ArticleLiterature Review

Smoking cessation and weight gain

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Abstract

Cigarette smoking is the single most important preventable cause of death and illness. Smoking cessation is associated with substantial health benefits. Weight gain is cited as a primary reason for not trying to quit smoking. There is a great variability in the amount of weight gain but younger ages, lower socio-economic status and heavier smoking are predictors of higher weight gain. Weight change after smoking cessation appears to be influenced by underlying genetic factors. Besides, weight gain after smoking cessation is largely because of increased body fat and some studies suggest that it mostly occurs in the subcutaneous region of the body. The mechanism of weight gain includes increased energy intake, decreased resting metabolic rate, decreased physical activity and increased lipoprotein lipase activity. Although there is convincing evidence for the association between smoking cessation and weight gain, the molecular mechanisms underlying this relationship are not well understood. This review summarizes current information of the effects of nicotine on peptides involved in feeding behaviour. Smoking was shown to impair glucose tolerance and insulin sensitivity and cross-sectional studies have demonstrated that smokers are insulin-resistant and hyperinsulinaemic, as compared with non-smokers. Smoking cessation seems to improve insulin sensitivity in spite of the weight gain. Nicotine replacement - in particular nicotine gum - appears to be effective in delaying post-cessation weight gain. In a group of women who failed to quit smoking because of weight gain, a dietary intervention (intermittent very-low-calorie diet) plus nicotine gum showed to both increase success rate in terms of smoking cessation and prevent weight gain. On the other hand, body weight gain at the end of treatment was significantly lower in the patients receiving bupropion or bupropion plus nicotine patch, compared with placebo. Studies with new drugs available for the treatment of obesity - sibutramine and orlistat - are warranted.

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... However, heavy and/or long-term smokers are more likely to be overweight or obese (Dare, Mackay, & Pell, 2015;Mackay, Gray, & Pell, 2013), associated with tendency to develop central adiposity and insulin resistance (IR) (Houston et al., 2006). So, the paradoxical scenario is that while smoking reduces body weight, obese subjects are more likely to smoke and show a higher smoking intensity (Carreras-Torres et al., 2018;Filozof, Fernandez Pinilla, & Fernandez-Cruz, 2004). Body weight control might be the explanation to this as, especially in adolescent women (Fang, 2019), higher body mass index causally influences several aspects of smoking, including lifetime smoking habits, the likelihood of smoking initiation, and the number of cigarettes smoked per day (Taylor et al., 2019). ...
... Smoking increases plasma endothelin levels, promoting vasoconstriction and subsequent tissue hypoxemia that could account for reduced glucose utilization by peripheral tissues and thus may elevate plasma glucose levels (Borissova, Tankova, Kirilov, Dakovska, & Krivoshiev, 2004). In this way, smokers show high fasting glucose, dyslipidemia, postprandial lipid intolerance, among other features of the IR syndrome (Chiolero, Faeh, Paccaud, & Cornuz, 2008;Filozof et al., 2004). Accordingly, smoking increases the risk of type 2 diabetes and leads to a worst prognosis of comorbidities associated with this illness, while smoke cessation decreases the rate of diabetes to that of nonsmokers (Chase et al., 1991;Eliasson, 2003;Will, Galuska, Ford, Mokdad, & Calle, 2001). ...
... NRT in the form of nicotine gum (Eliasson et al., 1996;Filozof et al., 2004) has become a popular therapy to combat the substantial postcessation weight gain in ex-smokers (Aubin, Farley, Lycett, Lahmek, & Aveyard, 2012;Audrain-Mcgovern & Benowitz, 2011). However, nicotine gum has also been associated with IR and other metabolic disorders (Eliasson et al., 1996). ...
