195 resultados para Indoor smoking ban
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BACKGROUND: Immunodeficiency and AIDS-related pulmonary infections have been suggested as independent causes of lung cancer among HIV-infected persons, in addition to smoking. METHODS: A total of 68 lung cancers were identified in the Swiss HIV Cohort Study (SHCS) or through linkage with Swiss Cancer Registries (1985-2010), and were individually matched to 337 controls by centre, gender, HIV-transmission category, age and calendar period. Odds ratios (ORs) were estimated by conditional logistic regression. RESULTS: Overall, 96.2% of lung cancers and 72.9% of controls were ever smokers, confirming the high prevalence of smoking and its strong association with lung cancer (OR for current vs never=14.4, 95% confidence interval (95% CI): 3.36-62.1). No significant associations were observed between CD4+ cell count and lung cancer, neither when measured within 1 year (OR for <200 vs ≥500=1.21, 95% CI: 0.49-2.96) nor further back in time, before lung cancer diagnosis. Combined antiretroviral therapy was not significantly associated with lung cancer (OR for ever vs never=0.67, 95% CI: 0.29-1.52), and nor was a history of AIDS with (OR=0.49, 95% CI: 0.19-1.28) or without (OR=0.53, 95% CI: 0.24-1.18) pulmonary involvement. CONCLUSION: Lung cancer in the SHCS does not seem to be clearly associated with immunodeficiency or AIDS-related pulmonary disease, but seems to be attributable to heavy smoking.
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Rapport de synthèse : Introduction : plusieurs études observationnelles suggèrent qu'il existe une association entre le tabagisme actif et l'incidence du diabète de type 2. Toutefois de telles études n'ont jamais été synthétisées de façon systématique. Objectif : conduire une revue systématique avec meta-analyse des études évaluant l'association entre le tabagisme actif et l'incidence du diabète de type 2. Méthode : nous avons effectué une recherche dans les bases de donnée électroniques MEDLINE et EMBASE de 1966 à mai 2007, et l'avons complétée par une recherche manuelle des bibliographies des articles clés retenus ainsi que par la recherche d'abstracts de congrès scientifiques et le contact d'experts. Pour être inclues dans notre revue, les études devaient avoir un design de type cohorte, reporter un risque de glycémies jeun élevée, d'intolérance au glucose ou de diabète de type 2 en relation avec le statut tabagique des participants lors du recrutement et devaient exclure les sujets avec un diabète au début de l'étude. Deux auteurs ont sélectionné de façon indépendante les études et ont extrait les données. Les risques relatifs de diabète étaient ensuite compilés, utilisant un modèle de type « random effect ». Résultats : la recherche a aboutit à 25 études de cohorte prospectives (N=1'165'374 participants) et a reporté en tout 45'844 cas de diabète de type 2 pendant une durée de suivi s'étendant sur 5 à 30 années. Sur les 25 études, 24 reportaient un risque augmenté de diabète chez les fumeurs par comparaison aux non fumeurs. Le risque relatif (RR) commun de toutes les études était de 1.44 (intervalle de confiance (IC) à 95% : 1.31-1.58). Le risque de diabète était plus élevé chez les fumeurs de plus de 20 cigarettes par jour (RR : 1.61, IC 95% : 1.43-1.80) en comparaison aux fumeurs ayant une consommation inférieure (RR : 1.29, IC 95% : 1.13-1.48) et le risque était moindre pour les anciens fumeurs (RR :1.23; IC 95% : 1.14-1.33) comparé aux fumeurs actifs. Ces éléments parlent en faveur d'un effet dose-réponse et donc d'une relation de causalité, sans pour autant la prouver. Conclusion : notre étude révèle que le tabagisme actif est associé avec un risque augmenté de 44% de diabète de type 2. Des recherches futures sont nécessaires pour évaluer si cette association est causale et pour clarifier les mécanismes d'action. Dans l'intervalle, les professionnels de santé devraient mentionner l'éviction du diabète comme une raison supplémentaire d'arrêter de fumer ou de ne pas commencer à fumer.
