Letter to the Editor

Meta-analysis of the effects of smokefree laws on acute myocardial infarction: An update

This article explores a nexus between society, nature and technology (SNT) in the context of a biomedical problem-solution through innovation project for a new product development in the biopharmaceutical sector. The nexus implies that social intervention is an antecedent to and consequence of nature as a type of morbidity. The central proposition is that national morbidities are partially resulting of national institutions such as policy and culture, and the national institutions partially constitute the response to through industrialisation processes and cultural habits. Based on the data from China and India as two comparable socio-culture contexts, we draw on six types of national morbidities: diabetes, infections, cancer, hepatitis, respiratory dysfunction and hypertension. An analysis shows that diabetes and infectious diseases projects exist more in India; cancer, hepatitis and hypertension projects exist more in China; and contrary to prediction, respiratory dysfunction project appears more in India than China. There are some statistical differences between the North and South regions. The discussion explains the SNT nexus in a broader context suggests two types of interventions: preventive and curing. The preventive intervention comes before nature (morbidity), and the curing intervention occurs after the formation of morbidity. We suggest that preventive institutional intervention for education can be more effective than curing intervention. The prevention mechanism induces awareness; the curing mechanism induces treatment solutions. Our argument supports the social development as much as industrialisation, and not pure industrialisation alone.

In our latest update of the evidence on smoking bans and heart disease we summarize 59 studies. We take account of the underlying trends in incidence rates as far as possible by using control data in eight studies, and by adjustment based on observed trends in cases pre- and post-ban in 40 studies, being unable to make an adjustment in the remaining 11 studies. Overall, based on 62 independent estimates from the 59 studies, we estimate that bans reduce incidence by 5.0% (95% CI 3.2–6.8%), though this estimate reduces to 2.9% (0.01–5.6%) when we exclude regional estimates where national estimates are available, and studies where trend adjustment is not possible. For 25 of the studies, quadratic rather than linear adjustment is possible, but this hardly affects the overall estimates. Ban effects are somewhat greater when the pre-ban period studied is relatively short, and in smaller studies. We compare our findings with those in other recent reviews, one of which totally ignored underlying trends and results from control populations. We discuss reasons why we believe there is likely to be a true small effect of smoking bans, and weaknesses in the data which preclude reaching any very confident conclusion.

We update an earlier review of smoking bans and heart disease, restricting attention to admissions for acute myocardial infarction. Forty-five studies are considered. New features of our update include consideration of non-linear trends in the underlying rate, a modified trend adjustment method where there are multiple time periods post-ban, comparison of estimates based on changes in rates and numbers of cases, and comparison of effect estimates according to post-ban changes in smoking restrictiveness. Using a consistent approach to derive ban effect estimates, taking account of linear time trends and control data, the reduction in risk following a ban was estimated as 4.2% (95% confidence interval 1.8–6.5%). Excluding regional estimates where national estimates are available, and studies where trend adjustment was not possible, the estimate reduced to 2.6% (1.1–4.0%). Estimates were little affected by non-linear trend adjustment, where possible, or by basing estimates on changes in rates. Ban effect estimates tended to be greater in smaller studies, and studies with greater post-ban changes in smoking restrictiveness. Though the findings suggest a true effect of smoking bans, uncertainties remain, due to the weakness of much of the evidence, the small estimated effect, and various possibilities of bias.

Public smoking ordinances may reduce acute myocardial infarction events. Most studies assessed small communities with reported reductions as high as 40%. No reduction or smaller reductions were found in countrywide studies; less is known about the impact of statewide ordinances. We previously demonstrated identical 27% reductions in acute myocardial infarction hospitalizations in 2 Colorado communities after enactment of strict smoking ordinances. Subsequently, on July 1, 2006, a statewide ordinance went into effect. We sought to determine the impact of this legislation on acute myocardial infarction hospitalization rates.

Hospital admissions for a primary acute myocardial infarction diagnosis were examined from 2000 to 2008. Poisson regression models were fit to the monthly events from January 1, 2000, to March 31, 2008. The final model included a quadratic trend over time, harmonic terms, and a post-ordinance effect. The model was adjusted temporally for population changes, using population estimates as an offset variable.

A total of 58,399 unique acute myocardial infarctions were recorded during the study period. No significant reduction in acute myocardial infarction rates was observed post-ordinance (relative risk, 1.059; 95% confidence interval, 0.993-1.131). However, a steep decline in acute myocardial infarction rates was noted from 2000 to 2005 just before enactment. There were 11 strict, local smoking ordinances in effect within Colorado before enactment of the statewide ordinance. After excluding these communities, the findings were similar (relative risk, 1.038; 95% confidence interval, 0.971-1.11).

Although local smoking ordinances in Colorado previously suggested a reduction in acute myocardial infarction hospitalizations, no significant impact of smoke-free legislation was demonstrated at the state level, even after accounting for preexisting ordinances.

Secondhand smoke (SHS) exposure poses serious health risks for all nonsmokers, especially children and pregnant women. SHS is estimated to contribute to heart attacks in nonsmokers and nearly 53,800 deaths in the U.S. annually. A literature review of English-language articles was performed using PubMed, organizational websites, and pertinent review articles. Over the past 25 years, smokefree policies have protected nearly half the U.S. population from the adverse health effects of SHS. Smokefree policies have been shown to improve health outcomes with no consequences to local businesses. As of April 2013, a total of 24 states and 561 municipalities and territories, including the District of Columbia, New York City, Puerto Rico, and the U.S. Virgin Islands, have established laws that require nonhospitality workplaces, restaurants, and bars to be 100% smokefree. Four other states—Florida, Indiana, Louisiana, and Nevada—have smokefree laws that cover restaurants but provide an exemption for stand-alone bars. At least 14 states have no smokefree laws.

This paper describes the benefits of policies that reduce SHS and concludes with recommendations for future directions. The American College of Preventive Medicine (ACPM) recommends expanded clean indoor air policies for workplaces, stand-alone bars, restaurants, and multi-use family housing such as apartment buildings. ACPM recommends clean air policies for all university campuses, secondary school campuses, primary schools, child care centers, and city landmarks to further shift social norms and protect the health of children, adolescents, and adults. ACPM recommends closing existing gaps in clean indoor air policies.

Social studies of science have produced a critical description of science that challenges traditional ideas about “objectivity” and “neutrality”. Given evidence that scientific tools have been used to undermine solid science against the interests of the general public as opposed to protecting society from findings prematurely declared to be facts, this article asks: how can one differentiate between the usual proceedings of scientists and deliberate attempts to distort science? In order to respond to this question, the author presents systematic studies of the distortion (or “bending”) of science, with special attention to the role of public relation firms in the process. Drawing on examples from the tobacco industry, the article concludes that there are two key features of the tobacco industry case that indicate that distortions in science may have taken place: the fact that controversies surrounding tobacco has been centered in public forums, and legal or regulatory arenas more than scientific domains; and the presence of conflicts of interest in authorship and funding.