838 resultados para Smoking habit


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ABSTRACT: BACKGROUND: Recent data indicate a slight decrease in the prevalence of smoking in Switzerland, but little is known regarding the intention and difficulty to quit smoking among current smokers. Hence, we aimed to quantify the difficulty and intention to quit smoking among current smokers in Switzerland. METHODS: Cross-sectional study including 607 female and 658 male smokers. Difficulty, intention and motivation to quit smoking were assessed by questionnaire. RESULTS: 90% of women and 85% of men reported being "very difficult" or "difficult" to quit smoking. Almost three quarters of smokers (73% of women and 71% of men) intended to quit; however, less than 20% of them were in the preparation stage and 40% were in the precontemplation stage. On multivariate analysis, difficulty to quit was lower among men (Odds ratio and 95% [confidence interval]: 0.51 [0.35-0.74]) and increased with nicotine dependence and number of previous quitting attempts (OR=3.14 [1.75-5.63] for 6+ attempts compared to none). Intention to quit decreased with increasing age (OR=0.48 [0.30-0.75] for [greater than or equal to]65 years compared to <45 years) and increased with nicotine dependence, the number of previous quitting attempts (OR=4.35 [2.76-6.83] for 6+ attempts compared to none) and among non-cigarette smokers (OR=0.51 [0.28-0.92]). Motivation to quit was inversely associated with nicotine dependence and positively associated with the number of previous quitting attempts and personal history of lung disease. CONCLUSION: Over two thirds of Swiss smokers want to quit. However, only a small fraction wishes to do so in the short term. Nicotine dependence, previous attempts to quit or previous history of lung disease are independently associated with difficulty and intention to quit.

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Odds ratios for head and neck cancer increase with greater cigarette and alcohol use and lower body mass index (BMI; weight (kg)/height(2) (m(2))). Using data from the International Head and Neck Cancer Epidemiology Consortium, the authors conducted a formal analysis of BMI as a modifier of smoking- and alcohol-related effects. Analysis of never and current smokers included 6,333 cases, while analysis of never drinkers and consumers of < or =10 drinks/day included 8,452 cases. There were 8,000 or more controls, depending on the analysis. Odds ratios for all sites increased with lower BMI, greater smoking, and greater drinking. In polytomous regression, odds ratios for BMI (P = 0.65), smoking (P = 0.52), and drinking (P = 0.73) were homogeneous for oral cavity and pharyngeal cancers. Odds ratios for BMI and drinking were greater for oral cavity/pharyngeal cancer (P < 0.01), while smoking odds ratios were greater for laryngeal cancer (P < 0.01). Lower BMI enhanced smoking- and drinking-related odds ratios for oral cavity/pharyngeal cancer (P < 0.01), while BMI did not modify smoking and drinking odds ratios for laryngeal cancer. The increased odds ratios for all sites with low BMI may suggest related carcinogenic mechanisms; however, BMI modification of smoking and drinking odds ratios for cancer of the oral cavity/pharynx but not larynx cancer suggests additional factors specific to oral cavity/pharynx cancer.

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Clozapine, an atypical antipsychotic, depends mainly on cytochrome P4501A2 (CYP1A2) for its metabolic clearance. CYP1A2 is inducible by smoking, and lower plasma concentrations of clozapine are measured in smokers than in nonsmokers. Case reports have been published on the effects of discontinuing smoking in patients receiving clozapine, which might lead to elevated plasma concentrations and severe side effects. We present 2 cases on the consequences of smoking cessation in patients receiving this drug. In the first patient, smoking cessation resulted, within 2 weeks, in severe sedation and fatigue, with an approximately 3-fold increase of plasma clozapine concentrations. In the second patient, a very high plasma concentration of clozapine (3004 ng/mL) was measured 6 days following a 16-day stay in a general hospital, during which smoking was prohibited. In the latter patient, the replacement of omeprazole, a strong CYP1A2 inducer, by pantoprazole, a weaker CYP1A2 inducer, could have contributed, in addition to smoking cessation, to the observed strong increase of plasma clozapine concentrations. Genotyping of the 2 patients revealed that they were carriers of the AA genotype for the -164C>A polymorphism (CYP1A2*1F) in intron 1 of CYP1A2 gene, which has previously been shown to confer a high inducibility of CYP1A2 by smoking. Thus, at the initiation of clozapine treatment, smoking patients should be informed that, if they decide to stop smoking, they are encouraged to do so but must inform their prescriber beforehand. Also, because of the increased use of no-smoking policies in many hospitals, studies examining the consequences of such policies on the pharmacokinetics/pharmacodynamics of drugs metabolized by CYP1A2, taking into account different CYP1A2 genotypes, are needed.

