Smoking cessation after diagnosis of COPD is associated with lower all-cause and cause-specific mortality: a nationwide population-based cohort study of South Korean men.

BACKGROUND: The most effective way to halt the advancement of COPD is smoking cessation. However, limited data are available on the question of whether quitting smoking within two years after COPD diagnosis reduces the risk of mortality. The goal of our research was to analyze the relationship between quitting smoking after COPD diagnosis and the risks of all-cause and cause-specific mortality, using the Korean National Health Insurance Service (NHIS) database. METHODS: This study included 1,740 male COPD patients aged 40 years or more who had been newly diagnosed within the 2003-2014 time period and had smoked prior to their COPD diagnosis. The patients were categorized into two groups according to their smoking status after COPD diagnosis: (i) persistent smokers (ii) quitters (smoking cessation within two years of COPD diagnosis). Multivariate Cox proportional hazard regression was performed to determine the adjusted hazard ratio (HR) and 95% confidence interval (CI) for both all-cause and cause-specific mortality. RESULTS: Among 1,740 patients (mean age, 64.6 years; mean follow-up duration, 7.6 years), 30.5% stopped smoking after COPD diagnosis. Quitters gained a 17% risk reduction in all-cause mortality (aHR, 0.83; 95% CI, 0.69-1.00) and a 44% risk reduction in cardiovascular mortality (aHR, 0.56; 95% CI, 0.33-0.95) compared with persistent smokers. CONCLUSION: Our study found that patients who quit smoking within two years after COPD diagnosis had lower risks of all-cause and cardiovascular mortality relative to persistent smokers. These results can be used to encourage newly diagnosed COPD patients to stop smoking.

Experiences Using Family or Peer Support for Smoking Cessation and Considerations for Support Interventions: A Qualitative Study in Persons With Mental Health Conditions.

Background: The current study aimed to understand how people with mental health conditions who currently smoke or recently quit engaged with family members or peers when quitting and assessed interest in involving family or peers in cessation interventions. Methods: Adults with mental health conditions who smoke or had quit within the past 5 years were recruited from publicly funded mental health programs (N = 24). We conducted virtual qualitative interviews between November 2020 and August 2021 and analyzed the data using the rapid thematic analytic approach. Results: Most participants were men (62%), and 71% were current smokers. We found that: having family/peers who were interested in quitting presented communal quitting opportunities, communication that facilitated quitting tended to be encouraging, and strong relationships with family members increased willingness to involve them in cessation interventions. But family or peer support was less helpful for individuals who were not ready to quit. Conclusion: Training family and peers to engage in supportive behaviors may promote cessation in this population. Cessation interventions may benefit from recruiting support partners who share a strong relationship with the smoker.

Longer-term use of electronic cigarettes when provided as a stop smoking aid: Systematic review with meta-analyses.

Moderate certainty evidence supports use of nicotine electronic cigarettes to quit smoking combustible cigarettes. However, there is less certainty regarding how long people continue to use e-cigarettes after smoking cessation attempts. We set out to synthesise data on the proportion of people still using e-cigarettes or other study products at 6 months or longer in studies of e-cigarettes for smoking cessation. We updated Cochrane searches (November 2021). For the first time, we meta-analysed prevalence of continued e-cigarette use among individuals allocated to e-cigarette conditions, and among those individuals who had successfully quit smoking. We updated meta-analyses comparing proportions continuing product use among individuals allocated to use nicotine e-cigarettes and other treatments. We included 19 studies (n = 7787). The pooled prevalence of continued e-cigarette use at 6 months or longer was 54% (95% CI: 46% to 61%, I2 86%, N = 1482) in participants assigned to e-cigarette conditions. Of participants who had quit combustible cigarettes overall 70% were still using e-cigarettes at six months or longer (95% CI: 53% to 82%, I2 73%, N = 215). Heterogeneity in direction of effect precluded meta-analysis comparing long-term use of nicotine e-cigarettes with NRT. More people were using nicotine e-cigarettes at longest follow-up compared to non-nicotine e-cigarettes, but CIs included no difference (risk ratio 1.15, 95% CI: 0.94 to 1.41, n = 601). The levels of continued e-cigarette use observed may reflect the success of e-cigarettes as a quitting tool. Further research is needed to establish drivers of variation in and implications of continued use of e-cigarettes.