Article
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Obesity has reached pandemic proportions and is associated with severe comorbidities, such as type 2 diabetes mellitus, hepatic and cardiovascular diseases, and certain cancer types. However, the therapeutic options to treat obesity are limited. Extensive epidemiological studies have shown a strong relationship between smoking and body weight, with non-smokers weighing more than smokers at any age. Increased body weight after smoking cessation is a major factor that interferes with their attempts to quit smoking. Numerous controlled studies in both humans and rodents have reported that nicotine, the main bioactive component of tobacco, exerts a marked anorectic action. Furthermore, nicotine is also known to modulate energy expenditure, by regulating the thermogenic activity of brown adipose tissue (BAT) and the browning of white adipose tissue (WAT), as well as glucose homeostasis. Many of these actions occur at central level, by controlling the activity of hypothalamic neuropeptide systems such as proopiomelanocortin (POMC), or energy sensors such as AMP-activated protein kinase (AMPK). However, direct impact of nicotine on metabolic tissues, such as BAT, WAT, liver and pancreas has also been described. Here, we review the actions of nicotine on energy balance. The relevance of this interaction is interesting, because considering the restricted efficiency of obesity treatments, a possible complementary approach may focus on compounds with known pharmacokinetic profile and pharmacological actions, such as nicotine or nicotinic acetylcholine receptors signaling.
... Smokers lose subcutaneous body fat through increased fat tissue breakdown (lipolysis) and a reduction in adipose tissue synthesis (lipogenesis) [12]. The fat distribution however appears to change unfavourably with an increase of the abdominal fat depot. ...
... Apart from carcinogenic tar, cigarettes contain nicotine, which suppresses appetite as confirmed in rat experiments by a decrease in their meal size and lengthening of intervals between meals [16]. This is mediated by nicotine affecting appetite regulating hormones (peptide YY, orexin, neuropeptide Y), activation of proopiomelanocortin (POMC) and changes in expression of various hypothalamic receptors [12]. Nicotine also affects adipose tissue metabolism directly by an increase in lipolysis and affects lipases which regulate deposition of free fatty acids into adipose tissue as well as the secretion of fat hormones such as adiponectin [12]. ...
... This is mediated by nicotine affecting appetite regulating hormones (peptide YY, orexin, neuropeptide Y), activation of proopiomelanocortin (POMC) and changes in expression of various hypothalamic receptors [12]. Nicotine also affects adipose tissue metabolism directly by an increase in lipolysis and affects lipases which regulate deposition of free fatty acids into adipose tissue as well as the secretion of fat hormones such as adiponectin [12]. A resulting surplus of FFA leads to lipotoxicity and contributes to insulin resistance. ...
Article
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Obesity is closely linked with the pathogenesis of type 2 diabetes (T2DM) and cardiovascular disease (CVD), and whilst smoking cessation is associated with weight gain, there are concerns that this weight gain may offset the benefit of CVD risk reduction especially in those with considerable post-cessation weight gain. The aim of this narrative review is to evaluate recent evidence on smoking cessation and cardiometabolic outcomes and discuss limitations of current knowledge and studies. Nicotine is a key player in modulating energy balance by influencing lipid storage in adipose tissue by affecting lipolysis, energy input by modulating appetite and energy output by increasing sympathetic drive and thermogenesis. It also increases insulin resistance and promotes abdominal obesity. The CVD risk and mortality associated with cigarette smoking potentiate the CVD risks in patients with diabetes. Evidence supports the benefit of quitting cigarette smoking regardless of any subsequent weight gain. Data suggests that the cardiometabolic risk is limited to the first few years and that cardiovascular health and mortality benefit of smoking cessation outweighs the harm related to weight gain. This weight gain can be limited by nicotine replacement of which e-cigarettes (vaping) are increasingly popular if it is not an alternative to cigarette smoking. However, long-term health data on e-cigarettes is needed prior to formal recommendation for its use in smoking cessation. The recommendation for cessation of cigarette smoking is justified for those at high risk of weight gain and diabetes. However, for most benefit, consideration should be given for personalized weight management to limit weight gain. Awareness of a ‘lean paradox’ by which lower weight is associated with increased CVD risk may help to improve motivation and insight into the bias of smoking, health and body composition otherwise known to epidemiologists as the ‘obesity paradox’.
... However, some patients may prefer the gum or lozenge because each not only provides nicotine, but also offers a distraction or routine to replace the behavioral patterns associated with smoking. In addition, NRT gum and lozenge both delay the weight gain associated with smoking cessation (Rx for Change 2019 ;Filozof 2004;Doherty 1996). In one study, among 79 participants, successful abstainers receiving placebo gained 3.7 kg at 90 days post-cessation, around 2 kg more than participants receiving 4 mg (1.7 kg, p=0.05) or 2 mg (2.1 kg, p=0.09) gum (Doherty 1996). ...
