913 resultados para Smoking Bans


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Background: Medical and pharmacological direct costs of cigarette smoking cessation programmes are not covered by health insurance in several countries despite documented cost-effectiveness. Design: prospective cost identification study of a 9-week programme in Switzerland. Methods: A total of 481 smokers were followed-up for 9 weeks. Socio-demographic characteristics, number of outpatient visits, dosage and frequency of use of nicotine replacement therapy (NRT) as well as date of relapse were prospectively collected. Individual cost of care until relapse or programme end as well as cost per week of follow-up were computed. Comparisons were carried out between the groups with or without relapse at the end of the programme. Results: Of the 209 men and 272 women included, 347 patients (72%) finished the programme. Among them, 240 patients (70%) succeeded in quitting and 107 patients (30%) relapsed. As compared with the group relapsing by the end of the programme, the group succeeding in quitting was more often living in a couple (68% vs. 55%, p = 0.029). Their mean weekly costs of visits were higher (CHF 81.2 ± 6.1 vs. 78.4 ± 7.6, p = 0.001), while their mean weekly costs for NRT were similar (CHF 24.2 ± 12.6 vs. 25.4 ± 15.9, p = 0.711). Mean total costs per week were similar (CHF 105.4 ± 15.4 vs. 103.8 ± 19.4, p = 0.252). More intensive NRT at week 4 increased the probability not to relapse at the end of the programme. Conclusions: Over 9 weeks, medical and pharmacological costs of stopping smoking are low. Good medical and social support as well as adequate NRT seem to play a role in successful quitting.

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Smoking is a leading global cause of disease and mortality. We established the Oxford-GlaxoSmithKline study (Ox-GSK) to perform a genome-wide meta-analysis of SNP association with smoking-related behavioral traits. Our final data set included 41,150 individuals drawn from 20 disease, population and control cohorts. Our analysis confirmed an effect on smoking quantity at a locus on 15q25 (P = 9.45 x 10(-19)) that includes CHRNA5, CHRNA3 and CHRNB4, three genes encoding neuronal nicotinic acetylcholine receptor subunits. We used data from the 1000 Genomes project to investigate the region using imputation, which allowed for analysis of virtually all common SNPs in the region and offered a fivefold increase in marker density over HapMap2 (ref. 2) as an imputation reference panel. Our fine-mapping approach identified a SNP showing the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.

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Different compounds have been reported as biomarkers of a smoking habit, but, to date, there is no appropriate biomarker for tobacco-related exposure because the proposed chemicals seem to be nonspecific or they are only appropriate for short-term exposure. Moreover, conventional sampling methodologies require an invasive method because blood or urine samples are required. The use of a microtrap system coupled to gas chromatography–mass spectrometry analysis has been found to be very effective for the noninvasive analysis of volatile organic compounds in breath samples. The levels of benzene, 2,5-dimethylfuran, toluene, o-xylene, and m- p-xylene have been analyzed in breath samples obtained from 204 volunteers (100 smokers, 104 nonsmokers; 147 females, 57 males; ages 16 to 53 years). 2,5-Dimethylfuran was always below the limit of detection (0.005 ppbv) in the nonsmoker population and always detected in smokers independently of the smoking habits. Benzene was only an effective biomarker for medium and heavy smokers, and its level was affected by smoking habits. Regarding the levels of xylenes and toluene, they were only different in heavy smokers and after short-term exposure. The results obtained suggest that 2,5-dimethylfuran is a specific breath biomarker of smoking status independently of the smoking habits (e.g., short- and long-term exposure, light and heavy consumption), and so this compound might be useful as a biomarker of smoking exposure