Buddies as In-Group Influencers in Online Support Groups: A Social Network Analysis of Processes and Outcomes.

Buddies, serving as in-group influencers to aid demographically similar cobuddies, are extensively used in face-to-face support groups to enhance positive social influence. The authors examine the efficacy of buddies in online support groups and investigate underlying mediating processes using social network analysis. They observe what happens when members of support groups for quitting smoking, including members who are relatively active and less active in the group, after a few days are called on to be buddies and assigned to specific cobuddies. The findings indicate that, consistent with normative expectations for buddies, members form especially strong ties with their designated cobuddies. The more active buddies are in the group, the stronger the ties they form with their cobuddies and, in turn, their cobuddies form stronger ties with group members overall, which then relates to cobuddy goal attainment. The findings suggest that interactive marketers should consider using buddies in online support groups but observe activity levels before making buddy assignments, because positive outcomes are contingent on buddies being active in the group. Marketers should also ensure that online support group members post to everyone, not just their buddies, because ties formed among group members as a whole are crucial for goal attainment.

Association of smoking cessation after atrial fibrillation diagnosis on the risk of cardiovascular disease: a cohort study of South Korean men.

BACKGROUND: While smoking elevates the risk for cardiovascular disease (CVD) among atrial fibrillation (AF) patients, whether smoking cessation after AF diagnosis actually leads to reduced CVD risk is unclear. We aimed to determine the association of smoking cessation after AF diagnosis with subsequent CVD Risk among South Korean men. METHODS: This retrospective cohort study included 2372 newly diagnosed AF male patients during 2003-2012 from the Korean National Health Insurance Service database. Self-reported smoking status within 2 years before and after diagnosis date were determined, after which the participants were divided into continual smokers, quitters (smokers who quit after AF diagnosis), sustained-ex smokers (those who quit prior to AF diagnosis), and never smokers. Participants were followed up from 2 years after AF diagnosis until 31 December 2015 for CVD. Cox proportional hazards regression was used to determine the adjusted hazard ratios (aHRs) and 95% confidence interval (CIs) for CVD according to the change in smoking habits before and after AF diagnosis. RESULTS: The mean (standard deviation, minimum-maximum) age of the study subjects was 62.5 (8.6, 41-89) years. Among AF patients, quitters had 35% reduced risk (aHR 0.65, 95% CI 0.44-0.97) and never smokers had 32% reduced risk (aHR 0.68, 95% CI 0.52-0.90) for CVD compared to continual smokers (p for trend 0.020). Similarly, compared to continual smokers, quitters had 41% risk-reduction (aHR 0.59, 95% CI 0.35-0.99) and never smokers 34% risk-reduction (aHR 0.66, 95% CI 0.46-0.93) for total stroke (p for trend 0.047). Quitters had 50% reduction (aHR 0.50, 95% CI 0.27-0.94), sustained ex-smokers had 36% reduction (aHR 0.64, 95% CI 0.42-0.99), and never smokers had 39% reduction (aHR 0.61, 95% CI 0.41-0.91) in ischemic stroke risk (p for trend 0.047). The risk-reducing effect of quitting on CVD risk tended to be preserved regardless of aspirin or warfarin use. CONCLUSIONS: Smoking cessation after AF diagnosis was associated with reduced CVD, total stroke, and ischemic stroke risk.

Similar softening across different racial and ethnic groups of smokers in California as smoking prevalence declined.