... In one study, among 79 participants, successful abstainers receiving placebo gained 3.7 kg at 90 days post-cessation, around 2 kg more than participants receiving 4 mg (1.7 kg, p=0.05) or 2 mg (2.1 kg, p=0.09) gum (Doherty 1996). Additional evidence suggests that weight suppression is greater with increased use of the gum, but once the gum is discontinued, the patient tends to gain weight similar to those not using the gum (Filozof 2004). ...
... and bupropion versus NRT as 0.99 (95% CI, 0.86-1.13). Like NRT gum or lozenge, bupropion reduces cessation-associated weight gain by around 1-2 kg (Filozof 2004). ...
Chapter
To effectively care for patients who are at risk of opioid-related mortality and morbidity, clinical pharmacists must consider the following: • People who inject opioids are at extremely high risk of mortality and morbidity, and identification of their use should result in expanded care delivery rather than punitive action. • Supply reduction interventions that decrease the availability of prescription opioids for misuse result in increased use of more dangerous illegal substances; thus, they should be paired with harm reduction interventions to maximize public health benefit. • Opioid intoxication may lead to fatal poisoning by inducing severe respiratory depression and hypoxia. Risk of overdose increases over time and with escalating doses. • Naloxone is a potent opioid antagonist that can rapidly reverse opioid-induced respiratory depression. Many formulations of naloxone are available for layperson administration. None of these formulations has been proven more effective than another. • The evidence base supporting expanded access to naloxone through pharmacies, primary care clinics, hospitals, and community organizations is substantial. Pharmacists can play a key role in overdose prevention across all of these settings. • Syringe services programs are endorsed by the CDC for prevention of injection-related infections and associated morbidity, however they remain illegal in 15 states. Effective pharmacy-based syringe access can fill this gap. • Fentanyl cannot cause an overdose through passive exposure, and it is not resistant to naloxone. However, it is extremely potent and increasingly found in the illegal drug supply. Fentanyl test strips can help patients identify it and modify their drug use behaviors. • Typical naloxone doses can effectively reverse the effects of fentanyl and fentanyl analogs. However, naloxone may need to be administered more quickly in the case of a fentanyl overdose, given the rapid onset of effect.
... Smoking is related to obesity, and various association analyses between smoking and obesity-related traits have been conducted. Typically, smoking is associated with weight loss [13,14,[20][21][22]. Previous studies have reported that nicotine causes weight loss by increasing energy expenditure and insulin resistance, as well as reducing appetite and insulin sensitivity [13,20]. ...
... Typically, smoking is associated with weight loss [13,14,[20][21][22]. Previous studies have reported that nicotine causes weight loss by increasing energy expenditure and insulin resistance, as well as reducing appetite and insulin sensitivity [13,20]. However, smoking increases the waist circumference, WHR, and abdominal and visceral fat [15,23,24]. ...
... However, smoking increases the waist circumference, WHR, and abdominal and visceral fat [15,23,24]. Moreover, former smokers tend to increase in body weight and subcutaneous fat for 1-8 years after smoking cessation; however, most of them do not gain excessive weight, and their average BMIs tend to be similar to those of nonsmokers [14,20,21,25,26]. Thus, smoking is a complex environmental factor affecting obesity and obesity-related traits, and more accurate information can be obtained about its effects by identifying genes and pathways that interact with smoking. ...
Article
Full-text available
Introduction: Although many studies have investigated the association between smoking and obesity, very few have analyzed how obesity traits are affected by interactions between genetic factors and smoking. Here, we aimed to identify the loci that affect obesity traits via smoking status-related interactions in European samples. Methods: We performed stratified analysis based on the smoking status using both the UK Biobank (UKB) data (N = 334,808) and the Genetic Investigation of ANthropometric Traits (GIANT) data (N = 210,323) to identify gene-smoking interaction for obesity traits. We divided the UKB subjects into two groups, current smokers and nonsmokers, based on the smoking status, and performed genome-wide association study (GWAS) for body mass index (BMI), waist circumference adjusted for BMI (WCadjBMI), and waist-hip ratio adjusted for BMI (WHRadjBMI) in each group. And then we carried out the meta-analysis using both GWAS summary statistics of UKB and GIANT for BMI, WCadjBMI, and WHRadjBMI, and computed the stratified P-values (Pstratified) based on the differences between meta-analyzed estimated beta coefficients with standard errors in each group. Results: We identified four genome-wide significant loci in interactions with the smoking status (Pstratified < 5×10-8); rs336396 (INPP4B) and rs12899135 (near CHRNB4) for BMI, and rs998584 (near VEGFA) and rs6916318 (near RSPO3) for WHRadjBMI. Moreover, we annotated the biological functions of the SNPs using expression quantitative trait loci (eQTL) and GWAS databases, along with publications, which revealed possible mechanisms underlying the association between the smoking status-related genetic variants and obesity. Conclusions: Our findings suggest that obesity traits can be modified by the smoking status via interactions with genetic variants through various biological pathways.