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To assess the preferred methods to quit smoking among current smokers. Cross-sectional, population-based study conducted in Lausanne between 2003 and 2006 including 988 current smokers. Preference was assessed by questionnaire. Evidence-based (EB) methods were nicotine replacement, bupropion, physician or group consultations; non-EB-based methods were acupuncture, hypnosis and autogenic training. EB methods were frequently (physician consultation: 48%, 95% confidence interval (45-51); nicotine replacement therapy: 35% (32-38)) or rarely (bupropion and group consultations: 13% (11-15)) preferred by the participants. Non-EB methods were preferred by a third (acupuncture: 33% (30-36)), a quarter (hypnosis: 26% (23-29)) or a seventh (autogenic training: 13% (11-15)) of responders. On multivariate analysis, women preferred both EB and non-EB methods more frequently than men (odds ratio and 95% confidence interval: 1.46 (1.10-1.93) and 2.26 (1.72-2.96) for any EB and non-EB method, respectively). Preference for non-EB methods was higher among highly educated participants, while no such relationship was found for EB methods. Many smokers are unaware of the full variety of methods to quit smoking. Better information regarding these methods is necessary.

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INTRODUCTION: Several studies have shown an increased risk of type 2 diabetes among smokers. Therefore, the aim of this analysis was to assess the relationship between smoking, cumulative smoking exposure and nicotine dependence with pre-diabetes. METHODS: We performed a cross-sectional analysis of healthy adults aged 25-41 in the Principality of Liechtenstein. Individuals with known diabetes, Body Mass Index (BMI) >35 kg/m² and prevalent cardiovascular disease were excluded. Smoking behaviour was assessed by self-report. Pre-diabetes was defined as glycosylated haemoglobin between 5.7% and 6.4%. Multivariable logistic regression models were done. RESULTS: Of the 2142 participants (median age 37 years), 499 (23.3%) had pre-diabetes. There were 1,168 (55%) never smokers, 503 (23%) past smokers and 471 (22%) current smokers, with a prevalence of pre-diabetes of 21.2%, 20.9% and 31.2%, respectively (p <0.0001). In multivariable regression models, current smokers had an odds ratio (OR) of pre-diabetes of 1.82 (95% confidential interval (CI) 1.39; 2.38, p <0.0001). Individuals with a smoking exposure of <5, 5-10 and >10 pack-years had an OR (95% CI) for pre-diabetes of 1.34 (0.90; 2.00), 1.80 (1.07; 3.01) and 2.51 (1.80; 3.59) (p linear trend <0.0001) compared with never smokers. A Fagerström score of 2, 3-5 and >5 among current smokers was associated with an OR (95% CI) for pre-diabetes of 1.27 (0.89; 1.82), 2.15 (1.48; 3.13) and 3.35 (1.73; 6.48) (p linear trend <0.0001). DISCUSSION: Smoking is strongly associated with pre-diabetes in young adults with a low burden of smoking exposure. Nicotine dependence could be a potential mechanism of this relationship.

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An open prospective study was conducted among the patients visiting an urban medical policlinic for the first time without an appointment to assess whether the immigrants (who represent more than half of our patients) are aware of the health effects of smoking, whether the level of acculturation influences knowledge, and whether doctors give similar advice to Swiss and foreign smokers. 226 smokers, 105 Swiss (46.5%), and 121 foreign-born (53.5%), participated in the study. 32.2% (95% CI [24.4%; 41.1%]) of migrants and 9.6% [5.3%; 16.8%] of Swiss patients were not aware of negative effects of smoking. After adjustment for age, the multivariate model showed that the estimated odds of "ignorance of health effects of smoking" was higher for people lacking mastery of the local language compared with those mastering it (odds ratio (OR) = 7.5 [3.6; 15.8], p < 0.001), and higher for men (OR = 4.3 [1.9; 10.0], p < 0.001). Advice to stop smoking was given with similar frequency to immigrants (31.9% [24.2%; 40.8%] and Swiss patients (29.0% [21.0%; 38.5%]). Nonintegrated patients did not appear to receive less counselling than integrated patients (OR = 1.1 [0.6; 2.1], p = 0.812). We conclude that the level of knowledge among male immigrants not integrated or unable to speak the local language is lower than among integrated foreign-born and Swiss patients. Smoking cessation counselling by a doctor was only given to a minority of patients, but such counselling seemed irrespective of nationality.

