Prevalence and factors associated with difficulty and intention to quit smoking in Switzerland.

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.

Biomedical risk assessment as an aid for smoking cessation.

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. 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 the Cochrane Collaboration Tobacco Addiction Group Specialized Register, Cochrane Central Register of Controlled Trials 2008 Issue 4, MEDLINE (1966 to January 2009), and EMBASE (1980 to January 2009). 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. Results were expressed as a relative risk (RR) for smoking cessation with 95% confidence intervals (CI). Where appropriate a pooled effect was estimated using a Mantel-Haenszel fixed effect method. MAIN RESULTS: We included eleven trials using a variety of biomedical tests. Two pairs of trials had sufficiently similar recruitment, setting and interventions to calculate a pooled effect; there was no evidence that CO measurement in primary care (RR 1.06, 95% CI 0.85 to 1.32) or spirometry in primary care (RR 1.18, 95% CI 0.77 to 1.81) increased cessation rates. We did not pool the other seven trials. One trial in primary care detected a significant benefit of lung age feedback after spirometry (RR 2.12; 95% CI 1.24 to 3.62). One trial that used ultrasonography of carotid and femoral arteries and photographs of plaques detected a benefit (RR 2.77; 95% CI 1.04 to 7.41) but enrolled a population of light smokers. Five trials failed to detect evidence of a significant effect. One of these tested CO feedback alone and CO + genetic susceptibility as two different intervention; none of the three possible comparisons detected significant effects. Three others used a combination of CO and spirometry feedback in different settings, and one tested for a genetic marker. AUTHORS' CONCLUSIONS: There is little evidence about the effects of most types of biomedical tests for risk assessment. Spirometry combined with an interpretation of the results in terms of 'lung age' had a significant effect in a single good quality trial. Mixed quality evidence does not support the hypothesis that other types of biomedical risk assessment increase smoking cessation in comparison to standard treatment. Only two pairs of studies were similar enough in term of recruitment, setting, and intervention to allow meta-analysis.

The joint influence of gender and amount of smoking on weight gain one year after smoking cessation.

Weight gain is often associated with smoking cessation and may discourage smokers from quitting. This study estimated the weight gained one year after smoking cessation and examined the risk factors associated with weight gain in order to identify socio-demographic groups at higher risk of increased weight after quitting. We analyzed data from 750 adults in two randomized controlled studies that included smokers motivated to quit and found a gradient in weight gain according to the actual duration of abstinence during follow-up. Subjects who were abstinent for at least 40 weeks gained 4.6 kg (SD = 3.8) on average, compared to 1.2 kg (SD = 2.6) for those who were abstinent less than 20 weeks during the 1-year follow-up. Considering the duration of abstinence as an exposure variable, we found an age effect and a significant interaction between sex and the amount of smoking before quitting: younger subjects gained more weight than older subjects; among light smokers, men gained more weight on average than women one year after quitting, while the opposite was observed among heavy smokers. Young women smoking heavily at baseline had the highest risk of weight gain after quitting.

High expectation in non-evidence-based smoking cessation interventions among smokers--the CoLaus study.

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.

Biomedical risk assessment as an aid for smoking cessation.

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.