Factor Surveillance System Survey Data30
Figure 3
Prevalence of self-reported high cholesterol, diabetes, hypertension and obesity in Minnesota, 1995–2010 from Behavioral Risk Factor Surveillance System Survey Data30

DISCUSSION

We report a substantial decline in the incidence of MI from 18 months before the smoke-free restaurant law was implemented, to 18 months after the comprehensive smoke-free workplace law was implemented 5 years later. Our observed decrease in the incidence of MI is similar to the 40% decrease in the incidence of MI in the first report in Helena, Montana.7 In a large study which included biomarker confirmation, the decrease in the rate of admission to Scottish hospitals decreased by 19%.14 This study was limited by its inclusion of only 9 hospitals which accounted for 64% of the country’s hospital admissions; thus the rates were not true incidence rates, and the time frame was much shorter than ours.

The mechanisms of the deleterious effect of SHS are diverse. As little as five minutes of exposure to SHS in nonsmokers reduces aortic distensibility35 and abdominal aortic stiffness is increased with SHS exposure in children.36 In nonsmokers, thirty minutes of SHS exposure produces an abrupt and dramatic reduction in coronary artery flow velocity reserve.37 Thirty minutes of SHS exposure leads to vascular injury characterized by mobilization of dysfunctional endothelial progenitor cells with blocked nitric oxide production, which is essential to endothelial function as its release mediates vasodilatation.38 SHS exposure in nonsmokers has been associated with lower HDL levels, increased markers of inflammation, increased serum fibrinogen and homocysteine, decreased antioxidant levels, and increased insulin resistance.3943

Causal Inference

While not embodying the “ideal design” as described by the Institute of Medicine report,16 our study addresses some key limitations by reporting data from a defined community with a large sample size and a prolonged period of observation. As our data constitute before-after comparisons in the absence of a comparison geographic area in which no smoke-free law has been implemented, its interpretation should also explicitly consider alternative causes of changes in MI incidence. To this end, the new diagnostic criteria for MI were deployed in 2000, and we have reported that these new criteria increased the number of MIs25, 26 and thus could mask a decline in incidence. The present results, however, are not contaminated by the change in biomarkers as all MIs were confirmed with CK/CKMB. No concurrent intervention could explain the observed trends during the time period of the study. In particular, while automated external defibrillators have been increasingly used in the city of Rochester, MN, the concurrent incidence of ventricular fibrillation out-of-hospital cardiac arrest had begun to level off prior to the implementation of the first smoke-free law.44 Further, the prevalence of smoking declined (Figure 2) while the rate of hypertension and hypercholesterolemia remained essentially constant, whereas the rate of diabetes and obesity increased30 (Figure 3).

Finally, one important consideration is the interpretation of the trends reported herein in light of known secular trends. Although the incidence of SCD has been declining over the past thirty years, the decrease in the incidence of SCD and MI accelerated over the time period of the implementation of these smoke-free workplace laws. There were other tobacco control activities in Minnesota during the time frame of this study including a 2001 mass media campaign focused on helping smokers to stop smoking using a tobacco quitline or clinic services and a 2004–2007 mass media campaign focused on the hazards of SHS. A 2005 “Health Impact” fee of $0.75 per pack of cigarettes was imposed followed by a $0.62 per pack increase in Federal excise tax. In addition to a decrease in smoking prevalence, during the time period of 1999–2010 were: per capita cigarette sales in Minnesota declined by 40%, and smoke-free homes increased from 64.5% (1999) to 74.8% (2003) and from 83.2% (2007) to 87.2% (2010).45

While the determinants of the secular trend in the incidence of MI and SCD cannot be determined with certainty in ecological analysis, particularly with concomitant other tobacco control activities, the acceleration of the trends (nonlinearity of the smoothing spline analysis for MI), while all other cardiovascular risk factors (except smoking prevalence) were either stable or increasing, support the critical role of smoke-free workplace laws in tobacco control efforts. The impact of smoke-free legislation is multifold: reducing the intensity of smoking among smokers, increasing quit rates, reducing smoking startups by teenagers, and reducing exposure to SHS. Thus, the impact can be expected to occur over a period of time before and after implementation. Previous trends in MI in Olmsted County were stable between 1987 and 2006.26 Herein, we report that MI incidence did not change during the 18 months before and the 18 months after Ordinance 1 (July 2000 - June 2003) which is consistent with these previously published data. Thereafter, there was a substantial decline in MI incidence from the 18 months before compared to the 18 months after Ordinance 2 (April 2006-March 2009) pointing to a notable discontinuity of the MI trends, within a time period where no other obvious factor could have plausibly played a large role.