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Cigar and pipe smoking are considered risk factors for head and neck cancers, but the magnitude of effect estimates for these products has been imprecisely estimated. By using pooled data from the International Head and Neck Cancer Epidemiology (INHANCE) Consortium (comprising 13,935 cases and 18,691 controls in 19 studies from 1981 to 2007), we applied hierarchical logistic regression to more precisely estimate odds ratios and 95% confidence intervals for cigarette, cigar, and pipe smoking separately, compared with reference groups of those who had never smoked each single product. Odds ratios for cigar and pipe smoking were stratified by ever cigarette smoking. We also considered effect estimates of smoking a single product exclusively versus never having smoked any product (reference group). Among never cigarette smokers, the odds ratio for ever cigar smoking was 2.54 (95% confidence interval (CI): 1.93, 3.34), and the odds ratio for ever pipe smoking was 2.08 (95% CI: 1.55, 2.81). These odds ratios increased with increasing frequency and duration of smoking (Ptrend ≤ 0.0001). Odds ratios for cigar and pipe smoking were not elevated among ever cigarette smokers. Head and neck cancer risk was elevated for those who reported exclusive cigar smoking (odds ratio = 3.49, 95% CI: 2.58, 4.73) or exclusive pipe smoking (odds ratio = 3.71, 95% CI: 2.59, 5.33). These results suggest that cigar and pipe smoking are independently associated with increased risk of head and neck cancers.

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BACKGROUND: Cardiovascular disease and non-AIDS malignancies have become major causes of death among HIV-infected individuals. The relative impact of lifestyle and HIV-related factors are debated. METHODS: We estimated associations of smoking with mortality more than 1 year after antiretroviral therapy (ART) initiation among HIV-infected individuals enrolled in European and North American cohorts. IDUs were excluded. Causes of death were assigned using standardized procedures. We used abridged life tables to estimate life expectancies. Life-years lost to HIV were estimated by comparison with the French background population. RESULTS: Among 17 995 HIV-infected individuals followed for 79 760 person-years, the proportion of smokers was 60%. The mortality rate ratio (MRR) comparing smokers with nonsmokers was 1.94 [95% confidence interval (95% CI) 1.56-2.41]. The MRRs comparing current and previous smokers with never smokers were 1.70 (95% CI 1.23-2.34) and 0.92 (95% CI 0.64-1.34), respectively. Smokers had substantially higher mortality from cardiovascular disease, non-AIDS malignancies than nonsmokers [MRR 6.28 (95% CI 2.19-18.0) and 2.67 (95% CI 1.60-4.46), respectively]. Among 35-year-old HIV-infected men, the loss of life-years associated with smoking and HIV was 7.9 (95% CI 7.1-8.7) and 5.9 (95% CI 4.9-6.9), respectively. The life expectancy of virally suppressed, never-smokers was 43.5 years (95% CI 41.7-45.3), compared with 44.4 years among 35-year-old men in the background population. Excess MRRs/1000 person-years associated with smoking increased from 0.6 (95% CI -1.3 to 2.6) at age 35 to 43.6 (95% CI 37.9-49.3) at age at least 65 years. CONCLUSION: Well treated HIV-infected individuals may lose more life years through smoking than through HIV. Excess mortality associated with smoking increases markedly with age. Therefore, increases in smoking-related mortality can be expected as the treated HIV-infected population ages. Interventions for smoking cessation should be prioritized.

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Physicians are in a unique position to advice smokers to quit by the ability to integrate the various aspects of nicotine dependence. This review provides an overview of intervention with smokers presenting in a primary care setting. Strategies used for smoking cessation counseling differed according to patient's readiness to quit. For smokers who do not intend to quit smoking, physicians should inform and sensitize patients about tobacco use and cessation, especially by personalizing benefits to quit and challenging smokers 'beliefs. For smokers who are dissonant, physicians should use motivational strategies, such as discussing barriers to cessation and their solutions. For smokers ready to quit, the physician should show strong support, help set a quit date, prescribe pharmaceutical therapies for nicotine dependence, such as replacement therapy and/or bupropion, with instructions for use, and suggest behavioral strategies to prevent relapse.

