Carole Clair

Association of Smoking Cessation and Weight Change With Cardiovascular Disease Among Adults With and Without Diabetes

IMPORTANCE Smoking cessation reduces the risks of cardiovascular disease (CVD), but weight gain that follows quitting smoking may weaken the CVD benefit of quitting. OBJECTIVE To test the hypothesis that weight gain following smoking cessation does not attenuate the benefits of smoking cessation among adults with and without diabetes. DESIGN, SETTING, AND PARTICIPANTS Prospective community-based cohort study using data from the Framingham Offspring Study collected from 1984 through 2011. At each 4-year examination, self-reported smoking status was assessed and categorized as smoker, recent quitter (≤ 4 years), long-term quitter (>4 years), and nonsmoker. Pooled Cox proportional hazards models were used to estimate the association between quitting smoking and 6-year CVD events and to test whether 4-year change in weight following smoking cessation modified the association between smoking cessation and CVD events. MAIN OUTCOME MEASURE Incidence over 6 years of total CVD events, comprising coronary heart disease, cerebrovascular events, peripheral artery disease, and congestive heart failure. RESULTS After a mean follow-up of 25 (SD, 9.6) years, 631 CVD events occurred among 3251 participants. Median 4-year weight gain was greater for recent quitters without diabetes (2.7 kg [interquartile range {IQR}, -0.5 to 6.4]) and with diabetes (3.6 kg [IQR, -1.4 to 8.2]) than for long-term quitters (0.9 kg [IQR, -1.4 to 3.2] and 0.0 kg [IQR, -3.2 to 3.2], respectively, P < .001). Among participants without diabetes, age- and sex-adjusted incidence rate of CVD was 5.9 per 100 person-examinations (95% CI, 4.9-7.1) in smokers, 3.2 per 100 person-examinations (95% CI, 2.1-4.5) in recent quitters, 3.1 per 100 person-examinations (95% CI, 2.6-3.7) in long-term quitters, and 2.4 per 100 person-examinations (95% CI, 2.0-3.0) in nonsmokers. After adjustment for CVD risk factors, compared with smokers, recent quitters had a hazard ratio (HR) for CVD of 0.47 (95% CI, 0.23-0.94) and long-term quitters had an HR of 0.46 (95% CI, 0.34-0.63); these associations had only a minimal change after further adjustment for weight change. Among participants with diabetes, there were similar point estimates that did not reach statistical significance. CONCLUSIONS AND RELEVANCE In this community-based cohort, smoking cessation was associated with a lower risk of CVD events among participants without diabetes, and weight gain that occurred following smoking cessation did not modify this association. This supports a net cardiovascular benefit of smoking cessation, despite subsequent weight gain.

Risk of falls and major bleeds in patients on oral anticoagulation therapy.

BACKGROUND The risk of falls is the most commonly cited reason for not providing oral anticoagulation, although the risk of bleeding associated with falls on oral anticoagulants is still debated. We aimed to evaluate whether patients on oral anticoagulation with high falls risk have an increased risk of major bleeding. METHODS We prospectively studied consecutive adult medical patients who were discharged on oral anticoagulants. The outcome was the time to a first major bleed within a 12-month follow-up period adjusted for age, sex, alcohol abuse, number of drugs, concomitant treatment with antiplatelet agents, and history of stroke or transient ischemic attack. RESULTS Among the 515 enrolled patients, 35 patients had a first major bleed during follow-up (incidence rate: 7.5 per 100 patient-years). Overall, 308 patients (59.8%) were at high risk of falls, and these patients had a nonsignificantly higher crude incidence rate of major bleeding than patients at low risk of falls (8.0 vs 6.8 per 100 patient-years, P=.64). In multivariate analysis, a high falls risk was not statistically significantly associated with the risk of a major bleed (hazard ratio 1.09; 95% confidence interval, 0.54-2.21). Overall, only 3 major bleeds occurred directly after a fall (incidence rate: 0.6 per 100 patient-years). CONCLUSIONS In this prospective cohort, patients on oral anticoagulants at high risk of falls did not have a significantly increased risk of major bleeds. These findings suggest that being at risk of falls is not a valid reason to avoid oral anticoagulants in medical patients.

