Secondhand Smoke Exposure and Cardiovascular Effects Making Sense of the Evidence (2010) / Chapter Skim
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7 Synthesis of Key Studies Examining the Effect of Smoking Bans on Acute Coronary Events
7 Synthesis of Key Studies Examining the Effect of Smoking Bans on Acute Coronary Events
Pages 163-200
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From page 163... ...
Those are all discussed in this section. When reviewing the key studies, the committee kept in mind the characteristics that would make an ideal study to evaluate the effect of an intervention, a smoking ban, on an outcome, acute coronary events.
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From page 164... ...
Although the 11 studies discussed here are observational studies and have limitations inherent to observational studies, it is important that the studies took advantage of natural experiments to directly evaluate the effects of an intervention (a smoking ban and concomitant activities) on a health outcome of interest (acute coronary events)
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From page 165... ...
SYNTHESIS OF KEY STUDIES TABLE 7-1 Continued Characteristics Ideal Research Challenges to Consider • Occurs at clearly defined • Investigators have no control Smoking-ban intervention time over terms or timing of • No other activities occur smoking-ban legislation, at same time that could implementation, or enforcement affect smoking rates or secondhand-smoke exposure • Need for exposure • If study is prospective, Exposure assessment assessment depends on study design can include air hypothesis tested monitoring or biomonitoring • Exposure data not needed before and after implementation to test effect of smoking of smoking ban, but increases ban costs and biomonitoring • Exposure data needed to requires more complex human test effect of secondhand- subjects approval smoke exposure • Both morbidity and • Access to data is sometimes Outcome mortality data analyzed inadequate • Confirmation of acute • It is often not practical to coronary event: have autopsies conducted on • Mortality data all cases unless sample is very confirmed by autopsy or small • Conducting an independent independent review of medical records review of mortality data or • Acute MI data clinically confirming morbidity independently confirmed data with standardized criteria clinically with is possible but would increase standardized criteria costs and require more complex human-subjects approval • In absence of independent review, data are only as good as what is recorded • Time between • Period between implementation Time between implementation and implementation and effect is and effect is difficult to effect clear establish because intervention does not occur at clearly defined time (because of other activities concurrent with ban) ; effect may increase over time because, for example, there are gradual changes in smoking behavior Continued
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From page 166... ...
SECONDHAND SMOKE EXPOSURE TABLE 7-1 Continued Characteristics Ideal Research Challenges to Consider • Both comparison population • Use of external control Comparison group (external control) and same population depends on population before and availability of comparable after implementation of population intervention are used • Effect being tested is • Identifying research designs that Biologic plausibility biologically plausible can address biologic plausibility • In hypothesis-generating studies, biologic plausibility is not always known before study is designed Experimental design • Experimental designs • It would not be possible are typically best able to ethically to test effect of demonstrate cause–effect secondhand smoke on acute relationship MIs experimentally • Hypothesis being tested is • Studies are designed to test Hypothesis clarification clearly stated specific hypothesis; users of • Tested hypothesis matches study results should consider question being asked in study hypothesis when interpreting results determining what questions study can answer • Appropriate statistical • Statistical analysis is generally Statistical Design analysis, determined under control of researchers a priori, controls for designing study, but appropriate confounders options could be limited by • Statistical models can be characteristics of available data • If appropriate data are used to control for potential confounders and trends available, choice of model and • Statistical modeling includes assumptions are under control description of modeling of researchers assumptions and sensitivity analysis of impact of model choice and assumptions on modeling results • Negative results are less • Both researchers and journal Publication bias apt to be published than editors should overcome their positive findings preference for publishing positive findings a A study typically cannot attain the ideal for all characteristics, so researchers must weigh the importance of each characteristic and the availability of data when determining study design.
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From page 167... ...
had information on the smoking status of cases; therefore, only those two directly addressed the question of the effect of secondhandsmoke exposure on nonsmokers rather than the question of the effect of a smoking ban. In both of these studies a decrease in coronary events was observed among nonsmokers after implementation of the smoking ban.
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From page 168... ...
The extent of migration in the communities studied most likely varied from study to study. However, as mentioned in Chapter 1, migration would be expected to decrease the effects of smoking bans on acute coronary events in studies unless smokers were selectively moving out of areas with bans and into areas without bans.
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From page 169... ...
Some compared acute cardiovascular events in a given population before and during smoking bans (internal control group)
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From page 170... ...
That is, decreases in adverse health effects that occur with the implementation of a ban cannot necessarily be attributed to the specific legislation; other activities, such as voluntary bans in households or outreach programs, could underlie the effects. Exposure Assessment To address its charge, the committee must consider the effects of smoking bans and the effects of decreases in secondhand-smoke exposure.
