Genetic variation at CHRNA5-CHRNA3-CHRNB4 interacts with smoking status to influence body mass index.

BACKGROUND: Cigarette smoking is associated with lower body mass index (BMI), and a commonly cited reason for unwillingness to quit smoking is a concern about weight gain. Common variation in the CHRNA5-CHRNA3-CHRNB4 gene region (chromosome 15q25) is robustly associated with smoking quantity in smokers, but its association with BMI is unknown. We hypothesized that genotype would accurately reflect smoking exposure and that, if smoking were causally related to weight, it would be associated with BMI in smokers, but not in never smokers. METHODS: We stratified nine European study samples by smoking status and, in each stratum, analysed the association between genotype of the 15q25 SNP, rs1051730, and BMI. We meta-analysed the results (n = 24 198) and then tested for a genotype × smoking status interaction. RESULTS: There was no evidence of association between BMI and genotype in the never smokers {difference per T-allele: 0.05 kg/m(2) [95% confidence interval (95% CI): -0.05 to 0.18]; P = 0.25}. However, in ever smokers, each additional smoking-related T-allele was associated with a 0.23 kg/m(2) (95% CI: 0.13-0.31) lower BMI (P = 8 × 10(-6)). The effect size was larger in current [0.33 kg/m(2) lower BMI per T-allele (95% CI: 0.18-0.48); P = 6 × 10(-5)], than in former smokers [0.16 kg/m(2) (95% CI: 0.03-0.29); P = 0.01]. There was strong evidence of genotype × smoking interaction (P = 0.0001). CONCLUSIONS: Smoking status modifies the association between the 15q25 variant and BMI, which strengthens evidence that smoking exposure is causally associated with reduced BMI. Smoking cessation initiatives might be more successful if they include support to maintain a healthy BMI.

Stratification by smoking status reveals an association of CHRNA5-A3-B4 genotype with body mass index in never smokers.

We previously used a single nucleotide polymorphism (SNP) in the CHRNA5-A3-B4 gene cluster associated with heaviness of smoking within smokers to confirm the causal effect of smoking in reducing body mass index (BMI) in a Mendelian randomisation analysis. While seeking to extend these findings in a larger sample we found that this SNP is associated with 0.74% lower body mass index (BMI) per minor allele in current smokers (95% CI -0.97 to -0.51, P = 2.00 × 10(-10)), but also unexpectedly found that it was associated with 0.35% higher BMI in never smokers (95% CI +0.18 to +0.52, P = 6.38 × 10(-5)). An interaction test confirmed that these estimates differed from each other (P = 4.95 × 10(-13)). This difference in effects suggests the variant influences BMI both via pathways unrelated to smoking, and via the weight-reducing effects of smoking. It would therefore be essentially undetectable in an unstratified genome-wide association study of BMI, given the opposite association with BMI in never and current smokers. This demonstrates that novel associations may be obscured by hidden population sub-structure. Stratification on well-characterized environmental factors known to impact on health outcomes may therefore reveal novel genetic associations.

Smoking status and tumor necrosis factor-alpha mediated systemic inflammation in COPD patients

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bleeding on probing as it relates to smoking status in patients enrolled in supportive periodontal therapy for at least 5 years

AIM To relate the mean percentage of bleeding on probing (BOP) to smoking status in patients enrolled in supportive periodontal therapy (SPT). MATERIALS AND METHODS Retrospective data on BOP from 8'741 SPT visits were related to smoking status among categories of both periodontal disease severity and progression (instability) in patients undergoing dental hygiene treatment at the Medi School of Dental Hygiene (MSDH), Bern, Switzerland 1985-2011. RESULTS A total of 445 patients were identified with 27.2% (n = 121) being smokers, 27.6% (n = 123) former smokers and 45.2% (n = 201) non-smokers. Mean BOP statistically significantly increased with disease severity (p = 0.0001) and periodontal instability (p = 0.0115) irrespective of the smoking status. Periodontally stable smokers (n = 30) categorized with advanced periodontal disease demonstrated a mean BOP of 16.2% compared to unstable smokers (n = 15) with a mean BOP of 22.4% (p = 0.0291). Assessments of BOP in relation to the percentage of sites with periodontal probing depths (PPD) ≥ 4 mm at patient-level yielded a statistically significantly decreased proportion of BOP in smokers compared to non-smokers and former smokers (p = 0.0137). CONCLUSIONS Irrespective of the smoking status, increased mean BOP in SPT patients relates to disease severity and periodontal instability while smokers demonstrate lower mean BOP concomitantly with an increased prevalence of residual PPDs.