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Nicotine cessation programmes in Switzerland, which are commonly based on the stage of change model of Prochaska and DiClemente (1983), are rarely offered to patients with illicit drug dependence. This stands in contrast to the high smoking rates and the heavy burden of tobacco-related problems in these patients. The stage of change was therefore assessed by self-administered questionnaire in 100 inpatients attending an illegal drug withdrawal programme. Only 15% of the patients were in the contemplation or decision stage. 93% considered smoking cessation to be difficult or very difficult. These data show a discrepancy between the motivation to change illegal drug consumption habits and the motivation for smoking cessation. The high proportion of patients remaining in the precontemplation stage for smoking cessation, in spite of their motivation for illicit drug detoxification, may be due to the perception that cessation of smoking is more difficult than illicit drug abuse cessation.

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The Early Smoking Experience (ESE) questionnaire is the most widely used questionnaire to assess initial subjective experiences of cigarette smoking. However, its factor structure is not clearly defined and can be perceived from two main standpoints: valence, or positive and negative experiences, and sensitivity to nicotine. This article explores the ESE's factor structure and determines which standpoint was more relevant. It compares two groups of young Swiss men (German- and French-speaking). We examined baseline data on 3,368 tobacco users from a representative sample in the ongoing Cohort Study on Substance Use Risk Factors (C-SURF). ESE, continued tobacco use, weekly smoking and nicotine dependence were assessed. Exploratory structural equation modeling (ESEM) and structural equation modeling (SEM) were performed. ESEM clearly distinguished positive experiences from negative experiences, but negative experiences were divided in experiences related to dizziness and experiences related to irritations. SEM underlined the reinforcing effects of positive experiences, but also of experiences related to dizziness on nicotine dependence and weekly smoking. The best ESE structure for predictive accuracy of experiences on smoking behavior was a compromise between the valence and sensitivity standpoints, which showed clinical relevance.

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BACKGROUND: A possible strategy for increasing smoking cessation rates could be to provide smokers who have contact with healthcare systems with feedback on the biomedical or potential future effects of smoking, e.g. measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer. We reviewed systematically data on smoking cessation rates from controlled trials that used biomedical risk assessment and feedback. OBJECTIVES: To determine the efficacy of biomedical risk assessment provided in addition to various levels of counselling, as a contributing aid to smoking cessation. SEARCH STRATEGY: We systematically searched he Cochrane Collaboration Tobacco Addiction Group Specialized Register, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (1966 to 2004), and EMBASE (1980 to 2004). We combined methodological terms with terms related to smoking cessation counselling and biomedical measurements. SELECTION CRITERIA: Inclusion criteria were: a randomized controlled trial design; subjects participating in smoking cessation interventions; interventions based on a biomedical test to increase motivation to quit; control groups receiving all other components of intervention; an outcome of smoking cessation rate at least six months after the start of the intervention. DATA COLLECTION AND ANALYSIS: Two assessors independently conducted data extraction on each paper, with disagreements resolved by consensus. MAIN RESULTS: From 4049 retrieved references, we selected 170 for full text assessment. We retained eight trials for data extraction and analysis. One of the eight used CO alone and CO + Genetic Susceptibility as two different intervention groups, giving rise to three possible comparisons. Three of the trials isolated the effect of exhaled CO on smoking cessation rates resulting in the following odds ratios (ORs) and 95% confidence intervals (95% CI): 0.73 (0.38 to 1.39), 0.93 (0.62 to 1.41), and 1.18 (0.84 to 1.64). Combining CO measurement with genetic susceptibility gave an OR of 0.58 (0.29 to 1.19). Exhaled CO measurement and spirometry were used together in three trials, resulting in the following ORs (95% CI): 0.6 (0.25 to 1.46), 2.45 (0.73 to 8.25), and 3.50 (0.88 to 13.92). Spirometry results alone were used in one other trial with an OR of 1.21 (0.60 to 2.42).Two trials used other motivational feedback measures, with an OR of 0.80 (0.39 to 1.65) for genetic susceptibility to lung cancer alone, and 3.15 (1.06 to 9.31) for ultrasonography of carotid and femoral arteries performed in light smokers (average 10 to 12 cigarettes a day). AUTHORS' CONCLUSIONS: Due to the scarcity of evidence of sufficient quality, we can make no definitive statements about the effectiveness of biomedical risk assessment as an aid for smoking cessation. Current evidence of lower quality does not however support the hypothesis that biomedical risk assessment increases smoking cessation in comparison with standard treatment. Only two studies were similar enough in term of recruitment, setting, and intervention to allow pooling of data and meta-analysis.