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Purpose: There is evidence indicating that adolescent females smoke as a way to control weight. The aim of our research is to assess whether daily smoking is a marker for weight control practices among adolescent females. Methods: Data were drawn from the 2002 Swiss Multicenter Adolescent Survey on Health (SMASH02) data base, a survey including 7,548 [3,838 females] in-school adolescents aged 16-20 years in Switzerland. Among females self-reporting BMI (N _ 3,761), two groups were drawn: daily smokers (DS, N _ 1,273) included all those smoking at least 1 cigarette/day and never smokers (NS, N _ 1,888) included all those having never smoked. Former (N _ 177) and occasional (N _ 423) smokers were not included. Groups were compared on weight control practices (being on a diet, self-induced vomiting, use of doctor-prescribed or over-the-counter appetite suppressors) controlling for possible confounding variables (age, BMI, feeling fat, body image, use of other substances, depression, sport practice, academic track and perceived advanced puberty). Analyses were performed with STATA 9. Bivariate analyses are presented as point-prevalence and multivariate analysis (using logistic regression) are presented as adjusted odds ratio (AOR) and [95% confidence interval]. Results: In the bivariate analysis, DS females were significantly more likely (p _ 0.001) than NS to be on a diet (DS: 33.2%, NS: 22.2%), to self-induce vomiting (DS: 9.0%, NS: 3.3%), and to use doctor prescribed (DS: 2.3%, NS: 0.9%) or over-the-counter (DS: 3.2%, NS: 1.2%) appetite suppressors. In the multivariate analysis, DS females were more likely than NS to be on a diet (AOR: 1.40 [1.17/1.68]), to self-induce vomiting (AOR: 2.07 [1.45/2.97]), and to use doctor-prescribed appetite suppressors (AOR: 1.99 [1.00/ 3.96]). Conclusions: Weight control practices are more frequent among female daily smokers than among never smokers. This finding seems to confirm cigarette smoking as a way to control weight among adolescent females. Health professionals should inquire adolescent female smokers about weight control practices, and this association must be kept in mind when discussing tobacco cessation options with adolescent females. Sources of Support: The SMASH02 survey was funded by the Swiss Federal Office of Public Health and the participating cantons.
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BACKGROUND: Tobacco dependence is the leading cause of preventable death and disabilities worldwide and nicotine is the main substance responsible for the addiction to tobacco. A vaccine against nicotine was tested in a 6-month randomized, double blind phase II smoking cessation study in 341 smokers with a subsequent 6-month follow-up period. METHODOLOGY/PRINCIPAL FINDINGS: 229 subjects were randomized to receive five intramuscular injections of the nicotine vaccine and 112 to receive placebo at monthly intervals. All subjects received individual behavioral smoking cessation counseling. The vaccine was safe, generally well tolerated and highly immunogenic, inducing a 100% antibody responder rate after the first injection. Point prevalence of abstinence at month 2 showed a statistically significant difference between subjects treated with Nicotine-Qbeta (47.2%) and placebo (35.1%) (P = 0.036), but continuous abstinence between months 2 and 6 was not significantly different. However, in subgroup analysis of the per-protocol population, the third of subjects with highest antibody levels showed higher continuous abstinence from month 2 until month 6 (56.6%) than placebo treated participants (31.3%) (OR 2.9; P = 0.004) while medium and low antibody levels did not increase abstinence rates. After 12 month, the difference in continuous abstinence rate between subjects on placebo and those with high antibody response was maintained (difference 20.2%, P = 0.012). CONCLUSIONS: Whereas Nicotine-Qbeta did not significantly increase continuous abstinence rates in the intention-to-treat population, subgroup analyses of the per-protocol population suggest that such a vaccination against nicotine can significantly increase continuous abstinence rates in smokers when sufficiently high antibody levels are achieved. Immunotherapy might open a new avenue to the treatment of nicotine addiction. TRIAL REGISTRATION: Swiss Medical Registry 2003DR2327; ClinicalTrials.gov NCT00369616.
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Smoking, obesity and diabetes are among the leading cause of premature death worldwide. Smokers have globally a lower body weight compared with non smokers but they tend to accumulate more fat in the abdomen. Most smokers gain weight when they quit smoking, however this does not seem to diminish the health benefits associated with smoking cessation. Smoking increases the risk of developing type 2 diabetes. Among people with diabetes, smoking significantly increases the risks of complications and mortality. Interventions with pharmacologic help should be offered to all smokers, with or without diabetes, in order to increase smoking cessation rates and limit weight gain.