Smoking prevalence differs among different racial/ethnic groups. Previous research found that as smoking prevalence declined in the U.S., remaining smokers made more quit attempts and smoked fewer cigarettes per day (CPD), indicating so-called softening. We examined California, a state with a highly diverse population, to assess whether there is differential softening among remaining smokers in different racial/ethnic groups. We used the California Tobacco Survey (1990-2008, N: 145,128). We ran logistic and linear regressions for smoking prevalence, CPD, quit attempts and time to first cigarette (30 min) as a function of race/ethnicity (non-Hispanic White, Hispanic, African American, Japanese, Chinese, Filipino, Korean, other Asian/Pacific Islander, American Indian/Alaska Native) controlling for other demographics. Overall prevalence fell from 21.1% in 1990 to 12.3% in 2008 (p < 0.01), showing similar declining trends across all racial/ethnic groups (p = 0.44), albeit from different baseline prevalence levels. In terms of softening indicators the proportion with at least one quit attempt in the past 12 months increased from 46.2% to 59.3%, a factor of 1.25 per decade (95%CI = 1.17, 1.34) in the adjusted model. CPD declined from 16.9 to 10.9, by -2.95 CPD per decade (95%CI = -3.24, -2.67) in the adjusted model. There were no significant changes in the time to first cigarette. Interactions of race/ethnicity and time show similar trends among all subgroups expect Hispanics, whose CPD remained stable rather than declining. Although from different baseline levels, tobacco control policies have benefitted all subgroups of California smokers, exhibiting similar softening as prevalence fell. Interventions are still needed to reduce the baseline differences.

Helping hospitalized smokers in Hong Kong quit smoking by understanding their risk perception, behaviour, and attitudes related to smoking.

AIM: To understand the risk perceptions, behaviour, attitudes, and experiences related to smoking among hospitalized Chinese smokers. BACKGROUND: Understanding hospitalized smokers' perceptions of risks associated with smoking, along with their behaviour, attitudes, and smoking-related experiences, is essential prerequisite to design effective interventions to help them quit smoking. DESIGN: A phenomenological research design was adopted. METHODS: A purposive sampling approach was used. Between May 2016-January 2017, 30 hospitalized smokers were invited for an interview. RESULTS: Four themes were generated: (a) associations between perception of illness and smoking; (b) perceived support from healthcare professionals to quit smoking; (c) impact of hospitalization on behaviour, attitudes, and experiences; and (d) perceived barriers to quitting smoking. CONCLUSION: Development of an innovative intervention that helps to demystify misconceptions about smoking through brief interventions and active referrals is recommended to enhance the effectiveness of healthcare professionals promoting smoking cessation for hospitalized smokers. IMPACT: To date, no study examining smoking behaviour among hospitalized patients in Hong Kong has been conducted. Misconceptions about smoking and health, barriers to quitting that outweighed perceived benefits, lack of support from healthcare professionals, and difficulty overcoming withdrawal symptoms or cigarette cravings precluded hospitalized smokers sustaining smoking abstinence after discharge. Smoking is detrimental to physical health. Smoking cessation has beneficial effects on treatment efficacy and prognosis and helps to reduce the economic burden on society from smoking-attributable diseases.

The effects of smoking cessation on visceral adiposity index levels.

BACKGROUND: : Known to cause important metabolic disturbances, weight gain becomes a major health problem after smoking cessation. Visceral adiposity index (VAI) is becoming increasingly popular in the detection of cardiometabolic risks in several disorders and general population. Here, we aimed to investigate the effects of quitting smoking on VAI levels. MATERIALS AND METHODS: : Of 350 participants included into the cigarette cessation program, 70 (20%) completed the study and were enrolled into the analyses. VAI levels were calculated at the baseline and 3rd month after cigarette cessation. RESULTS: : Thirty-eight (54.3%) out of 70 participants were male. While the mean age was found as 42 ± 1.0 years, mean starting age of smoking was found to be 16.87 ± 0.45 years, and mean smoking time was 23.07 ± 1.18 years. While VAI levels were found higher in men at the baseline, VAI levels were found similar in both genders at the end of the study. Higher VAI levels were found in those smoking >20 cigarettes/day, compared to those smoking ≤20 cigarettes/day. Although weight, waist circumference, body mass index (BMI), and high-density lipoprotein cholesterol levels increased, VAI levels were found to decrease significantly at the 3rd month. In subgroup analyses, VAI levels were seen to decrease significantly only in men (P = 0.005). Furthermore, VAI levels were found to decrease (P < 0.001) in those with BMI ≥25 kg/m2, whereas no significant change was observed in those with BMI <25 kg/m2. CONCLUSIONS: Although body weight increases significantly after quitting smoking, VAI levels, an indicator of cardiovascular risks, decrease significantly, especially in men or obese patients.

Economic Evaluation of the effect of Quitting Smoking on Weight Gains: Evidence from the United Kingdom.