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From page 171... ...
Without that information, the committee could not determine whether acute exposures were triggering acute coronary events, chronic exposures were causing continuing damage that eventually resulted in acute coronary events, or a combination of chronic damage and acute exposure led to acute coronary events. Although many of the key publications do not contain air-monitoring or biomarker data to assess the changes in secondhand smoke after ban implementation, other publications on the implementation of smoking bans, either in the regions examined in the key studies or in other regions, show that secondhand smoke decreases after implementation of a ban (see Chapter 2)
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From page 172... ...
The concentration of secondhand-smoke–related compounds was lower in nonsmoking restaurants than in restaurants that permitted smoking in separate rooms. On the basis of those data, the committee concludes that, with the exception of some establishments in Bowling Green, Ohio, the smoking bans evaluated in the key studies appear to have resulted in a large decrease in potential exposure to secondhand smoke.
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From page 173... ...
The ICD system is revised about every 10 years, and both ICD- and ICD-0 were in use in some countries in the key studies under review.1 Regardless of whether ICD- or ICD-0 is used, physicians and others typically list all causes of death and list the underlying cause of death last on the death certificate.2 Regardless of the ICD code, that is often done incorrectly; coders using death certificates for gathering statistics are directed in the ICD rules to select the listed underlying cause of death only if it could have given rise to all the other conditions listed as among the causes of death. Otherwise, they are to determine a logical sequence of events that could have led to death and select the underlying cause of the sequence, disregarding "ill-defined conditions." In that respect, a change between ICD- and ICD-0 is of potential relevance to this review: in ICD0, for the first time, the diagnosis "cardiac arrest, unspecified," I46.9, is regarded as ill-defined.
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From page 174... ...
In general, multiple studies have demonstrated that there are inaccuracies in the diagnosis of acute coronary events in medical records. A recent ecologic study in Texas found that only 401 of 496 cases of "definite myocardial infarction" met diagnostic criteria3 for acute MI developed by the 3 The criteria are based on electrocardiograms, cardiac enzymes, and cardiac pain as recorded in medical records.
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From page 175... ...
In relation to the key studies reviewed by the committee that only changes in diagnostic criteria that occurred during the timeframe of the study would affect the results of the study, and would only be relevant to studies that compared the same region before and after a smoking ban. All the key studies compare acute MIs before and after the ban, and the timeframes of all but two of the key studies (Barone-Adesi et al., 2006; Pell et al., 2008)
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From page 176... ...
16–18%) after implementation of smoking ban 0–12 monthsc Cesaroni et al., 2008 11% decrease in 35- to 64(Rome, Italy)
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From page 177... ...
fewer (New York state) admissions in 2004 than expected with just local smoking bans implemented; 19% (estimated)
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From page 178... ...
However, given the blurred timing of the interventions and the numerous differences among the studies -- such as in the characteristics of the smoking bans, in the implementation of smoking restrictions or bans before implementation of the bans under study, and in background rates of smoking and acute MIs -- the key intervention studies do not provide strong evidence on which to establish a more precise time between an intervention and a decrease in risk of acute MI. Plausibility As the key studies showing reductions in acute MIs after implementation of smoking bans were published, some skepticism was expressed as to the believability or likelihood of the effects, whether a detectable change in heart attacks could possibly be associated with banning smoking in public places and offices, and whether the magnitude of the effect could be as high as seen in some of the studies.
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From page 179... ...
The data support a role of secondhand smoke as a potential causative agent in acute coronary events, that is, they constitute evidence that it is biologically plausible for secondhand smoke to be a causative agent in cardiovascular disease and acute coronary events. Plausibility of Magnitude of an Effect When considering the plausibility of the magnitude of the effect, the committee looked at the effects seen in the studies that examined the effects of secondhand smoke and the implementation of smoking bans compared with studies that examined the effects of smoking, and with studies that examined the effects of PM in air pollution.
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From page 180... ...
. Therefore, the increase in risk of acute MI associated with secondhand-smoke exposure in the case–control studies and the decrease in risk of acute MI seen after implementation of smoking bans are about the same or smaller than those seen with a low level of current smoking and substantially smaller than those seen with current heavy smoking.
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From page 181... ...
Therefore, the estimates do not represent the potential public-health impact of secondhand smoke but are provided to put the decreases in hospital admissions seen in the key studies that evaluated the effect of smoking bans in the context of the health effects of one of the constituents of secondhand smoke. For each scenario, the committee calculated, on the basis of published data, the daily average concentration of ambient PM2.5.
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From page 182... ...