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INTRODUCTION: This study examines the relationship between nicotine exposure and tobacco addiction among young smokers consuming either only tobacco or only tobacco and cannabis. METHODS: Data on tobacco and cannabis use were collected by a questionnaire among 313 adolescents and young adults in Western Switzerland between 2009 and 2010. In addition, a urine sample was used to determine urinary cotinine level. Nicotine addiction was measured using the Fagerström Test for Nicotine Dependence (FTND). In this study, we focused on a sample of 142 participants (mean age 19.54) that reported either smoking only tobacco cigarettes (CIG group, n = 70) or smoking both tobacco cigarettes and cannabis (CCS group, n = 72). RESULTS: The FTND did not differ significantly between CIG (1.96 ± 0.26) and CCS (2.66 ± 0.26) groups (p = 0.07). However, participants in the CCS group smoked more cigarettes (8.30 ± 0.79 vs. 5.78 ± 0.8, p = 0.03) and had a higher mean cotinine value (671.18 ± 67.6 vs. 404.32 ± 68.63, p = 0.008) than the CIG group. Further, the association between cotinine and FTND was much stronger among the CIG than among the CCS group (regression coefficient of 0.0031 vs. 0.00099, p < 0.0001). CONCLUSION: Adolescents smoking tobacco and cannabis cigarettes featured higher levels of cotinine than youth smoking only tobacco; however, there was no significant difference in the addiction score. The FTND score is intended to measure nicotine dependence from smoked tobacco cigarettes. Hence, to accurately determine nicotine exposure and the associated dependence among young smokers, it seems necessary to inquire about cannabis consumption.
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BACKGROUND: Smoking contributes to reasons for hospitalisation, and the period of hospitalisation may be a good time to provide help with quitting. OBJECTIVES: To determine the effectiveness of interventions for smoking cessation that are initiated for hospitalised patients. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Group register which includes papers identified from CENTRAL, MEDLINE, EMBASE and PsycINFO in December 2011 for studies of interventions for smoking cessation in hospitalised patients, using terms including (hospital and patient*) or hospitali* or inpatient* or admission* or admitted. SELECTION CRITERIA: Randomized and quasi-randomized trials of behavioural, pharmacological or multicomponent interventions to help patients stop smoking, conducted with hospitalised patients who were current smokers or recent quitters (defined as having quit more than one month before hospital admission). The intervention had to start in the hospital but could continue after hospital discharge. We excluded studies of patients admitted to facilities that primarily treat psychiatric disorders or substance abuse, studies that did not report abstinence rates and studies with follow-up of less than six months. Both acute care hospitals and rehabilitation hospitals were included in this update, with separate analyses done for each type of hospital. DATA COLLECTION AND ANALYSIS: Two authors extracted data independently for each paper, with disagreements resolved by consensus. MAIN RESULTS: Fifty trials met the inclusion criteria. Intensive counselling interventions that began during the hospital stay and continued with supportive contacts for at least one month after discharge increased smoking cessation rates after discharge (risk ratio (RR) 1.37, 95% confidence interval (CI) 1.27 to 1.48; 25 trials). A specific benefit for post-discharge contact compared with usual care was found in a subset of trials in which all participants received a counselling intervention in the hospital and were randomly assigned to post-discharge contact or usual care. No statistically significant benefit was found for less intensive counselling interventions. Adding nicotine replacement therapy (NRT) to an intensive counselling intervention increased smoking cessation rates compared with intensive counselling alone (RR 1.54, 95% CI 1.34 to 1.79, six trials). Adding varenicline to intensive counselling had a non-significant effect in two trials (RR 1.28, 95% CI 0.95 to 1.74). Adding bupropion did not produce a statistically significant increase in cessation over intensive counselling alone (RR 1.04, 95% CI 0.75 to 1.45, three trials). A similar pattern of results was observed in a subgroup of smokers admitted to hospital because of cardiovascular disease (CVD). In this subgroup, intensive intervention with follow-up support increased the rate of smoking cessation (RR 1.42, 95% CI 1.29 to 1.56), but less intensive interventions did not. One trial of intensive intervention including counselling and pharmacotherapy for smokers admitted with CVD assessed clinical and health care utilization endpoints, and found significant reductions in all-cause mortality and hospital readmission rates over a two-year follow-up period. These trials were all conducted in acute care hospitals. A comparable increase in smoking cessation rates was observed in a separate pooled analysis of intensive counselling interventions in rehabilitation hospitals (RR 1.71, 95% CI 1.37 to 2.14, three trials). AUTHORS' CONCLUSIONS: High intensity behavioural interventions that begin during a hospital stay and include at least one month of supportive contact after discharge promote smoking cessation among hospitalised patients. The effect of these interventions was independent of the patient's admitting diagnosis and was found in rehabilitation settings as well as acute care hospitals. There was no evidence of effect for interventions of lower intensity or shorter duration. This update found that adding NRT to intensive counselling significantly increases cessation rates over counselling alone. There is insufficient direct evidence to conclude that adding bupropion or varenicline to intensive counselling increases cessation rates over what is achieved by counselling alone.