OBJECTIVE: This article estimated the causal effect of quitting smoking on body weight gains in the United Kingdom to evaluate whether savings in health costs deriving from smoking prevention and its related diseases are greater than the costs associated with increased obesity. METHODS: We used a longitudinal data set extracted from two waves (2004-2006) of the British Household Panel Survey, which includes information on smoking and a large number of sociodemographic variables. We modeled the effect of quitting smoking on body weight accounting for heterogeneous responses from individuals belonging to different clinical classes of body mass index (BMI) (i.e., overweight and obese individuals). National Health Service costs associated with smoking were then used to implement a cost-benefit analysis, comparing the advantages of smoking reductions with the costs associated with increased obesity. RESULTS: The BMI was found to increase by 0.26 points for quitters compared with those who continued to smoke. The estimated BMI increase was larger for overweight (0.49 points) and obese (0.76 points) people. This result does not change when different control groups are examined. From an economic perspective, the National Health Service cost reductions attributable to quitting smoking were £156.81 million whereas the lost benefit for unintended increases in body weight was £24.07 million. CONCLUSIONS: This article found that the health benefits associated with quitting smoking are greater than the costs associated with increased overweight and obesity.

Estimating the decline in excess risk of chronic obstructive pulmonary disease following quitting smoking - a systematic review based on the negative exponential model.

We quantified the decline in COPD risk following quitting using the negative exponential model, as previously carried out for other smoking-related diseases. We identified 14 blocks of RRs (from 11 studies) comparing current smokers, former smokers (by time quit) and never smokers, some studies providing sex-specific blocks. Corresponding pseudo-numbers of cases and controls/at risk formed the data for model-fitting. We estimated the half-life (H, time since quit when the excess risk becomes half that for a continuing smoker) for each block, except for one where no decline with quitting was evident, and H was not estimable. For the remaining 13 blocks, goodness-of-fit to the model was generally adequate, the combined estimate of H being 13.32 (95% CI 11.86-14.96) years. There was no heterogeneity in H, overall or by various studied sources. Sensitivity analyses allowing for reverse causation or different assumed times for the final quitting period little affected the results. The model summarizes quitting data well. The estimate of 13.32years is substantially larger than recent estimates of 4.40years for ischaemic heart disease and 4.78years for stroke, and also larger than the 9.93years for lung cancer. Heterogeneity was unimportant for COPD, unlike for the other three diseases.

Evaluating the association between menthol cigarette use and the likelihood of being a former versus current smoker.

Menthol in cigarettes has been examined for its potential to affect smoking dependence, measured primarily as number of cigarettes smoked per day and time to first cigarette after waking; the ability to quit smoking constitutes an additional measure of dependence. Successful quitting among menthol compared to non-menthol cigarette smokers is difficult to determine from the literature, due in part to the various definitions of quitting used by researchers. Nevertheless, intervention and follow-up studies of smoking cessation treatments generally indicate no differences in quitting success among menthol compared to non-menthol smokers, while cross-sectional studies suggest some differences within race/ethnicity groups. The association between menthol cigarette use and likelihood of being a former versus current smoker was examined based on data from the National Health Interview Survey and Tobacco Use Supplement to the Current Population Survey. Analyses stratified by race/ethnicity and limited to smokers who had quit at least one year prior to survey participation provided inconsistent results with regard to menthol cigarette use and quitting, both within surveys (i.e., comparing race/ethnicity groups) and between surveys (i.e., same race/ethnicity group across surveys). Evidence suggesting the existence or direction of an association between menthol in cigarettes and quitting depended on the data source.

Estimating the decline in excess risk of cerebrovascular disease following quitting smoking--a systematic review based on the negative exponential model.

We attempted to quantify the decline in stroke risk following quitting using the negative exponential model, with methodology previously employed for IHD. We identified 22 blocks of RRs (from 13 studies) comparing current smokers, former smokers (by time quit) and never smokers. Corresponding pseudo-numbers of cases and controls/at risk formed the data for model-fitting. We tried to estimate the half-life (H, time since quit when the excess risk becomes half that for a continuing smoker) for each block. The method failed to converge or produced very variable estimates of H in nine blocks with a current smoker RR <1.40. Rejecting these, and combining blocks by amount smoked in one study where problems arose in model-fitting, the final analyses used 11 blocks. Goodness-of-fit was adequate for each block, the combined estimate of H being 4.78(95%CI 2.17-10.50) years. However, considerable heterogeneity existed, unexplained by any factor studied, with the random-effects estimate 3.08(1.32-7.16). Sensitivity analyses allowing for reverse causation or differing assumed times for the final quitting period gave similar results. The estimates of H are similar for stroke and IHD, and the individual estimates similarly heterogeneous. Fitting the model is harder for stroke, due to its weaker association with smoking.