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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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AIMS: Smoking cessation has been suggested to increase the short-term risk of type 2 diabetes mellitus (T2DM). This study aimed at assessing the association between smoking cessation and incidence of T2DM and impaired fasting glucose (IFG). METHODS: Data from participants in the CoLaus study, Switzerland, aged 35-75 at baseline and followed for 5.5years were used. Participants were classified as smokers, recent (≤5years), long-term (>5years) quitters, and non-smokers at baseline. Outcomes were IFG (fasting serum glucose (FSG) 5.6-6.99mmol/l) and T2DM (FSG ≥7.0mmol/l and/or treatment) at follow up. RESULTS: 3,166 participants (63% women) had normal baseline FSG, of whom 26.7% were smokers, 6.5% recent quitters, and 23.5% long-term quitters. During follow-up 1,311 participants (41.4%) developed IFG (33.6% women, 54.7% men) and 47 (1.5%) developed T2DM (1.1% women, 2.1% men). Former smokers did not have statistically significant increased odds of IFG compared with smokers after adjustment for age, education, physical activity, hypercholesterolemia, hypertension and alcohol intake, with OR of 1.29 [95% confidence interval 0.94-1.76] for recent quitters and 1.03 [0.84-1.27] for long-term quitters. Former smokers did not have significant increased odds of T2DM compared with smokers with multivariable-adjusted OR of 1.53 [0.58-4.00] for recent quitters and 0.64 [0.27-1.48] for long-term quitters. Adjustment for body-mass index and waist circumference attenuated the association between recent quitting and IFG (OR 1.07 [0.78-1.48]) and T2DM (OR 1.28 [0.48-3.40]. CONCLUSION: In this middle-aged population, smoking cessation was not associated with an increased risk of IFG or T2DM.

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BACKGROUND: While the association between smoking and arterial cardiovascular events has been well established, the association between smoking and venous thromboembolism (VTE) remains controversial. OBJECTIVES: To assess the association between smoking and the risk of recurrent VTE and bleeding in patients who have experienced acute VTE. PATIENTS/METHODS: This study is part of a prospective Swiss multicenter cohort that included patients aged ≥65years with acute VTE. Three groups were defined according to smoking status: never, former and current smokers. The primary outcome was the time to a first symptomatic, objectively confirmed VTE recurrence. Secondary outcomes were the time to a first major and clinically relevant non-major bleeding. Associations between smoking status and outcomes were analysed using proportional hazard models for the subdistribution of a competing risk of death. RESULTS: Among 988 analysed patients, 509 (52%) had never smoked, 403 (41%) were former smokers, and 76 (8%) current smokers. After a median follow-up of 29.6months, we observed a VTE recurrence rate of 4.9 (95% confidence interval [CI] 3.7-6.4) per 100 patient-years for never smokers, 6.6 (95% CI 5.1-8.6) for former smokers, and 5.2 (95% CI 2.6-10.5) for current smokers. Compared to never smokers, we found no association between current smoking and VTE recurrence (adjusted sub-hazard ratio [SHR] 1.05, 95% CI 0.49-2.28), major bleeding (adjusted SHR 0.59, 95% CI 0.25-1.39), and clinically relevant non-major bleeding (adjusted SHR 1.21, 95% CI 0.73-2.02). CONCLUSIONS: In this multicentre prospective cohort study, we found no association between smoking status and VTE recurrence or bleeding in elderly patients with VTE.

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Collection : Les archives de la Révolution française ; 8.262