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PURPOSE: We examined the role of smoking in the two dimensions behind the time trends in adult mortality in European countries, that is, rectangularization of the survival curve (mortality compression) and longevity extension (increase in the age-at-death). METHODS: Using data on national sex-specific populations aged 50 years and older from Denmark, Finland, France, West Germany, Italy, the Netherlands, Norway, Sweden, Switzerland, and the United Kingdom, we studied trends in life expectancy, rectangularity, and longevity from 1950 to 2009 for both all-cause and nonsmoking-related mortality and correlated them with trends in lifetime smoking prevalence. RESULTS: For all-cause mortality, rectangularization accelerated around 1980 among men in all the countries studied, and more recently among women in Denmark and the United Kingdom. Trends in lifetime smoking prevalence correlated negatively with both rectangularization and longevity extension, but more negatively with rectangularization. For nonsmoking-related mortality, rectangularization among men did not accelerate around 1980. Among women, the differences between all-cause mortality and nonsmoking-related mortality were small, but larger for rectangularization than for longevity extension. Rectangularization contributed less to the increase in life expectancy than longevity extension, especially for nonsmoking-related mortality among men. CONCLUSIONS: Smoking affects rectangularization more than longevity extension, both among men and women.

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Background: Diverse projects and guidelines to assist hospitals towards the attainment of comprehensive smoke-free policies have been developed. In 2006, Spain government passed a new smoking ban that reinforce tobacco control policies and banned completely smoking in hospitals. This study assesses the progression of tobacco control policies in the Catalan Network of Smokefree Hospitals before and after a comprehensive national smoking ban. Methods: We used the Self-Audit Questionnaire of the European Network for Smoke-free Hospitals to score the compliance of 9 policy standards (global score = 102). We used two crosssectional surveys to evaluate tobacco control policies before (2005) and after the implementation of a national smoking ban (2007) in 32 hospitals of Catalonia, Spain. We compared the means of the overall score in 2005 and 2007 according to the type of hospital, the number of beds, the prevalence of tobacco consumption, and the number of years as a smoke-free hospital. Results: The mean of the implementation score of tobacco control policies was 52.4 (95% CI:45.4-59.5) in 2005 and 71.6 (95% CI: 67.0-76.2) in 2007 with an increase of 36.7% (p < 0.01). The hospitals with greater improvement were general hospitals (48% increase; p < 0.01), hospitals with > 300 beds (41.1% increase; p < 0.01), hospitals with employees' tobacco consumption prevalence 35-39% (72.2% increase; p < 0.05) and hospitals that had recently implemented smoke-free policies (74.2% increase; p < 0.01). Conclusion: The national smoking ban appears to increase tobacco control activities in hospitals combined with other non-bylaw initiatives such as the Smoke-free Hospital Network.

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Background: Diverse projects and guidelines to assist hospitals towards the attainment of comprehensive smoke-free policies have been developed. In 2006, Spain government passed a new smoking ban that reinforce tobacco control policies and banned completely smoking in hospitals. This study assesses the progression of tobacco control policies in the Catalan Network of Smokefree Hospitals before and after a comprehensive national smoking ban. Methods: We used the Self-Audit Questionnaire of the European Network for Smoke-free Hospitals to score the compliance of 9 policy standards (global score = 102). We used two crosssectional surveys to evaluate tobacco control policies before (2005) and after the implementation of a national smoking ban (2007) in 32 hospitals of Catalonia, Spain. We compared the means of the overall score in 2005 and 2007 according to the type of hospital, the number of beds, the prevalence of tobacco consumption, and the number of years as a smoke-free hospital. Results: The mean of the implementation score of tobacco control policies was 52.4 (95% CI:45.4-59.5) in 2005 and 71.6 (95% CI: 67.0-76.2) in 2007 with an increase of 36.7% (p < 0.01). The hospitals with greater improvement were general hospitals (48% increase; p < 0.01), hospitals with > 300 beds (41.1% increase; p < 0.01), hospitals with employees' tobacco consumption prevalence 35-39% (72.2% increase; p < 0.05) and hospitals that had recently implemented smoke-free policies (74.2% increase; p < 0.01). Conclusion: The national smoking ban appears to increase tobacco control activities in hospitals combined with other non-bylaw initiatives such as the Smoke-free Hospital Network.