Mood, mood regulation, and frontal systems functioning in current smokers, long-term abstinent ex-smokers, and never-smokers.

Indices of mood, mood regulation, and executive functioning were examined in 61 current smokers who have smoked daily for at least one year, 36 ex-smokers who had not smoked a cigarette for at least one year, and 86 never-smokers. All participants completed the following measures online: Depression Anxiety Stress Scales (DASS-21), the Negative Mood Regulation (NMR) scale, the Frontal Systems Behavior Scale (FrSBe), the Fagerström Test for Cigarette Dependence (FTCD), and the Alcohol Use Disorders Identification Test (AUDIT). Multivariate analysis of variance (MANOVA) followed by Tukey post-hoc tests revealed significant differences (p < .01) such that current smokers indicated worse functioning than both ex-smokers and never-smokers on DASS, NMR, and FrSBe, as well as heavier drinking as measured by AUDIT. These differences remained significant even after controlling for AUDIT scores. Results most plausibly reflect a return to pre-smoking baseline brain function in long-term abstinent ex-smokers.

Electronic cigarette use in relation to changes in smoking status and respiratory symptoms.

INTRODUCTION: How e-cigarette use relates to changes in smoking status and respiratory symptoms in the population remains controversial. The aim was to study the association between e-cigarette use and, changes in smoking status and changes in respiratory symptoms. METHODS: A prospective, population-based study of random samples of the population (age 16-69 years) was performed within The Obstructive Lung Disease in Northern Sweden (OLIN) study and West Sweden Asthma Study (WSAS). A validated postal questionnaire containing identical questions was used in OLIN and WSAS at baseline in 2006-2008 and at follow-up in 2016. In total, 17325 participated on both occasions. Questions about respiratory symptoms and tobacco smoking were included in both surveys, while e-cigarette use was added in 2016. RESULTS: In 2016, 1.6% used e-cigarettes, and it was significantly more common in persistent tobacco smokers (10.6%), than in those who quit smoking (2.1%), started smoking (7.8%), or had relapsed into tobacco smoking at follow-up (6.4%) (p<0.001). Among current smokers at baseline, tobacco smoking cessation was less common in e-cigarette users than e-cigarette non-users (14.2% vs 47.6%, p<0.001) and there was no association with a reduction in the number of tobacco cigarettes smoked per day. Those who were persistent smokers reported increasing respiratory symptoms. In contrast, the symptoms decreased among those who quit tobacco smoking, but there was no significant difference in respiratory symptoms between quitters with and without e-cigarette use. CONCLUSIONS: E-cigarette use was associated with persistent tobacco smoking and reporting respiratory symptoms. We found no association between e-cigarette use and tobacco smoking cessation, reduction of number of tobacco cigarettes smoked per day or reduction of respiratory symptoms.

Quitting smoking as a probable trigger for new-onset hypothyroidism after successful medical treatment of Graves' disease: case report.

Graves' disease (GD) is the most common cause of hyperthyroidism while Hashimoto or autoimmune thyroiditis is the most common cause of hypothyroidism. Spontaneous hypothyroidism may develop after successful medical treatment of GD in up to 20% of cases. This report presents a gentleman who is a known smoker and was diagnosed with GD at the age of 64 years. He was counseled about smoking cessation and started with medical treatment using carbimazole (CBZ). He was adequately controlled using medical treatment, yet he continued to smoke. After 2 years of medical treatment, CBZ was stopped due to developing hypothyroidism on the minimum dose of treatment. Celebrating the discontinuation of treatment, the patient decided to quit smoking. One month later, he was euthyroid; however, 4 months later, he developed overt hypothyroidism. He received levothyroxine replacement therapy and titrated to achieve euthyroidism and remained on levothyroxine for more than 5 years. The possibility that quitting smoking may have triggered the development of hypothyroidism was raised due to the coincidence of developing hypothyroidism only 4 months after quitting smoking. Current smoking is associated with a higher risk of developing both GD and Graves' orbitopathy. Quitting smoking is associated with a higher risk of developing new-onset thyroid autoimmunity. Quitting smoking is also associated with a sevenfold higher risk of autoimmune hypothyroidism especially in the first year of smoking cessation. Involved mechanisms may include a sudden increase in oxidative stress, a sudden increase in iodide delivery to thyroid follicles, or promoting T-helper 1-mediated autoimmune thyroiditis after quitting smoking. The present case suggests that quitting smoking may be a triggering factor for the development of hypothyroidism following successful medical treatment of GD, a phenomenon that may affect one-fifth of GD patients without previously reported triggers.