The role of smoking status on postoperative complications and survival in lung cancer patients presenting to M.D. Anderson Cancer Center

It is estimated that 50% of all lung cancer patients continue to smoke after diagnosis. Many of these lung cancer patients who are current smokers often experience tremendous guilt and responsibility for their disease, and feel it might be too late for them to quit smoking. In addition, many oncologists may be heard to say that it is 'too late', 'it doesn't matter', 'it is too difficult', 'it is too stressful' for their patients to stop smoking, or they never identify the smoking status of the patient. Many oncologists feel unprepared to address smoking cessation as part of their clinical practice. In reality, physicians can have tremendous effects on motivating patients, particularly when patients are initially being diagnosed with cancer. More information is needed to convince patients to quit smoking and to encourage clinicians to assist patients with their smoking cessation. ^ In this current study, smoking status at time of lung cancer diagnosis was assessed to examine its impact on complications and survival, after exploring the reliability of smoking data that is self-reported. Logistic Regression was used to determine the risks of smoking prior to lung resection. In addition, survival analysis was performed to examine the impact of smoking on survival. ^ The reliability of how patients report their smoking status was high, but there was some discordance between current smokers and recent quitters. In addition, we found that cigarette pack-year history and duration of smoking cessation were directly related to the rate of a pulmonary complication. In regards to survival, we found that current smoking at time of lung cancer diagnosis was an independent predictor of early stage lung cancer. This evidence supports the idea that it is "never too late" for patients to quit smoking and health care providers should incorporate smoking status regularly into their clinical practice.^

Hypertension, dyslipidemia, body mass index, Diabetes and smoking status in aboriginal australians in a remote community

Objectives: Study objectives were: 1) to describe the differences in the prevalence of CHID risk factors between Aboriginal people in a remote community and the general Australian population; and 2) to compare the predicted risks of CHD events between Aboriginal and non-Aboriginal Australians. Design: A cross-sectional study. Participants: 681 Aboriginal adults aged 25 to 74 years. Results: Aboriginal young adults had substantially higher prevalence of diabetes compared to non-Aboriginal Australians. The prevalence ratios for diabetes were 12.5, 5.6, 3.2, 1.3, and 0.73 for 25-, 35-, 45-, 55-, and 65- to 74-year-old females, respectively, The corresponding values for males were 12.1, 2.7, 2.9, 0.69, and 0.42. Young females had a higher prevalence of obesity, overweight, and abnormal waist circumference, while males and females 45 years and older tended to have a lower prevalence of overweight and ab. normal waist circumference. Compared to the general population, Aboriginal adults had a lower prevalence of abnormal total cholesterol but a higher prevalence of abnormal HDL, triglycerides, hypertension, and smoking. The risk ratios of abnormal total cholesterol for females ages 2534, 35-44, 45-54, 55-64, and 65-75 years were 0.38, 0.53, 0.48, 0.48, and 0.41, respectively. Conclusions: Aboriginal people in the remote community experienced different levels of CHD risk predictors from the general Australian population. They had a lower prevalence of abnormal total cholesterol and a higher prevalence of abnormal HDL, smoking, diabetes, and hypertension.

