State-Specific Prevalence of Current Cigarette Smoking Among Adults and Secondhand Smoke Rules and Policies in Homes and Workplaces—United States, 2005
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Abstract:
Smoking causes premature death and disease in children and adults who do not smoke but are exposed to secondhand smoke (SHS). To assess the state-specific prevalence of current smoking among adults in the United States and the proportions of adults who report having smoke-free home rules and smoke-free policies in their workplace, CDC analyzed data from the 2005 Behavioral Risk Factor Surveillance System (BRFSS). This report summarizes the results of that analysis, which indicated a threefold difference (from lowest to highest) in self-reported cigarette smoking prevalence in 50 states, the District of Columbia (DC), Puerto Rico (PR), and the U.S. Virgin Islands (USVI) (range: 8.3%-28.7%). Wide variations also were observed in USVI and the 14 states that assessed prevalence of smoke-free home rules (from 63.6% [Kentucky] to 82.9% [Arizona]) and smoke-free workplace policies (from 54.8% [Nevada] to 85.8% [West Virginia]). Evidence-based, comprehensive tobacco prevention and control programs that focus on decreasing smoking initiation, increasing smoking cessation, and establishing smoke-free workplaces, homes, and other venues should be continued and expanded to reduce smoking prevalence, exposure of nonsmokers to SHS, and smoking-related morbidity and mortality.Keywords:
Secondhand Smoke
Smoking prevalence
Cross-sectional study
Smoking causes premature death and disease in children and adults who do not smoke but are exposed to secondhand smoke (SHS). To assess the state-specific prevalence of current smoking among adults in the United States and the proportions of adults who report having smoke-free home rules and smoke-free policies in their workplace, CDC analyzed data from the 2005 Behavioral Risk Factor Surveillance System (BRFSS). This report summarizes the results of that analysis, which indicated a threefold difference (from lowest to highest) in self-reported cigarette smoking prevalence in 50 states, the District of Columbia (DC), Puerto Rico (PR), and the U.S. Virgin Islands (USVI) (range: 8.3%-28.7%). Wide variations also were observed in USVI and the 14 states that assessed prevalence of smoke-free home rules (from 63.6% [Kentucky] to 82.9% [Arizona]) and smoke-free workplace policies (from 54.8% [Nevada] to 85.8% [West Virginia]). Evidence-based, comprehensive tobacco prevention and control programs that focus on decreasing smoking initiation, increasing smoking cessation, and establishing smoke-free workplaces, homes, and other venues should be continued and expanded to reduce smoking prevalence, exposure of nonsmokers to SHS, and smoking-related morbidity and mortality.
Secondhand Smoke
Smoking prevalence
Cross-sectional study
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Secondhand Smoke
Behavioral risk
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The SimSmoke Tobacco Control Policy Simulation Model, as described in the paper by Levy & colleagues (2005), does a useful job of using the extensive empirical evidence on the impact of tobacco control policies on cigarette smoking to explain trends in smoking prevalence in the United States from 1993 to 2002. At the same time, it illustrates clearly the limits of our understanding about the impact of other environmental influences on smoking, as well as the effects of tobacco control policies on smoking in important subpopulations, suggesting several avenues for future research. To date, most tobacco policy research has focused on the impact of control policies on overall measures of cigarette smoking, typically overall cigarette sales or smoking prevalence. Studies of the effects of cigarette prices, smoke-free air laws and comprehensive tobacco control programs tend to be consistent in their estimates of how these influence smoking. Given that the findings from this extensive and consistent research have been incorporated into the model, it is no surprise that SimSmoke does well in explaining the role of changes in major tobacco control policies on overall cigarette smoking. The inclusion in the model of other major macro-level, non-policy influences on smoking behavior would further improve the model's performance. For example, adding a module capturing the impact of tobacco companies’ marketing would help to close the gap between the model's predictions and observed behavior. The fact that the model's predicted decline in prevalence for the 1993–97 period is similar to the observed change in prevalence during this period is consistent with the fact that, overall, inflation-adjusted tobacco company marketing expenditures changed little during this period (Federal Trade Commission 2004). In contrast, the less than predicted decline in prevalence from 1997 to 2002 is likely to be explained at least partially by the sharp rise in industry marketing expenditures, mainly on price-related promotions, that helped to offset the impact of higher prices and stronger tobacco control policies on smoking (Keeler et al. 2004). In contrast, SimSmoke's predictions are less consistent with the actual changes in age, gender and racial/ethnic specific prevalence rates over time. This almost certainly results from the very limited research on and, consequently, greater uncertainty about, the impact of major tobacco control policies on cigarette smoking in these important subpopulations. With the exception of the impact of price changes on youth smoking prevalence, very few studies have examined the differential effects of cigarette prices, smoke-free air laws and comprehensive tobacco control funding on smoking by men and women, teens and young adults and various racial/ethnic groups, and little is known about the differential impact of tobacco company marketing on smoking in these subgroups. Similarly, SimSmoke's treatment of comprehensive program funding does not account for the significant differences in the types of activities supported by these programs and for differences in their target populations. In addition, there are several under-researched issues that would improve SimSmoke's ability to explain the past and predict the future, both for the overall population as well as important subgroups. These range from research on the impact of large price increases on smoking behavior to research that examines the synergistic effects of different combinations of tobacco control policies. As new studies on these issues emerge, incorporating their findings in SimSmoke will improve the utility of the model in explaining changes in smoking prevalence over time and for informing the development of future tobacco control policy. The bottom line is clear—while much is known about the impact of tobacco control policies on overall cigarette smoking, much remains to be learned about the role of other environmental influences as well as the differential impact of these factors on smoking in key population subgroups. The SimSmoke model provides a useful tool for synthesizing the findings from past, ongoing and future research, both in explaining past trends in smoking and in predicting the future impact of stronger tobacco control policies.