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BACKGROUND: By reducing the amount of nicotine that reaches the brain when a person smokes a cigarette, nicotine vaccines may help people to stop smoking or to prevent recent quitters from relapsing. OBJECTIVES: The aims of this review are to assess the efficacy of nicotine vaccines for smoking cessation and for relapse prevention, and to assess the frequency and type of adverse events associated with the use of nicotine vaccines. SEARCH METHODS: We searched the Cochrane Tobacco Addiction Review Group specialised register for trials, using the term 'vaccine' in the title or abstract, or in a keyword (date of most recent search April 2012). To identify any other material including reviews and papers potentially relevant to the background or discussion sections, we also searched MEDLINE, EMBASE, and PsycINFO, combining terms for nicotine vaccines with terms for smoking and tobacco use, without design limits or limits for human subjects. We searched the Annual Meeting abstracts of the Society for Research on Nicotine and Tobacco up to 2012, using the search string 'vaccin'. We searched Google Scholar for 'nicotine vaccine'. We also searched company websites and Google for information related to specific vaccines. We searched clinicaltrials.gov in March 2012 for 'nicotine vaccine' and for the trade names of known vaccine candidates. SELECTION CRITERIA: We included randomized controlled trials of nicotine vaccines, at Phase II and Phase III trial stage and beyond, in adult smokers or recent ex-smokers. We included studies of nicotine vaccines used as part of smoking cessation or relapse prevention interventions. DATA COLLECTION AND ANALYSIS: We extracted data on the type of participants, the dose and duration of treatment, the outcome measures, the randomization procedure, concealment of allocation, blinding of participants and personnel, reporting of outcomes, and completeness of follow-up.Our primary outcome measure was a minimum of six months abstinence from smoking. We used the most rigorous definition of abstinence, and preferred cessation rates at 12 months and biochemically validated rates where available. We have used the risk ratio (RR) to summarize individual trial outcomes. We have not pooled the current group of included studies as they cover different vaccines and variable regimens. MAIN RESULTS: There are no nicotine vaccines currently licensed for public use, but there are a number in development. We found four trials which met our inclusion criteria, three comparing NicVAX to placebo and one comparing NIC002 (formerly NicQbeta) to placebo. All were smoking cessation trials conducted by pharmaceutical companies as part of the drug development process, and all trials were judged to be at high or unclear risk of bias in at least one domain. Overall, 2642 smokers participated in the included studies in this review. None of the four included studies detected a statistically significant difference in long-term cessation between participants receiving vaccine and those receiving placebo. The RR for 12 month cessation in active and placebo groups was 1.35 (95% Confidence Interval (CI) 0.82 to 2.22) in the trial of NIC002 and 1.74 (95% CI 0.73 to 4.18) in one NicVAX trial. Two Phase III NicVAX trials, for which full results were not available, reported similar quit rates of approximately 11% in both groups. In the two studies with full results available, post hoc analyses detected higher cessation rates in participants with higher levels of nicotine antibodies, but these findings are not readily generalisable. The two studies with full results showed nicotine vaccines to be well tolerated, with the majority of adverse events classified as mild or moderate. In the study of NIC002, participants receiving the vaccine were more likely to report mild to moderate adverse events, most commonly flu-like symptoms, whereas in the study of NicVAX there was no significant difference between the two arms. Information on adverse events was not available for the large Phase III trials of NicVAX.Vaccine candidates are likely to undergo significant changes before becoming available to the general public, and those included in this review may not be the first to reach market; this limits the external validity of the results reported in this review in terms of both effectiveness and tolerability. AUTHORS' CONCLUSIONS: There is currently no evidence that nicotine vaccines enhance long-term smoking cessation. Rates of serious adverse events recorded in the two trials with full data available were low, and the majority of adverse events reported were at mild to moderate levels. The evidence available suggests nicotine vaccines do not induce compensatory smoking or affect withdrawal symptoms. No nicotine vaccines are currently licensed for use in any country but a number are under development.Further trials of nicotine vaccines are needed, comparing vaccines with placebo for smoking cessation. Further trials are also needed to explore the potential of nicotine vaccines to prevent relapse. Results from past, current and future research should be reported in full. Adverse events and serious adverse events should continue to be carefully monitored and thoroughly reported.