Smoking status of Australian general practice patients and their attempts to quit

This paper seeks to report on smoking rates, quit attempt methods and success rates among adult patients attending Australian general practice. A cluster cross-sectional survey was used to survey adult patients (18+), who attended Australian GPs in during 2002 and 2003. Over a quarter of patients (27.3%; 95% CI: 26.0-28.7) were former smokers and one in five (21.5%; 95% CI: 20.1-22.9) were current smokers. Ninety-two percent of former and 80% of current smokers used only one method in their last quit attempt with cold turkey the most common method used by both former (88%) and current (62%) smokers. Overall, success rates varied from 77% for cold turkey to 23% for bupropion. Success rates were re-analysed to consider quit attempts post-bupropion listing, with success rate for cold turkey reduced to 40% while bupropion remained reasonably constant at 21%. By tailoring smoking cessation interventions to a smokers' preparedness to quit, scope exists to increase the pool of smokers offered strategies that are more effective in achieving abstinence and avoiding relapse rather than relying on less effective self-quitting behaviours such as cold turkey. (c) 2005 Elsevier Ltd. All rights reserved.

Work stress, smoking status and smoking intensity: an observational study of 46 190 employees

Study objective: To examine the relationship between work stress, as indicated by the job strain model and the effort-reward imbalance model, and smoking. Setting: Ten municipalities and 21 hospitals in Finland. Design and Participants: Binary logistic regression models for the prevalence of smoking were related to survey responses of 37 309 female and 8881 male Finnish public sector employees aged 17-65. Separate multinomial logistic regression models were calculated for smoking intensity for 8130 smokers. In addition, binary logistic regression models for ex-smoking were fitted among 16 277 former and current smokers. In all analyses, adjustments were made for age, basic education, occupational status, type of employment and marital status. Main results: Respondents with high effort-reward imbalance or lower rewards were more likely to be smokers. Among smokers, an increased likelihood of higher intensity of smoking was associated with higher job strain and higher effort-reward imbalance and their components such as low job control and low rewards. Smoking intensity was also higher in active jobs in women, in passive jobs and among employees with low effort expenditure. Among former and current smokers, high job strain, high effort-reward imbalance and high job demands were associated with a higher likelihood of being a current smoker. Lower effort was associated with a higher likelihood of ex-smoking. Conclusions: This evidence suggests an association between work stress and smoking and implies that smoking cessation programs may benefit from the taking into account the modification of stressful features of work environment. Key words: effort-reward imbalance; job strain; smoking. Abbreviations: OR, odds ratio; CI, confidence interval; SES, socioeconomic status

Effect of maternal weight status on the relationship between prenatal smoking and infant birth weight

The purpose of this study was to assess the effect of maternal pre-pregnancy weight status on the relationship between prenatal smoking and infant birth weight (IBW). Prenatal cigarette smoking and maternal weight exert opposing effects on IBW; smoking decreases birth weight while maternal pre-pregnancy weight is positively correlated with birth weight. As such, mutual effect modification may be sufficiently significant to alter the independent effects of these two birth weight correlates. Finding of such an effect has implications of prenatal smoking cessation education. Perception of risk is an important determinant of smoking cessation, and reduced or low birth weight (LBW) as a smoking-associated risk predominates prenatal smoking counseling and education. In a population such as the US, where obesity is becoming epidemic, particularly among minority and low-income groups, perception of risk may be lowered should increased maternal size attenuate the effect of smoking. Previous studies have not found a significant interaction effect of prenatal smoking and maternal pre-pregnancy weight on IBW; however, use of self-reported smoking status may have biased findings. Reliability of self-reported smoking status reported in the literature is variable, with deception rates ranging from a low of 5% to as high as 16%. This study, using data from a prenatal smoking cessation project, in which smoking status was validated by saliva cotinine, was an opportunity to assess effect modification of smoking and maternal weight using biochemically determined smoking status in lieu of self report. Stratified by saliva cotinine, 151 women from a prenatal smoking cessation cohort, who were 18 years and older and had full-term, singleton births, were included in this study. The effect of smoking in terms of mean birth weight across three levels of maternal pre-pregnancy weight was assessed by general linear modeling procedures, adjusting for other known correlates of IBW. Effect modification was marginally significant, p = .104, but only with control for differential effects among racial/ethnic groups. A smaller than planned sample of nonsmokers, or women who quit smoking during the pregnancy, prohibited rejection of the null hypothesis of no difference in the effect of smoking across levels of pre-pregnancy weight. ^

Depression: a predictor of smoking relapse in a 6-month follow-up after hospitalization for acute coronary syndrome

