Commentary
Clean indoor air laws immediately reduce heart attacks

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Acknowledgment

This work was funded by grants from the National Cancer Institute (CA-113710 and CA-61021). The funding agency had no role in the conduct of the research or preparation of the manuscript.

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  • Clean Indoor Air Acts reduce the burden of adverse cardiovascular outcomes

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    Even admission rates for respiratory diseases (e.g. asthma) decreased significantly following CIAA implementation.13,17 CIAAs were shown to be associated with a 27% reduction [pooled relative risk = 0.73, 95% confidence interval (CI) 0.56–0.89] in hospital admissions for heart disease,4 and a 17% reduction (incidence rate ratio 0.83, 95% CI 0.75–0.92) in AMI risk.15 Additionally, increases in smoking cessation following CIAA implementation have been found to be approximately 6.4%.32

  • Reassessing the evidence relating smoking bans to heart disease

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    The first review considered (Glantz, 2008) presented RRs and 95% CIs from eight studies (Barone-Adesi et al., 2006; Bartecchi et al., 2006; Cesaroni et al., 2008; Cronin et al., 2007; Juster et al., 2007; Khuder et al., 2007; Lemstra et al., 2008; Sargent et al., 2004) citing an overall random-effects estimate of 0.81 (95% CI 0.76–0.86). This was an update of an earlier meta-analysis (Dinno and Glantz, 2007). The review by Lightwood and Glantz (2009) presented RRs and 95% CI’s from eleven studies, citing a similar overall estimate of 0.81 (0.78–0.85).

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    Meta-analysis used the random-effects model in the metanstatistical package in STATA version 10 (Stata Corp., College Station, Texas) (13) because heterogeneity was significant in the fixed effects model (p < 0.001). Unlike previously published meta-analyses, which used average yearly incidence rates (14,15), we weighted studies by person-years, thus considering both population size and duration of observation, and assumed that the incidence of AMI satisfied a Poisson process (16). Because the funnel plot showed systematic heterogeneity among the study results, we performed a meta-regression analysis using the metaregpackage of STATA 10 to examine whether the estimate of incidence rate ratio (IRR) depends on such factors as post-ban duration, population size, or region (U.S. or non-U.S.).

  • Coronary Heart Disease Attributable to Passive Smoking. CHD Policy Model

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    If the excess risk due to passive smoking declines at the same rate following the elimination of exposure as for active smoking, then the avoidable burden over this time frame is approximately 70%–90% of the total burden. Recent evidence from smoking bans indicates that a relatively rapid reduction in excess risk is the more likely case, and that the avoidable burden approximates the total burden.58–60 This analysis has several limitations.

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