Quitting smoking may trigger hypothyroidism in previously treated Graves' disease patients Graves' disease is the commonest cause of hyperthyroidism. Medical treatment is the mainstay treatment, and about 5-20% of patients may develop hypothyroidism after successful medical treatment. The triggers to this conversion are not known. The present case, a 64 years old gentleman who is a smoker, after being diagnosed with graves' disease, receives medical treatment for 2 years. On the occasion of stopping medical treatment for graves' disease, he decides to quit smoking. One month later he is euthyroid off medications, but 4 months later, he develops severe hypothyroidism, for which he receives replacement therapy for the following five years. The possibility that quitting smoking may have triggered this conversion was raised. Smoking is associated with a 2-folds higher risk of having graves' disease. Quitting smoking on the other hand increases the risk of acquiring thyroid autoantibodies, and new onset autoimmune hypothyroidism. Quitting smoking is also associated with symptoms of weight gain, constipation, and depression, all of which may also occur in hypothyroidism. That is why, ordering thyroid function tests is recommended in recent quitters if they develop such symptoms. Thus, quitting smoking in the present case may have triggered this severe hypothyroidism. Underlying mechanisms may involve increased oxidative stress or autoimmune reactions favoring the occurrence of autoimmune thyroiditis.

Effect of dulaglutide in promoting abstinence during smoking cessation: 12-month follow-up of a single-centre, randomised, double-blind, placebo-controlled, parallel group trial.

Background: Smoking cessation is challenging, despite making use of established smoking cessation therapies. Preclinical studies and one clinical pilot study suggest the antidiabetic drug glucagon-like peptide-1 (GLP-1) analogue to modulate addictive behaviours and nicotine craving. Previously, we reported the short-term results of a randomised, double-blind, placebo-controlled trial. Herein we report long-term abstinence rates and weight developments after 24 and 52 weeks. Methods: This single-centre, randomised, double-blind, placebo-controlled, parallel group trial was done at the University Hospital Basel in Switzerland. We randomly assigned (1:1) individuals with at least a moderate nicotine dependence willing to quit smoking to either a 12-week treatment with dulaglutide 1.5 mg or placebo subcutaneously once weekly in addition to standard of care smoking cessation therapy (varenicline 2 mg/day and behavioural counselling). After 12 weeks, dulaglutide or placebo injections were discontinued and the participants were followed up at week 24 and 52. The primary outcome of self-reported and biochemically confirmed point prevalence abstinence rate, and secondary outcome of secondary outcome of weight change were assessed at weeks 24 and 52. All participants who received one dose of the study drug were included in the intention to treat set and participants who received at least 10/12 doses of the study drug formed the per protocol set. The trial was registered at ClinicalTrials.gov, NCT03204396. Findings: Of the 255 participants who were randomly assigned between June 22, 2017 and December 3, 2020, 63% (80/127) (dulaglutide group) and 65% (83/128) (placebo group) were abstinent after 12 weeks. These abstinence rates declined to 43% (54/127) and 41% (52/128), respectively, after 24 weeks and to 32% (41/127) and 32% (41/128), respectively, after 52 weeks. Post-cessation weight gain was prevented in the dulaglutide group (-1.0 kg, standard deviation [SD] 2.7) as opposed to the placebo group (+1.9 kg, SD 2.4) after 12 weeks. However, at week 24, increases in weight from baseline were observed in both groups (median, interquartile range [IQR]: dulaglutide: +1.5 kg, [-0.4, 4.1], placebo: +3.0 kg, [0.6, 4.6], baseline-adjusted difference in weight change -1.0 kg (97.5% CI [-2.16, 0.16])), and at week 52 the groups showed similar weight gain (median, IQR: dulaglutide: +2.8 kg [-0.4, 4.7], placebo: +3.1 kg [-0.4, 6.0], baseline-adjusted difference in weight change: -0.35 kg (95% CI [-1.72, 1.01])). In the follow-up period (week 12 to week 52) 51 (51%) and 48 (48%) treatment-unrelated adverse events were recorded in the dulaglutide and the placebo group, respectively. No treatment-related serious adverse events or deaths occurred. Interpretation: Dulaglutide does not improve long-term smoking abstinence, but has potential to counteract weight gain after quitting. However, 3 months of treatment did not have a sustained beneficial effect on weight at 1 year. As post-cessation weight gain is highest in the first year after quitting smoking, future studies should consider a longer treatment duration with a GLP-1 analogue in abstinent individuals. Funding: Swiss National Science Foundation, the Gottfried and Julia Bangerter-Rhyner Foundation, the Goldschmidt-Jacobson Foundation, the Hemmi-Foundation, the University of Basel, the Swiss Academy of Medical Sciences.