Objective The objective of the study was to investigate whether depression is a predictor of postdischarge smoking relapse among patients hospitalized for myocardial infarction (MI) or unstable angina (ILIA), in a smoke-free hospital. Methods Current smokers with MI or UA were interviewed while hospitalized; patients classified with major depression (MD) or no humor disorder were reinterviewed 6 months post discharge to ascertain smoking status. Potential predictors of relapse (depression; stress; anxiety; heart disease risk perception; coffee and alcohol consumption; sociodemographic, clinical, and smoking habit characteristics) were compared between those with MD (n = 268) and no humor disorder (n = 135). Results Relapsers (40.4%) were more frequently and more severely depressed, had higher anxiety and lower self-efficacy scale scores, diagnosis of UA, shorter hospitalizations, started smoking younger, made fewer attempts to quit, had a consort less often, and were more frequently at the `precontemplation` stage of change. Multivariate analysis showed relapse-positive predictors to be MD [odds ratio (OR): 2.549; 95% confidence interval (CI): 1.519-4.275] (P<0.001); `precontemplation` stage of change (OR: 7.798; 95% CI: 2.442-24.898) (P<0.001); previous coronary bypass graft surgery (OR: 4.062; 95% CI: 1.356-12.169) (P=0.012); and previous anxiolytic use (OR: 2.365; 95% CI: 1.095-5.107) (P=0.028). Negative predictors were diagnosis of MI (OR: 0.575; 95% CI: 0.361-0.916) (P=0.019); duration of hospitalization (OR: 0.935; 95% CI: 0.898-0.973) (P=0.001); smoking onset age (OR: 0.952; 95% CI: 0.910-0.994) (P=0.028); number of attempts to quit smoking (OR: 0.808; 95% CI: 0.678-0.964) (P=0.018); and `action` stage of change (OR: 0.065; 95% CI: 0.008-0.532) (P= 0.010). Conclusion Depression, no motivation, shorter hospitalization, and severity of illness contributed to postdischarge resumption of smoking by patients with acute coronary syndrome, who underwent hospital-initiated smoking cessation.

The effectiveness of personalized smoking cessation strategies for callers to a Quitline service

Aim To assess the effectiveness of a program of computer-generated tailored advice for callers to a telephone helpline, and to assess whether it enhanced a series of callback telephone counselling sessions in aiding smoking cessation. Design Randomized controlled trial comparing: (1) untailored self-help materials; (2) computer-generated tailored advice only, and (3) computer-generated tailored advice plus callback telephone counselling. Assessment surveys were conducted at baseline, 3, 6 and 12 months. Setting Victoria, Australia. Participants A total of 1578 smokers who called the Quitline service and agreed to participate. Measurements Smoking status at follow-up; duration of cessation, if quit; use of nicotine replacement therapy; and extent of participation in the callback service. Findings At the 3-month follow-up, significantly more (chi(2)(2) = 16.9; P < 0.001) participants in the computer-generated tailored advice plus telephone counselling condition were not smoking (21%) than in either the computer-generated advice only (12%) or the control condition (12%). Proportions reporting not smoking at the 12-month follow-up were 26%, 23% and 22%, respectively (NS) for point prevalence, and for 9 months sustained abstinence; 8.2, 6.0, and 5.0 (NS). In the telephone counselling group, those receiving callbacks were more likely than those who did not to have sustained abstinence at 12 months (10.2 compared with 4.0, P < 0.05). Logistic regression on 3-month data showed significant independent effects on cessation of telephone counselling and use of NRT, but not of computer-generated tailored advice. Conclusion Computer-generated tailored advice did not enhance telephone counselling, nor have any independent effect on cessation. This may be due to poor timing of the computer-generated tailored advice and poor integration of the two modes of advice.

Smoking trends in Switzerland, 1992-2007: a time for optimism?