Limitations and Strengths

Some limitations should be discussed to aid in the interpretation of the data. We examine temporal trends in MI and SCD concomitant to the implementation of smoke-free laws. This design is consistent with a natural experiment with its well-known limitation regarding causal inference. We recognize that misclassification of deaths occurs in death certificates; however, the study focuses on temporal trends which are unlikely to be confounded by the classification of deaths. We do not have county-specific prevalence data for smoking or other risk factors; however, the trends in Olmsted County are usually consistent with those observed in the Minnesota data30 (Figures 2 and and3).3). The population of Olmsted County is primarily Caucasian, and further studies are needed in communities of more diverse racial and ethnic composition. Further, we do not have self-reported exposure to SHS nor biochemical markers of SHS exposure, though we expect similar results to the Scottish study where self-reported SHS exposure, confirmed by salivary cotinine, decreased after the smoke-free law was implemented.14

Our study has several major strengths. It was conducted under the auspices of the REP, which has a long track record of robust epidemiological studies for over 50 years. Our results reflect a complete enumeration of the cases of MI and SCD in a well-defined community; and in particular, all MI and SCD cases were validated using rigorous epidemiological criteria.25, 29 The time period over which this study was conducted is longer than reported in most published studies, thereby affording greater power to detect significant trends.

Clinical and Public Health Implications

We believe that SHS could be considered a major risk factor for MI, joining family history, hypertension, hyperlipidemia, diabetes mellitus, and low physical activity. Hence, all clinicians should ascertain SHS exposure and promote the elimination of SHS exposure to their lifestyle recommendations.46 Further, all clinicians should be encouraged to become advocates for effective tobacco control policies such as increased taxes, graphic labeling, smoke-free workplaces, and marketing and advertising restrictions, as smoking and SHS exposure are responsible for 10% of all cardiovascular deaths globally.47

SCD represents 60% of all deaths from CHD, and the majority occur in people previously not diagnosed with CHD who do not meet high-risk criteria as defined by clinical trials and cohort studies.48 Thus, the prevention of SCD hinges upon public health interventions focused on the primary prevention of CHD or the wider availability of automated external defibrillators and implantable cardioverter-defibrillators. We observed a statistically nonsignificant decline in the incidence of SCD which may reflect the relatively smaller number of events in the SCD group. These findings suggest that SHS exposure could be a risk factor for SCD. As this risk factor is highly modifiable, the expansion of smoke-free workplace policies could have a major public health impact by reducing the incidence of SCD.

CONCLUSION

The implementation of smoke-free workplace ordinances was associated with a substantial decreases in MI, the magnitude of which is not explained by community co-interventions or changes in known cardiovascular risk factors with the exception of smoking prevalence. SHS exposure should be considered a modifiable risk factor for MI. All people should avoid SHS exposure, and people with known CHD should have no exposure to SHS.

Acknowledgments

Funding sources:

This study was supported in part by ClearWay Minnesota (PI, RD Hurt); R01 HL59205 from NHLBI/NIH (PI, VL Roger); and R01 AG034676 from NIA/NIH (Rochester Epidemiology Project). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

The authors have no conflicts of interest to declare.

Presented in part at the Annual Meeting of the American Heart Association, Orlando, Florida, November 2011.