Impact on quitting smoking of cognitive impairment in stroke patients.

INTRODUCTION: Smoking is a well-established risk factor for strokes, leading to a high incidence of cognitive deficits. Since the impact of cognitive impairment on the effectiveness of interventions for smoking cessation is not yet known, we considered important to assess it. METHODS: We compared, from April 2012 to November 2015, the success rate of quitting smoking in two groups of acutely hospitalised adult smokers. The first group consisted of stroke patients (SP, n = 54) with lesions confirmed by cerebral imaging. The second used as a control group (NSP, n = 38), included patients hospitalised for any reason other than stroke and characterised by normal global cognition. All participants were assessed twice, in acute phase (T0) and 3 months later (T1), using exhaled carbon monoxide (CO) and several questionnaires. RESULTS: At T1, we observed in SP group an inverse correlation between the Montreal Cognitive Assessment (MoCA) and CO (r = -0.33, p = 0.015). Amongst patients who continued smoking, a higher increase in CO between T0 and T1 was observed in SP group (average 20 ± 15, p < 0.001) than NSP (average 9 ± 13, p = 0.002). CONCLUSIONS: The inverse correlation between CO and cognitive parameters at T1 in SP group suggests an increased susceptibility to tobacco dependency in case of residual cognitive impairment. The global cognitive assessment should thus be taken into consideration when providing assistance with quitting smoking, especially in case of stroke patients.

Risk Factors of Relapse After Smoking Cessation: Results in China Family Panel Studies From 2010 to 2018.

Background: Tobacco use is still highly prevalent globally in spite of the tobacco control efforts made by the governments. In view of the harm of smoking and relapse after smoking cessation, the purpose of this study is to establish a competitive risk model to determine potential risk factors for smoking relapse. Methods: The population-based cohort of ex-smokers over the age of 18 years was obtained from the China Family Panel Studies (CFPS) database from 2010 to 2018. Competing risk models were conducted to identify the risk factors for relapse. Results: A total of 1,019 subjects were included in this study, of which 311 (30.52%) subjects relapsed during the follow-up period. A multivariate analysis indicated that age < 40 years [hazard ratio (HR) 19.142; 95% CI: 10.641-34.434, p < 0.01], cohabitation (HR: 1.422; 95% CI: 1.081-1.87, p = 0.01), and often depression [HR 1.422; 95% CI, (1.081-1.87), p = 0.01] were associated with a great risk of relapse while the age of quitting smoking < 60 years (HR: 0. 436; 95% CI: 0.229-0.831, p < 0.01) and joining the Chinese Communist Party (CCP) (HR 0.611; 95% CI: 0.397-0.939, p = 0.03) were reduced risk factors for relapse. Conclusions: Approximately 3 in 10 ex-smokers were observed to relapse. There are various risk factors for relapse as well. In the face of such a serious situation, it is urgent to take action to control smoking.

Efficacy of smoking cessation intervention delivered through mobile tele-counseling among smokers with tuberculosis in a Revised National Tuberculosis Control Program.