Objective To assess trends in smoking status according to gender, age and educational level in the adult Swiss population. Methods Four national health interview surveys conducted between 1992 and 2007 in representative samples of the Swiss population. Results The prevalence of current smokers increased between 1992 and 1997, decreasing thereafter. In 2007, the prevalence of current smokers (32.0% of men and 23.8% of women) was lower than in 1992 (38.4% and 26.7%, respectively). Whereas the prevalence of current + former smoking decreased from 64.5% in 1992 to 59.3% in 2007 among men, it was similar among women during the same period (44.0% in 1992 and 43.9% in 2007). The prevalence of current + former smokers decreased from 47.2% in 1992 to 46.3% in 2007 in the lower education group (no education + primary), from 54.8% to 52.9% in subjects with secondary level education, and from 55.4% to 48.7% in subjects with university level education. The prevalence of current smokers decreased in all age groups. Finally, the amount of cigarette equivalents smoked per day decreased, but the amount of non-cigarette tobacco (alone or in combination with cigarettes) increased for both sexes. Conclusion The prevalence of smoking has been decreasing in the Swiss population, for both sexes and for most age groups and educational levels between 1992 and 2007. The health effects of the change in type of tobacco products consumed await further investigation.

Change in physical activity after smoking cessation: the Coronary Artery Risk Development in Young Adults (CARDIA) study.

AIMS: To estimate physical activity trajectories for people who quit smoking, and compare them to what would have been expected had smoking continued. DESIGN, SETTING AND PARTICIPANTS: A total of 5115 participants in the Coronary Artery Risk Development in Young Adults Study (CARDIA) study, a population-based study of African American and European American people recruited at age 18-30 years in 1985/6 and followed over 25 years. MEASUREMENTS: Physical activity was self-reported during clinical examinations at baseline (1985/6) and at years 2, 5, 7, 10, 15, 20 and 25 (2010/11); smoking status was reported each year (at examinations or by telephone, and imputed where missing). We used mixed linear models to estimate trajectories of physical activity under varying smoking conditions, with adjustment for participant characteristics and secular trends. FINDINGS: We found significant interactions by race/sex (P = 0.02 for the interaction with cumulative years of smoking), hence we investigated the subgroups separately. Increasing years of smoking were associated with a decline in physical activity in black and white women and black men [e.g. coefficient for 10 years of smoking: -0.14; 95% confidence interval (CI) = -0.20 to -0.07, P < 0.001 for white women]. An increase in physical activity was associated with years since smoking cessation in white men (coefficient 0.06; 95% CI = 0 to 0.13, P = 0.05). The physical activity trajectory for people who quit diverged progressively towards higher physical activity from the expected trajectory had smoking continued. For example, physical activity was 34% higher (95% CI = 18 to 52%; P < 0.001) for white women 10 years after stopping compared with continuing smoking for those 10 years (P = 0.21 for race/sex differences). CONCLUSIONS: Smokers who quit have progressively higher levels of physical activity in the years after quitting compared with continuing smokers.

Predictors of Weight Change in Sedentary Smokers Receiving a Standard Smoking Cessation Intervention.

INTRODUCTION: Quitting smoking is associated with weight gain, which may threaten motivation to engage or sustain a quit attempt. The pattern of weight gained by smokers treated according to smoking cessation guidelines has been poorly described. We aimed to determine the weight gained after smoking cessation and its predictors, by smokers receiving individual counseling and nicotine replacement therapies for smoking cessation. METHODS: We performed an ancillary analysis of a randomized controlled trial assessing moderate physical activity as an aid for smoking cessation in addition to standard treatment in sedentary adult smokers. We used mixed longitudinal models to describe the evolution of weight over time, thus allowing us to take every participant into account. We also fitted a model to assess the effect of smoking status and reported use of nicotine replacement therapy at each time point. We adjusted for intervention group, sex, age, nicotine dependence, and education. RESULTS: In the whole cohort, weight increased in the first 3 months, and stabilized afterwards. Mean 1-year weight gain was 3.3kg for women and 3.9kg for men (p = .002). Higher nicotine dependence and male sex were associated with more weight gained during abstinence. Age over median was associated with continuing weight gain during relapse. There was a nonsignificant trend toward slower weight gain with use of nicotine replacement therapies. CONCLUSION: Sedentary smokers receiving a standard smoking cessation intervention experience a moderate weight gain, limited to the first 3 months. Older age, male sex, and higher nicotine dependence are predictors of weight gain.