Smoking prevalence
Youth smoking
Surprise
Tobacco Industry
Smoking prevention
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Background
Tobacco use is still highly prevalent in Europe, despite the tobacco control efforts made by the governments. The development of tobacco control policies varies substantially across countries. The Tobacco Control Scale (TCS) was introduced to quantify the implementation of tobacco control policies across European countriesObjective
To assess the midterm association of tobacco control policies on smoking prevalence and quit ratios among 27 European Union (EU) Member States (EU27).Methods
Ecological study. We used the TCS in EU27 in 2007 and the prevalence of tobacco and quit ratios data from the Eurobarometer survey (2006 (n=27 585) and 2014 (n=26 793)). We analysed the relationship between the TCS scores and smoking prevalence and quit ratios and their relative changes (between 2006 and 2014) by means of scatter plots and multiple linear regression models.Results
In EU27, countries with higher scores in the TCS, which indicates higher tobacco control efforts, have lower prevalence of smokers, higher quit ratios and higher relative decreases in their prevalence rates of smokers over the last decade. The correlation between TCS scores and smoking prevalence (rsp=–0.444; P=0.02) and between the relative changes in smoking prevalence (rsp=–0.415; P=0.03) was negative. A positive correlation was observed between TCS scores and quit ratios (rsp=0.373; P=0.06). The percentage of smoking prevalence explained by all TCS components was 28.9%.Conclusion
EU27 should continue implementing comprehensive tobacco control policies as they are key for reducing the prevalence of smoking and an increase tobacco cessation rates in their population.Smoking prevention
Smoking prevalence
Quit smoking
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Effectiveness of tobacco control programmes in reducing smoking prevalence during 2001 to 2005 is examined. Tobacco control spending is found to exert no significant effects on smoking prevalence across the 50 states. Cigarette prices are found to lower prevalence of daily smokers, but exert no effect on nondaily smoking prevalence. Several reasons are suggested for why these results might conflict with previous research. These include that most previous studies examined two states (California and Massachusetts) with long-standing tobacco control programmes and that most studies examined periods in which many of the states in their samples did not actively fund their programmes. Another reason may be that, unlike most previous studies, this study controls for the possibility that tobacco control spending is endogenous when, for example, states exhibiting relatively low smoking prevalence are also states with relatively high distaste for smoking and accordingly fund tobacco control programmes more generously. A negative relation between tobacco control spending and smoking prevalence does not necessarily indicate that higher spending causes lower prevalence when spending is endogenously determined.
Smoking prevalence
Smoking epidemiology
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In France, following a long-term decline in smoking prevalence, an increase in smoking was observed between 2005 and 2010, an unusual occurrence in countries in the 'mature' stage of the smoking epidemic. By contrast, smoking prevalence in England, the neighbouring country, continued its long-term decline.We identified and translated recent reports on smoking and tobacco control in France and using these assessed the main data sources on smoking and compared them with similar sources in England, in order to explore possible explanations. In France, national smoking prevalence data are collected 5-yearly, minimizing opportunities for fine-grained analysis; the comparable study in England is implemented annually.We identified several probable causes of the recent increased prevalence of smoking in France, the primary one being the absence of sufficient price rises between 2005 and 2010, due probably to the lack of a robust tobacco control strategy, which also appeared to have empowered tobacco industry influence. Funding to compensate tobacconists appears to incentivize tobacco sales and is significantly higher than tobacco control funding.Mindful of the limitations of a case-study approach, the absence of sufficient price rises in the context of a weak tobacco control strategy seems the most likely explanation for the recent increase in smoking prevalence in France. A new cancer control plan and a national smoking reduction programme have been proposed by the French government in 2014 which, depending on implementation, may reverse the trend. In both countries, the higher levels of smoking among the more disadvantaged groups are of great concern and require greater political leadership for effective action.