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BACKGROUND: The association between smoking and total energy expenditure (TEE) is still controversial. We examined this association in a multi-country study where TEE was measured in a subset of participants by the doubly labeled water (DLW) method, the gold standard for this measurement. METHODS: This study includes 236 participants from five different African origin populations who underwent DLW measurements and had complete data on the main covariates of interest. Self-reported smoking status was categorized as either light (<7 cig/day) or high (≥7 cig/day). Lean body mass was assessed by deuterium dilution and physical activity (PA) by accelerometry. RESULTS: The prevalence of smoking was 55% in men and 16% in women with a median of 6.5 cigarettes/day. There was a trend toward lower BMI in smokers than non-smokers (not statistically significant). TEE was strongly correlated with fat-free mass (men: 0.70; women: 0.79) and with body weight (0.59 in both sexes). Using linear regression and adjusting for body weight, study site, age, PA, alcohol intake and occupation, TEE was larger in high smokers than in never smokers among men (difference of 298 kcal/day, p = 0.045) but not among women (162 kcal/day, p = 0.170). The association became slightly weaker in men (254 kcal/day, p = 0.058) and disappeared in women (-76 kcal/day, p = 0.380) when adjusting for fat-free mass instead of body weight. CONCLUSION: There was an association between smoking and TEE among men. However, the lack of an association among women, which may be partly related to the small number of smoking women, also suggests a role of unaccounted confounding factors.
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OBJECTIVE: To describe the determinants of self-initiated smoking cessation of duration of at least 6 months as identified in longitudinal population-based studies of adolescent and young adult smokers. METHODS: A systematic search of the PubMed and EMBASE databases using smoking, tobacco, cessation, quit and stop as keywords was performed. Limits included articles related to humans, in English, published between January 1984 and August 2010, and study population aged 10-29 years. A total of 4502 titles and 871 abstracts were reviewed independently by 2 and 3 reviewers, respectively. Nine articles were retained for data abstraction. Data on study location, timeframe, duration of follow-up, number of data collection points, sample size, age/grade of participants, number of quitters, smoking status at baseline, definition of cessation, covariates and analytic method were abstracted from each article. The number of studies that reported a statistically significant association between each determinant investigated and cessation were tabulated, from among all studies that assessed the determinant. RESULTS: Despite heterogeneity in methods across studies, five factors robustly predicted quitting across studies in which the factor was investigated: not having friends who smoke, not having intentions to smoke in the future, resisting peer pressure to smoke, being older at first use of cigarette and having negative beliefs about smoking. CONCLUSIONS: The literature on longitudinal predictors of cessation in adolescent and young adult smokers is not well developed. Cessation interventions for this population will remain less than optimally effective until there is a solid evidence base on which to develop interventions.
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The worldwide prevalence of smoking has been estimated at about 50% in men, and 10% in women, with larger variations among different populations studied. Smoking has been shown to affect many organ systems resulting in severe morbidity and increased mortality. In addition, smoking has been identified as a predictor of ten-year fracture risk in men and women, largely independent of an individual's bone mineral density. This finding has eventually lead to incorporation of this risk factor into FRAX®, an algorithm that has been developed to calculate an individual's ten-year fracture risk. However, only little, or conflicting data is available on a possible association between smoking dose, duration, length of time after cessation, type of tobacco and fracture risk, limiting this risk factor's applicability in the context of FRAX®.