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In Seychelles, comprehensive tobacco control legislation enacted in 2009, and subsequent regulations, ban smoking in all enclosed places (defined as any area under a fixed or transient roof). A survey in October-November 2014 assessed i) the compliance to the Act and these regulations in 63 restaurants, bars or discotheques and ii) knowledge of the Tobacco control Act and these regulations of supervisors and managers of these hospitality premises; (47 agreed to answer). No person was found smoking in 92% of all premises. However, "no smoking" signs did not conform to regulations in >70% of premises, and ashtrays were seen in 17% of enclosed premises. All supervisors and managers (100%) knew that smoking is banned in enclosed premises but <15% knew the fines liable to persons, respective owners of enclosed places, when a person smokes in an enclosed premise. Furthermore, 60% of supervisors were not aware that no smoking signs must comply with a specific regulation and 40% were not aware that ashtrays are not permitted in enclosed premises. In conclusion, the positive finding is that few persons smoke in restaurants, bars and discotheques, but the survey also showed that several aspects of regulations for tobacco control in enclosed premises are not well implemented. This calls for further information campaigns targeting both the public and the managers of hospitality premises, but also for strengthening enforcement measures, including fines for offenses. Scaling up comprehensive tobacco control measures, including full enforcement of clean air policy, is of paramount importance to meet the national target of 30% reduction of the smoking prevalence between 2010 and 2025.

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OBJECTIVES: To investigate, using a Mendelian randomisation approach, whether heavier smoking is associated with a range of regional adiposity phenotypes, in particular those related to abdominal adiposity. DESIGN: Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730 in the CHRNA5-CHRNA3-CHRNB4 gene region) as a proxy for smoking heaviness, of the associations of smoking heaviness with a range of adiposity phenotypes. PARTICIPANTS: 148 731 current, former and never-smokers of European ancestry aged ≥16 years from 29 studies in the consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA). PRIMARY OUTCOME MEASURES: Waist and hip circumferences, and waist-hip ratio. RESULTS: The data included up to 66 809 never-smokers, 43 009 former smokers and 38 913 current daily cigarette smokers. Among current smokers, for each extra minor allele, the geometric mean was lower for waist circumference by -0.40% (95% CI -0.57% to -0.22%), with effects on hip circumference, waist-hip ratio and body mass index (BMI) being -0.31% (95% CI -0.42% to -0.19), -0.08% (-0.19% to 0.03%) and -0.74% (-0.96% to -0.51%), respectively. In contrast, among never-smokers, these effects were higher by 0.23% (0.09% to 0.36%), 0.17% (0.08% to 0.26%), 0.07% (-0.01% to 0.15%) and 0.35% (0.18% to 0.52%), respectively. When adjusting the three central adiposity measures for BMI, the effects among current smokers changed direction and were higher by 0.14% (0.05% to 0.22%) for waist circumference, 0.02% (-0.05% to 0.08%) for hip circumference and 0.10% (0.02% to 0.19%) for waist-hip ratio, for each extra minor allele. CONCLUSIONS: For a given BMI, a gene variant associated with increased cigarette consumption was associated with increased waist circumference. Smoking in an effort to control weight may lead to accumulation of central adiposity.

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A smoke-free law came into effect in Spain on 1st January 2006, affecting all enclosed workplaces except hospitality venues, whose proprietors can choose among totally a smoke-free policy, a partial restriction with designated smoking areas, or no restriction on smoking on the premises. We aimed to evaluate the impact of the law among hospitality workers by assessing second-hand smoke (SHS) exposure and the frequency of respiratory symptoms before and one year after the ban.