BACKGROUND: India has high burden of tuberculosis and smokers. Prevalence of tuberculosis is three times higher in smokers than non-smokers. Active smoking causes severe disease, delay in seeking treatment, lost to treatment follow up, delayed sputum conversion and drug resistance. WHO advocates mobile phone technology to improve health outcomes (mHealth). We used mobile tele-counseling as a smoking cessation intervention in smokers with tuberculosis (TB) receiving treatment under tuberculosis control program. AIM: To determine smoking quit rate at six months of TB treatment among smokers receiving mobile tele-counseling versus brief advice and to estimate smoking quit rates and relapse rates during the tele-counseling period. METHODS: Open label randomized controlled trial. Newly detected pulmonary tuberculosis or pleural effusion patients received brief advice on smoking cessation as per The UNION's guiding framework. Subjects were then randomly allocated to intervention or control group. Intervention group was contacted telephonically at 2,3,4,5 and 6 months to assess smoking quit rates and provide continued smoking cessation advice. RESULTS: Intervention group had 80 and 82 in the control group, mean (SD) age was 40.6(12.6), 43.5(12.7) p = 0.53. Quit rate at six months was 54 (67.5%) in intervention group versus 34 (42%) in control group; RR 1.60 (95% CI 1.19, 2.16) p = 0.001. Trend in smoking quit rates in intervention group was 81.3%, 61.3%, 55%, 73.8% at 2,3,4 and 5 months respectively. Smoking relapse rate was 43.1%, 53.1%, 20.5%,15.3% at 3,4,5 and 6 months respectively. 27.5%, 43.8% were abstinent for last three, two months. CONCLUSIONS: Mobile tele-counseling is an effective strategy for smoking cessation among TB patients.

Methods and factors influencing successful smoking cessation in Thailand: A case-control study among smokers at the community level.

INTRODUCTION: Despite comprehensive tobacco control policies being in place since 1992, smoking prevalence in Thailand has not declined since 2009, indicating a potential need for individual-level measures. This study examined factors influencing successful smoking cessation attempts in Thailand. METHODS: With a case-control design, smoking cessation experiences of 284 successful (defined as having quit smoking for at least six months) and 837 unsuccessful quitters, who were all lifetime daily smokers, were compared, using sociodemographic data, smoking behaviors, and smoking cessation experiences from their last quitting attempt. Data were collected between August and December 2020. Multivariate-adjusted logistic regressions were employed. RESULTS: Unaided smoking cessation was the most popular method among Thais attempting to quit smoking; more than 99% of both successful and unsuccessful quitters used this method. A significantly higher proportion of successful quitters favored stopping their smoking abruptly than did unsuccessful quitters. Depending on the cessation phases (nicotine withdrawal or relapse prevention), cessation-supporting factors included a doctor's recommendation to stop smoking due to smoker's sickness (OR=2.6; 95% CI: 1.9-3.6), having a grandchild (OR=2.5; 95% CI: 1.1-5.6) or child (OR=2.0; 95% CI: 1.2-3.1), exercising (OR=13.9; 95% CI: 7.2-26.9), avoiding smokers (OR=6.7; 95% CI: 4.1-11.1), self-efficacy (OR=8.5; 95% CI: 3.6-20.0), having a good appetite (OR=1.9; 95% CI: 1.3-2.8), wishing to avoid the unpleasant smell of other people's smoking after cessation (OR=3.7; 95% CI: 2.5-5.5), smoking prohibitions in public places (OR=2.8; 95% CI: 1.2-6.4) and workplaces (OR=4.5; 95% CI: 1.9-10.3), and expensive tobacco (OR=1.9; 95% CI: 1.3-2.9). Barriers to successful cessation included using roll-your-own (OR=0.4; 95% CI: 0.3-0.5), insomnia (OR=0.3; 95% CI: 0.2-0.5), social pressure to smoke (OR=0.4; 95% CI: 0.3-0.6), associating smoking with a habit/specific activity (OR=0.4; 95% CI: 0.3-0.5), and pleasure of smoking (OR=0.5; 95% CI: 0.3-0.7). CONCLUSIONS: This study highlights several factors found to influence successful smoking cessation among Thai smokers which can be used to design a guideline for unaided smoking cessation, and for smoking cessation enhancement programs and policies.