Upper Estimate) Nonsmoking workplace, nonsmoking home (reference concentration, assuming 16 h at home, 17 μg/m3)
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From page 183... ...
50,021 (31,389, 2 h at pub or bar 68,286) a Committee calculated changes in particulate-matter exposures for different exposure sce narios and estimated corresponding changes in risk of cardiovascular-disease admissions due to those changes and corresponding reductions in annual hospital admissions in 204 largest urban counties on basis of hospital admissions data from U.S.
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From page 184... ...
Upper Estimate) Nonsmoking workplace, nonsmoking home (reference concentration, assuming 16 h at home, 17 μg/m3)
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From page 185... ...
For each scenario, it calculated the difference in 24-hour average PM2.5 exposure that would result from smoking bans for those who lived with smokers and for those who lived in smoke-free homes. The committee used data on changes in daily exposure to PM2.5 and cardiovascular diseases from epidemiologic studies of the Medicare population (which includes only people at least 65 years old)
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From page 186... ...
Upper Estimate) Nonsmoking workplace, nonsmoking home (reference concentration, assuming 16 h at home, 17 μg/m3)
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From page 187... ...
36,553) a Committee calculated changes in particulate-matter exposures for different exposure sce narios and estimated corresponding changes in risk of heart failure due to those changes and corresponding reductions in annual hospital admissions in 204 largest urban counties on basis of hospital admissions data from U.S.
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From page 188... ...
. Those estimates indicate that changes in individual PM exposure that would be expected after implementation of smoking bans would be expected to result in substantial reductions in hospital admissions, and this implies that the results seen in the 11 key studies are plausible.
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From page 189... ...
but fitted the regression model to the data from before implementation of a smoking ban and predicted the outcome after implementation. Scenario assumed that the underlying trend, common to all the counties, is a spline with 3 degrees of freedom for the entire period 1999–2006 (as in Scenario 2)
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From page 190... ...
. If the assumption of linearity is relaxed, the results change substantially because the committee is estimating the trend for the entire study period, that is, using data from before and after 3,800 3,600 3,400 Number of Admissions 3,200 3,000 2,800 2,600 2,400 2,200 Without Statewide Ban Observed Admissions 2,000 99 00 01 02 03 04 05 06 07 Year FIGuRE 7-1 Observed admissions for acute MI and those predicted without statewide smoking ban on basis of Scenario 1.
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From page 191... ...
7-2 rev.eps 3,800 3,600 3,400 Number of Admissions 3,200 3,000 2,800 2,600 2,400 2,200 Predicted Admissions Observed Admissions 2,000 99 00 01 02 03 04 05 06 07 Year FIGuRE 7-3 Observed admissions for acute MI and those predicted on basis of Scenario 3. The dashed vertical line indicates when during 2003 the statewide ban was implemented.
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From page 192... ...
7-4 rev.eps 200 Crude Hospitalization Rate (per 100,000) 180 160 140 120 Smooth Function of Time Observed Admission Rate 100 99 00 01 02 03 04 05 06 07 Year FIGuRE 7-5 Crude acute MI hospitalization rate (per 100,000)
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From page 193... ...
Given that model choice can affect the results substantially, it is important to discuss the rationale for and the sensitivity of the results to the choice of model in publications, especially for more statistically sophisticated analyses. Publication Bias The published studies all showed some statistically significant evidence that smoking bans reduced the risk of cardiovascular disease events.
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From page 194... ...
The National Association of City and County Health Officials Web site was also searched to determine whether other studies had been initiated, and the committee requested information from the Centers for Disease Control and Prevention and AHA on other studies that were under way or had been conducted and never published; no such studies were identified. There is still the possibility that studies showing no association were conducted but not published; this would bias the data toward there being an association between secondhand-smoke exposure or smoking bans and acute coronary events.
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From page 195... ...
In summary, the studies all appear to have found substantial reductions in acute cardiovascular events after the implementation of smoking bans and in that sense were consistent, but separately and collectively they had statistical shortcomings. The committee concludes that the shortcomings
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From page 196... ...
. • Analyses that showed decreases in secondhand smoke after im plementation of smoking bans.
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From page 197... ...
2008. Effect of the Italian smoking ban on population rates of acute coronary events.
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From page 198... ...
2007. Declines in hospital admissions for acute myocardial infarction in New York state after implementation of a comprehensive smoking ban.
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From page 199... ...
1996. An assessment of the validity of ICD code 410 to identify hospital admissions for myocardial infarction: The Corpus Christi Heart Project.
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From page 200... ...
2007. Reduced admissions for acute myocardial infarction as sociated with a public smoking ban: Matched controlled study.
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