Dr. Hurt had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

References

1. Barnoya J, Glantz SA. Cardiovascular effects of secondhand smoke: nearly as large as smoking. Circulation. 2005;111(20):2684–2698. [PubMed]
2. Celermajer DS, Adams MR, Clarkson P, et al. Passive smoking and impaired endothelium-dependent arterial dilatation in healthy young adults. N Engl J Med. 1996;334(3):150–154. [PubMed]
3. Raitakari OT, Adams MR, McCredie RJ, Griffiths KA, Celermajer DS. Arterial endothelial dysfunction related to passive smoking is potentially reversible in healthy young adults. Ann Intern Med. 1999;130(7):578–581. [PubMed]
4. U.S. Department of Health and Human Services. The Health Consequences of Involuntary Exposure to Tobacco Smoke: A Report of the Surgeon General. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Coordinating Center for Health Promotion, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2006.
5. National Cancer Institute, National Institutes of Health. [Accessed June 20, 2011.];Smoking and Tobacco Control Monographs, Monograph 10: Health Effects of Exposure to Environmental Tobacco Smoke. http://cancercontrol.cancer.gov/tcrb/monographs/10/
6. Fichtenberg CM, Glantz SA. Effect of smoke-free workplaces on smoking behaviour: systematic review. BMJ. 2002;325(7357):188. [PMC free article] [PubMed]
7. Sargent RP, Shepard RM, Glantz SA. Reduced incidence of admissions for myocardial infarction associated with public smoking ban: before and after study. BMJ. 2004;328(7446):977–980. [PMC free article] [PubMed]
8. Bartecchi C, Alsever RN, Nevin-Woods C, et al. Reduction in the incidence of acute myocardial infarction associated with a citywide smoking ordinance. Circulation. 2006;114(14):1490–1496. [PubMed]
9. Khuder SA, Milz S, Jordan T, Price J, Silvestri K, Butler P. The impact of a smoking ban on hospital admissions for coronary heart disease. Prev Med. 2007;45(1):3–8. [PubMed]
10. Juster HR, Loomis BR, Hinman TM, et al. Declines in hospital admissions for acute myocardial infarction in New York state after implementation of a comprehensive smoking ban. Am J Public Health. 2007;97(11):2035–2039. [PubMed]
11. Barone-Adesi F, Vizzini L, Merletti F, Richiardi L. Short-term effects of Italian smoking regulation on rates of hospital admission for acute myocardial infarction. Eur Heart J. 2006;27(20):2468–2472. [PubMed]
12. Cesaroni G, Forastiere F, Agabiti N, Valente P, Zuccaro P, Perucci CA. Effect of the Italian smoking ban on population rates of acute coronary events. Circulation. 2008;117(9):1183–1188. [PubMed]
13. Cronin E, Kearney P, Sullivan P. Impact of a national smoking ban on the rate of admissions to hospital with acute coronary syndromes. Eur Heart J. 2007;28(abstract supplement):585.
14. Pell JP, Haw S, Cobbe S, et al. Smoke-free legislation and hospitalizations for acute coronary syndrome. N Engl J Med. 2008;359(5):482–491. [PubMed]
15. Mackay DF, Irfan MO, Haw S, Pell JP. Meta-analysis of the effect of comprehensive smoke-free legislation on acute coronary events. Heart. 2010;96(19):1525–1530. [PubMed]
16. Committee on Secondhand Smoke Exposure and Acute Coronary Events; Institute of Medicine. . Secondhand Smoke Exposure and Cardiovascular Effects: Making Sense of the Evidence. Washington, DC: National Academies Press; 2009.
17. U.S. Census Bureau. [Accessed June 1, 2012.];State & County QuickFacts. Olmsted County, Minnesota. http://quickfacts.census.gov/qfd/states/27/27109.html.
18. Melton LJ., 3rd History of the Rochester Epidemiology Project. Mayo Clin Proc. 1996;71(3):266–274. [PubMed]
19. St Sauver JL, Grossardt BR, Yawn BP, Melton LJ, 3rd, Rocca WA. Use of a medical records linkage system to enumerate a dynamic population over time: the Rochester epidemiology project. Am J Epidemiol. 2011;173(9):1059–1068. [PMC free article] [PubMed]
20. Roger VL, Weston SA, Redfield MM, et al. Trends in heart failure incidence and survival in a community-based population. JAMA. 2004;292(3):344–350. [PubMed]
21. Bursi F, Weston SA, Redfield MM, et al. Systolic and diastolic heart failure in the community. JAMA. 2006;296(18):2209–2216. [PubMed]
22. Adabag AS, Therneau TM, Gersh BJ, Weston SA, Roger VL. Sudden death after myocardial infarction. JAMA. 2008;300(17):2022–2029. [PMC free article] [PubMed]
23. Roger VL, Killian J, Henkel M, et al. Coronary disease surveillance in Olmsted County objectives and methodology. J Clin Epidemiol. 2002;55(6):593–601. [PubMed]