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BACKGROUND: Although smokers tend to have a lower body-mass index (BMI) than non-smokers, smoking may affect body fat (BF) distribution. Some studies have assessed the association between smoking, BMI and waist circumference (WC), but, to our knowledge, no population-based studies assessed the relation between smoking and BF composition. We assessed the association between amount of cigarette smoking, BMI, WC and BF composition. METHODS: Data was analysed from a cross-sectional population-based study including 6187 Caucasians aged 32-76 and living in Switzerland. Height, weight and WC were measured. BF, expressed in percent of total body weight, was measured by electrical bioimpedance. Obesity was defined as a BMI>=30 kg/m2 and normal weight as a BMI<25 kg/m2. Abdominal obesity was defined as a WC>=102 cm for men and >=88 cm for women and normal WC as <94 cm for men and <80 cm for women. In men, excess BF was defined as %BF >=28.1, 28.7, 30.6 and 32.6 for age groups 32-44, 45-54, 55-64 and 65-76, respectively; the corresponding values for women were 35.9, 36.5, 40.5 and 44.4. Cigarette smoking was assessed using a self-reported questionnaire. RESULTS: 29.3% of men and 25.0% of women were smokers. Prevalence of obesity, abdominal obesity, and excess of BF was 16.9% and 26.6% and 14.2% in men and 15.0%, 33.0% and 27.5% in women, respectively. Smokers had lower age-adjusted mean BMI, WC and percent of BF compared to non-smokers. However, among smokers,mean age-adjusted BMI,WC and BF increased with the number of cigarettes smoked per day: among light (1-10 cig/day), moderate (11-20) and heavy smokers (>20), mean +/-SE %BF was 22.4 +/−0.3, 23.1+/−0.3 and 23.5+/−0.4 for men, and 31.9+/−0.3, 32.6+/−0.3 and 32.9+/−0.4 for women, respectively. Mean WC was 92.9+/−0.6, 94.0+/−0.5 and 96.0+/−0.6 cm for men, and 80.2+/−0.5, 81.3+/−0.5 and 83.3+/−0.7 for women, respectively. Mean BMI was 25.7+/−0.2, 26.0+/−0.2, and 26.1+/−0.2 kg/m2 for men; and 23.6+/−0.2, 24.0+/−0.2 and 24.1+/−0.3 for women, respectively. Compared with light smokers, the age-adjusted odds ratio (95% Confidence Interval) for excess of BF was 1.04 (0.58 to 1.85) formoderatesmokers and 1.06 (0.57 to 1.99) for heavy smokers in men (p-trend = 0.9), and 1.35 (0.92 to 1.99) and 2.26 (1.38 to 3.72), respectively, in women (p-trend = 0.04). Odds ratio for abdominal obesity vs. normal WC was 1.32 (0.81 to 2.15) for moderate smokers and 1.95 (1.16 to 3.27) for heavy smokers in men (p-trend < 0.01), and 1.15 (0.79 to 1.69) and 2.36 (1.41 to 3.93) in women (p-trend = 0.03). Odds ratio for obesity vs. normal weight was 1.35 (0.76 to 2.41) for moderate smokers and 1.33 (0.71 to 2.49) for heavy smokers in men (p-trend = 0.9) and 0.78 (0.45 to 1.35) and 1.44 (0.73 to 2.85), in women (p-trend = 0.08). CONCLUSIONS: WC and BF were positively and dose-dependently associated with the number of cigarettes smoked per day in women, whereas onlyWC was dose dependently and significantly associated with the amount of cigarettes smoked per day in men. This suggests that heavy smokers, especially women, are more likely to have an excess of BF and to accumulate BF in the abdomen compared to lighter smokers.
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The objective of this study was to evaluate the association between cigarette smoking and endometrial cancer risk by investigating potential modifying effects of menopausal status, obesity, and exogenous hormones. We pooled data from three case-control studies with the same study design conducted in Italy and Switzerland between 1982 and 2006. Overall, 1446 incident endometrial cancers and 4076 hospital controls were enrolled. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using logistic regression models, conditioned on study and centre, and adjusted for age, period of interview, age at menarche, parity, and body mass index. In comparison with never smokers, current smokers showed reduced endometrial cancer risk (OR: 0.80; 95% CI: 0.66-0.96), with a 28% decrease in risk for smoking >/=20 cigarettes/day. The association did not vary according to menopausal status, oral contraceptive use, or hormone replacement therapy. However, heterogeneity emerged according to body mass index among postmenopausal women, with obese women showing the greatest risk reduction for current smoking (OR: 0.47; 95% CI: 0.27-0.81). In postmenopausal women, obesity turned out to be an important modifier of the association between cigarette smoking and the risk of endometrial cancer. This finding calls for caution in interpreting the favorable effects of cigarette smoking, considering the toxic and carcinogenic effects of tobacco.