Smoking prevalence
Disadvantaged
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Objectives
This study estimates the relative contribution of policies implemented between 1998 and 2010 to reductions in smoking prevalence by 2010. It then models the impact of implementing stronger policies, relative to a scenario of inaction, on smoking prevalence and smoking-attributable mortality in Ireland.Methods
IrelandSS is an adapted version of SimSmoke, a dynamic simulation model used to examine the effect of tobacco control policies on smoking prevalence, through initiation and cessation, and associated future premature mortality.Results
Model predictions for smoking prevalence are reasonably close to those from surveys. As a result of tobacco control policies implemented between 1998 and 2010, there was a 22% relative reduction in smoking prevalence and 1716 fewer smoking-attributable deaths (SADs) by 2010 increasing to a 29% relative reduction in prevalence and 50 215 fewer SADs by 2040. With the introduction of stricter FCTC-compliant policies in 2011, the smoking prevalence can be decreased by as much as 13% initially, increasing to 28% by 30 years. With these stronger policies, a total of 24 768 SADs will be averted by 2040.Conclusions
Predictions from the IrelandSS model suggest that policies implemented between 1998 and 2010 have had considerable effect; however, appreciable reductions in smoking prevalence and SADs can still be achieved through increasing taxes, maintaining a high-intensity tobacco control media campaign, introducing graphic health warnings and improving smoking cessation services.Smoking prevalence
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Introduction Protection from secondhand smoke (SHS) is one of the fundamental principles of the WHO Framework Convention for Tobacco Control. Objective data on SHS exposure in vehicles in South America is scarce. This study aimed to estimate prevalence of smoking inside vehicles. Methods The point prevalence of smoking in vehicles was observed, and a method for estimating smoking prevalence was piloted. Results We observed 10 011 vehicles. In 219 (2.2%; 95% CI 1.91 to 2.49) of them, smoking was observed, and in 29.2% of these, another person was exposed to SHS. According to the ‘expansion factor’ we constructed, direct observation detected one of six to one to nine vehicles in which smoking occurred. The observed prevalence of smoking in vehicles (2.2%) could reflect a real prevalence between 12% and 19%. In 29.2% (95% CI 23.6 to 35.5) and 4.6% (95% CI 2.2 to 8.3) of vehicles in which smoking was observed, another adult or a child, respectively, was exposed to SHS. Conclusions Smoking was estimated to occur in 12%–19% of vehicles, with involuntary exposure in one of three of vehicles observed. These data underscore a need for new public policies to eliminate SHS in vehicles to protect public health.
Secondhand Smoke
Smoking prevalence
Passive smoking
Smoking ban
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Each year, cigarette smoking causes an estimated 430,000 deaths in the United States (1). In addition, the health risks for smoking cigars, which include mouth, throat, and lung cancers, are well documented (2). This report summarizes the findings from the 1998 Behavioral Risk Factor Surveillance System (BRFSS) on the prevalence of current cigarette and cigar smoking in the 50 states and the District of Columbia. The findings indicate that state-specific cigarette smoking prevalence among adults aged > or = 18 years varied twofold and having ever smoked a cigar (i.e., ever cigar smoking) varied nearly fourfold.
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Smoking epidemiology
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Despite substantial positive impacts of Thailand's tobacco control policies on reducing the prevalence of smoking, current trends suggest that further reductions are needed to ensure that WHO's 2025 voluntary global target of a 30% relative reduction in tobacco use is met. In order to confirm this hypothesis, we aim to estimate the effect of tobacco control policies in Thailand on the prevalence of smoking and attributed deaths and assess the possibilities of achieving WHO's 2025 global target. This paper addresses this knowledge gap which will contribute to policy control measures on tobacco control. Results of this study can help guide policy makers in implementing further interventions to reduce the prevalence of smoking in Thailand.A Markov chain model was developed to examine the effect of tobacco control policies, such as accessibility restrictions for youths, increased tobacco taxes and promotion of smoking cessation programs, from 2015 to 2025. Outcomes included smoking prevalence and the number of smoking-attributable deaths. Due to the very low prevalence of female smokers in 2014, this study applied the model to estimate the smoking prevalence and attributable mortality among males only.Given that the baseline prevalence of smoking in 2010 was 41.7% in males, the target of a 30% relative reduction requires that the prevalence be reduced to 29.2% by 2025. Under a baseline scenario where smoking initiation and cessation rates among males are attained by 2015, smoking prevalence rates will reduce to 37.8% in 2025. The combined tobacco control policies would further reduce the prevalence to 33.7% in 2025 and 89,600 deaths would be averted.Current tobacco control policies will substantially reduce the smoking prevalence and smoking-attributable deaths. The combined interventions can reduce the smoking prevalence by 19% relative to the 2010 level. These projected reductions are insufficient to achieve the committed target of a 30% relative reduction in smoking by 2025. Increased efforts to control tobacco use will be essential for reducing the burden of non-communicable diseases in Thailand.
Smoking prevalence
Biostatistics
Attributable risk
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