Dose-dependent positive association between cigarette smoking, abdominal obesity and body fat: cross-sectional data from a population-based survey.

BackgroundAlthough smokers tend to have a lower body-mass index than non-smokers, smoking may favour abdominal body fat accumulation. To our knowledge, no population-based studies have assessed the relationship between smoking and body fat composition. We assessed the association between cigarette smoking and waist circumference, body fat, and body-mass index.MethodsHeight, weight, and waist circumference were measured among 6,123 Caucasians (ages 35-75) from a cross-sectional population-based study in Switzerland. Abdominal obesity was defined as waist circumference ≥102 cm for men and ≥88 cm for women. Body fat (percent total body weight) was measured by electrical bioimpedance. Age- and sex-specific body fat cut-offs were used to define excess body fat. Cigarettes smoked per day were assessed by self-administered questionnaire. Age-adjusted means and odds ratios were calculated using linear and logistic regression.ResultsCurrent smokers (29% of men and 24% of women) had lower mean waist circumference, body fat percentage, and body-mass index compared with non-smokers. Age-adjusted mean waist circumference and body fat increased with cigarettes smoked per day among smokers. The association between cigarettes smoked per day and body-mass index was non-significant. Compared with light smokers, the adjusted odds ratio (OR) for abdominal obesity in men was 1.28 (0.78-2.10) for moderate smokers and 1.94 (1.15-3.27) for heavy smokers (P = 0.03 for trend), and 1.07 (0.72-1.58) and 2.15 (1.26-3.64) in female moderate and heavy smokers, respectively (P < 0.01 for trend). Compared with light smokers, the OR for excess body fat in men was 1.05 (95% CI: 0.58-1.92) for moderate smokers and 1.15 (0.60-2.20) for heavy smokers (P = 0.75 for trend) and 1.34 (0.89-2.00) and 2.11 (1.25-3.57), respectively in women (P = 0.07 for trend).ConclusionAmong smokers, cigarettes smoked per day were positively associated with central fat accumulation, particularly in women.

Managing tobacco use: the neglected cardiovascular disease risk factor

Cigarette smoking is a major risk factor for cardiovascular disease (CVD) and the leading avoidable cause of death worldwide. Exposure to secondhand smoke (SHS) increases the risk of CVD among non-smokers. Smoking cessation benefits all smokers, regardless of age or amount smoked. The excess risk of CVD is rapidly reversible, and stopping smoking after a myocardial infarction reduces an individuals risk of CVD mortality by 36% over 2 years. Smoking cessation is a key component of primary and secondary CVD prevention strategies, but tobacco use often receives less attention from cardiologists than other risk factors, despite the availability of proven treatments that improve smoking cessation rates. Both psychosocial counselling and pharmacotherapy are effective methods to help smokers quit, but they are most effective when used together. The first-line medications licensed to aid smoking cessation, nicotine replacement therapy, bupropion and varenicline, are effective in and appropriate for patients with CVD. An evidence-based approach for physicians is to routinely ask all patients about smoking status and SHS exposure, advise all smokers to quit and all patients to adopt smoke-free policies for their home and car, and offer all smokers in the office or hospital brief counselling, smoking cessation pharmacotherapy, and referral to local programmes where psychosocial support can be sustained in person or by telephone. Like other chronic diseases, tobacco use requires a long-term management strategy. It deserves to be managed as intensively as other CVD risk factors.

Relationships of cotinine and self-reported cigarette smoking with hemoglobin A1c in the U.S.: results from the National Health and Nutrition Examination Survey, 1999-2008.