... 7 It acts as a selective α4β2 nicotinic acetylcholine receptor partial agonist that ameliorates craving and withdrawal symptoms while reducing the reinforcing effect of nicotine. 7 Weight gain after smoking cessation is widely cited as a major obstacle for smokers motivated to quit 8,9 and the optimal program for smoking cessation to prevent early weight gain is not yet clear. 10 People affected by overweight/obesity gain more weight than their normal weight counterparts during smoking cessation. ...
... 12 The mechanism of weight gain after smoking cessation is not completely elucidated, but increased energy intake and decreased resting metabolic rate, physical activity and fatty acid oxidation have been reported to contribute. 8,[13][14][15][16] Increased caloric intake is mostly reflected in higher intakes of fat and carbohydrates 16,17 and enhanced appetite for energy dense foods. 18 Nicotine may modulate appetite regulation by influencing gastrointestinal hormones such as ghrelin and peptide YY. ...
Article
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Because trying to quit smoking and not gain weight requires changes in two major behaviours simultaneously we explored eating behaviour in smokers with overweight/obesity making a quit attempt using guideline‐based treatment. Participants were randomized to a carbohydrate‐reduced or fat‐reduced diet. The Three Factor Eating Questionnaire and Binge Eating Scale were completed by 48 of 64 participants in the low‐carbohydrate and 47 of 58 in the fat‐reduced group at randomization, after 6 and 14 weeks. At 6 weeks, no between group differences were seen in eating behaviour scores thus, we combined the sample for further analyses. In the combined sample, restraint increased (3.94 [95% CI 3.05, 4.83]), disinhibition (uncontrolled eating) decreased (−0.86 [95% CI‐1.31, −0.41]) and binge eating decreased (−1.95 [95% CI −2.83, −1.06]), while hunger scores did not change (−0.43 [95% CI −0.89, 0.03]) after 14 weeks. In a general linear model, increase in dietary restraint (P = .012) and decrease in binge eating (P = .040) were associated with lower weight gain (model R²adj = .147). In a smoking cessation program, dietary support regardless of diet was associated with increased dietary restraint and reduced binge eating. Because smoking cessation causes weight gain these results indicate that dietary support leads to eating behaviour changes that may prevent weight gain.
... Most smokers who are aware of tobacco's harm want to quit but they often fail. Numerous physiological, behavioral, environmental, psychological, cognitive, and social factors are associated with quitting success or failure [2][3][4][5][6]. ...
... In general, unhealthy behaviors facilitate other unhealthy behaviors. Notably, skipping meals and smoking often share a common motivation, which is weight loss, because smoking is sometimes used to lose weight [6,42]. Studies have shown that nicotine suppresses appetite by increasing adrenaline and reducing insulin [43]. ...
Article
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Previous studies suggest that factors related to smoking cessation may vary with age. This study examined the factors affecting smoking cessation by age among Korean adult male smokers using data from the Korea National Health and Nutrition Examination Survey from 2007 to 2018 (excluding 2013). Logistic regression analyses were used to investigate various factors associated with smoking cessation in three different age groups. Out of a total of 15,492 individuals, 31.5% of the 3523 individuals aged 19–39 years (young adult), 54.7% of the 7390 individuals aged 40–64 years (middle-aged), and 78.6% of the 4589 individuals aged ≥65 years (older adults) succeeded in quitting. In the young adult and middle-aged groups, being married was associated with successful quitting, and lifetime smoking was associated with unsuccessful quitting. Willpower and several comorbidities were related to successful cessation in the middle-aged and older adult groups. Skipping any meal, which suggests unhealthy behavior, was negatively related to quitting in the young adult group. We observed that factors associated with smoking cessationsuccess or failure differed by age, which should be considered when developing smoking cessation policies and programs.