24. White AD, Folsom AR, Chambless LE, et al. Community surveillance of coronary heart disease in the Atherosclerosis Risk in Communities (ARIC) Study: methods and initial two years’ experience. J Clin Epidemiol. 1996;49(2):223–233. [PubMed]
25. Roger VL, Killian JM, Weston SA, et al. Redefinition of myocardial infarction: prospective evaluation in the community. Circulation. 2006;114(8):790–797. [PubMed]
26. Roger VL, Weston SA, Gerber Y, et al. Trends in incidence, severity, and outcome of hospitalized myocardial infarction. Circulation. 2010;121(7):863–869. [PMC free article] [PubMed]
27. Kors JA, Crow RS, Hannan PJ, Rautaharju PM, Folsom AR. Comparison of computer-assigned Minnesota Codes with the visual standard method for new coronary heart disease events. Am J Epidemiol. 2000;151(8):790–797. [PubMed]
28. Roger VL, Jacobsen SJ, Weston SA, et al. Trends in the incidence and survival of patients with hospitalized myocardial infarction, Olmsted County, Minnesota, 1979 to 1994. Ann Intern Med. 2002;136(5):341–348. [PubMed]
29. Goraya TY, Jacobsen SJ, Belau PG, Weston SA, Kottke TE, Roger VL. Validation of death certificate diagnosis of out-of-hospital coronary heart disease deaths in Olmsted County, Minnesota. Mayo Clin Proc. 2000;75(7):681–687. [PubMed]
30. Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System Survey Data. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 1999–2010.
31. Centers for Disease Control. Behavioral Risk Factor Surveillance System. About the BRFSS. [Accessed June 4, 2012];Turning Information Into Public Health. http://www.cdc.gov/brfss/index.htm.
32. Schafer JL, Olsen MK. Multiple imputation for multivariate missing-data problems: a data analyst’s perspective. Multivar Behav Res. 1998;33(4):545–571.
33. Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York: J. Wiley & Sons; 1987.
34. Hastie TJ, Tibshirani RJ. Generalized Additive Models. London: Chapman & Hall; 1990.
35. Stefanadis C, Vlachopoulos C, Tsiamis E, et al. Unfavorable effects of passive smoking on aortic function in men. Ann Intern Med. 1998;128(6):426–434. [PubMed]
36. Kallio K, Jokinen E, Hamalainen M, et al. Decreased aortic elasticity in healthy 11-year-old children exposed to tobacco smoke. Pediatrics. 2009;123(2):e267–273. [PubMed]
37. Otsuka R, Watanabe H, Hirata K, et al. Acute effects of passive smoking on the coronary circulation in healthy young adults. JAMA. 2001;286(4):436–441. [PubMed]
38. Heiss C, Amabile N, Lee AC, et al. Brief secondhand smoke exposure depresses endothelial progenitor cells activity and endothelial function: sustained vascular injury and blunted nitric oxide production. J Am Coll Cardiol. 2008;51(18):1760–1771. [PubMed]
39. Mizoue T, Ueda R, Hino Y, Yoshimura T. Workplace exposure to environmental tobacco smoke and high density lipoprotein cholesterol among nonsmokers. Am J Epidemiol. 1999;150(10):1068–1072. [PubMed]
40. Shima M, Adachi M. Effects of environmental tobacco smoke on serum levels of acute phase proteins in schoolchildren. Prev Med. 1996;25(5):617–624. [PubMed]
41. Tribble DL, Giuliano LJ, Fortmann SP. Reduced plasma ascorbic acid concentrations in nonsmokers regularly exposed to environmental tobacco smoke. Am J Clin Nutr. 1993;58(6):886–890. [PubMed]
42. Henkin L, Zaccaro D, Haffner S, et al. Cigarette smoking, environmental tobacco smoke exposure and insulin sensitivity: the Insulin Resistance Atherosclerosis Study. Ann Epidemiol. 1999;9(5):290–296. [PubMed]
43. Venn A, Britton J. Exposure to secondhand smoke and biomarkers of cardiovascular disease risk in never-smoking adults. Circulation. 2007;115(8):990–995. [PubMed]
44. Agarwal DA, Hess EP, Atkinson EJ, White RD. Ventricular fibrillation in Rochester, Minnesota: experience over 18 years. Resuscitation. 2009;80(11):1253–1258. [PubMed]
45. Centers for Disease Control and Prevention. Morbidity and Mortality Weekly Report. [Accessed June 22, 2012.];Decrease in Smoking Prevalence --- Minnesota, 1999–2010. http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6005a2.htm.
46. Chiuve SE, Fung TT, Rexrode KM, et al. Adherence to a low-risk, healthy lifestyle and risk of sudden cardiac death among women. JAMA. 2011;306(1):62–69. [PMC free article] [PubMed]
47. ITC Project, World Health Organization, and World Heart Federation. Cardiovascular harms from tobacco use and secondhand smoke: Global gaps in awareness and implications for action. Waterloo, Ontario, Canada and Geneva, Switzerland: Apr, 2012.
48. Adabag AS, Luepker RV, Roger VL, Gersh BJ. Sudden cardiac death: epidemiology and risk factors. Nat Rev Cardiol. 2010;7(4):216–225. [PubMed]