OBJECTIVE Whether nicotine leads to a persistent increase in blood glucose levels is not clear. Our objective was to assess the relationship between cotinine, a nicotine metabolite, and glycated hemoglobin (HbA1c), an index of recent glycemia. RESEARCH DESIGN AND METHODS We used cross-sectional data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2008. We limited our analysis to 17,287 adults without diabetes. We created three cotinine categories: <0.05 ng/mL, 0.05–2.99 ng/mL, and ≥3 ng/mL. RESULTS Using self-report, 25% of the sample were current smokers, 24% were former smokers, and 51% were nonsmokers. Smokers had a higher mean HbA1c (5.36% ± 0.01 SE) compared with never smokers (5.31% ± 0.01) and former smokers (5.31% ± 0.01). In a similar manner, mean HbA1c was higher among participants with cotinine ≥3 ng/mL (5.35% ± 0.01) and participants with cotinine 0.05–2.99 ng/mL (5.34% ± 0.01) compared with participants with cotinine <0.05 ng/mL (5.29% ± 0.01). In multivariable-adjusted analysis, we found that both a cotinine ≥3 ng/mL and self-reported smoking were associated with higher HbA1c compared with a cotinine <0.05 ng/mL or not smoking. People with a cotinine level ≥3 ng/mL had a relative 5% increase in HbA1c compared with people with a cotinine level <0.05 ng/mL, and smokers had a relative 7% increase in HbA1c compared with never smokers. CONCLUSIONS Our study suggests that cotinine is associated with increased HbA1c in a representative sample of the U.S. population without diabetes.

Smoking behavior among US adults with diabetes or impaired fasting glucose.

BACKGROUND Cigarette smoking is a well-known cardiovascular risk factor and its impact on cardiovascular disease is even greater among people with diabetes. The aim of this study is to compare the prevalence and determinants of smoking among US adults with diabetes or impaired fasting glucose, and those without diabetes or impaired fasting glucose. METHODS We analyzed data from the National Health and Nutrition Examination Surveys (1999-2008). Age-adjusted prevalence of smoking was calculated, and we used logistic regression models to identify the correlates of smoking among people with diabetes, impaired fasting glucose, and normal glucose metabolism. RESULTS Among 24,649 participants ≥20 years old, age-adjusted smoking prevalence was 25.7% in 3111 individuals with diabetes, 24.2% in 3557 individuals with impaired fasting glucose, and 24.1% in 17,981 individuals without diabetes. Smoking prevalence did not differ across groups or change over time (1999-2008) in any group. Younger age, less education, more alcohol consumption, less physical activity, and major depression symptoms were associated with smoking in people with diabetes, impaired fasting glucose, and normal glucose metabolism. CONCLUSIONS In the US, smoking prevalence among people with diabetes and impaired fasting glucose has not changed and is comparable with the nondiabetic population. Tobacco control efforts should be intensified among this population at high risk for complications and mortality.

Prevalence and factors associated with use of smokeless tobacco in young Swiss men

BACKGROUND Smokeless tobacco is of increasing interest to public health researchers and policy makers. This study aims to measure prevalence of smokeless tobacco use (nasal dry snuff, snus and chewing tobacco) among young Swiss men, and to describe its correlates. METHODS We invited 13 245 young men to participate in this survey on socio-economic and substance use data. Response rate was 45.2%. We included 5720 participants. Descriptive statistics and multivariable-adjusted logistic regression were performed. RESULTS Mean age of participants was 19.5 years. Self-reported use once a month or more often was 8% for nasal dry snuff, 3% for snus and negligible for chewing tobacco. In multivariable-adjusted logistic regression, the odds for nasal dry snuff use increased in non daily smokers [odds ratio (OR) 2.41, 95% confidence interval (CI) 1.90-3.05], compared with non smokers, participants reporting risky weekly drinking volume (OR 3.93, 95% CI 1.86-8.32), compared with abstinents, and binge drinking once a month or more often (OR 7.41, 95% CI 4.11-13.38), compared with never binge drinking. Nasal dry snuff use was positively associated with higher BMI, average or above family income and German language, compared with French, and negatively associated with academic higher education, compared with non higher education, and occasional cannabis use, compared with no cannabis use. Correlates of snus were similar to those of nasal dry snuff. CONCLUSION One in 12 young Swiss men use nasal dry snuff and 3% use snus. Consumption of smokeless tobacco is associated with a cluster of other risky behaviours, especially binge drinking.

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.

Association of smoking and nicotine dependence with pre-diabetes in young and healthy adults

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.

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.