... Furthermore, there was a significant difference between the groups at baseline with regards to smoking status. The metabolic effects of smoking are known to promote weight loss [31,32], and since the majority of patients in the CPAP group (75%) were never Split analyses by CPAP use groups showed non-significant shift in the prevalence of cardiovascular comorbidities between baseline and follow-up evaluation in either group excepting an intermediate size effect (r = 0.37) worsening in the evolution of arrhythmia diagnosis in non-CPAP group (Table 7). Table 7. Baseline and follow-up heart rate and cardiovascular comorbidities. ...
... Furthermore, there was a significant difference between the groups at baseline with regards to smoking status. The metabolic effects of smoking are known to promote weight loss [31,32], and since the majority of patients in the CPAP group (75%) were never smokers, while the majority of patients in the non-CPAP group (61.9%) were active or former smokers, this is further supportive of our results showing that CPAP therapy may play a role in BMI reduction. ...
Article
Full-text available
Background: We sought to investigate whether long-term continuous positive airway pressure (CPAP) treatment in patients with obstructive sleep apnea (OSA) and resistant hypertension (RHTN) could attenuate the cardiovascular disease risk by lowering their body-mass index (BMI). Methods: This was a long-term observational study of RHTN patients diagnosed with OSA. Patients were evaluated with polysomnography initially and after a mean follow-up period of four years. The patients were divided into two groups based on their compliance to CPAP therapy. Results: 33 patients (aged 54.67 ± 7.5, 18 men, 54.5%) were included in the study, of which 12 were compliant to CPAP therapy. A significant reduction in BMI at follow-up was noted in patients compliant to CPAP therapy (1.4 ± 3.5 vs. -1.6 ± 2.5, p = 0.006). We also noted a large effect size reduction in abdominal circumference at follow-up in the CPAP group. At follow-up evaluation, the mean heart rate (b/min) was lower in the CPAP group (58.6 ± 9.5 vs. 67.8 ± 7.8), while arrhythmia prevalence increased between initial (28.6%) and follow-up (42.9%) evaluation with an intermediate effect size in non-compliant patients. Conclusions: In our cohort of OSA patients with RHTN, long-term adherence to CPAP therapy was associated with weight loss and improvement in cardiac rhythm outcomes.
... One of them is weight change. Some studies reported weight gain after quitting smoking [13,14], but another study reported weight loss after quitting smoking [15]. In general, most studies have concluded that the relationship between weight change and TB is that weight loss is a risk factor for TB and that overweight has a protective effect against TB [16,17]. ...
... To quit smoking, in addition to simply quitting, lifestyle corrections are usually accompanied, such as abstinence or regular exercise [33]. In addition, it is known that smoking cessation sometimes leads to weight gain [13,23,34]. Therefore, current smokers are expected to do lifestyle modifications, such as exercise or diet control, along with quitting smoking to avoid weight gain following smoking cessation [35][36][37]. ...
Article
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Background Smoking or weight loss is a risk of tuberculosis (TB) development. However, the impact of weight change after smoking cessation on the occurrence of TB remains elusive. We aimed to determine the relationship between weight change after smoking cessation and the risk of TB development. Methods We conducted a population-based cohort study using the national database in Republic of Korea. Of the 10,490,491 subjects who underwent health check-up in 2009, we enrolled 9,953,124 subjects without a previous TB history and followed them until 2017. We divided all study participants into the following three groups: never, former, and current smokers. The primary endpoint was newly developed TB. Results Among 9,953,124 subjects analyzed, 5,922,845 (59.5%) were never smokers, 1,428,209 (14.4%) were former smokers, and 2,602,080 (26.1%) were current smokers. The risk of TB development was significantly higher in current smokers than in never smokers (adjusted hazard ratio (aHR) 1.158; 95% confidence interval [CI] 1.131–1.186). Among current smokers, individuals who stopped smoking and maintained weight after baseline evaluation had a significantly lower risk of TB development compared with those who continued to smoke (aHR 0.771; 95% CI 0.741–0.892). However, even after smoking cessation, individuals who lost weight were at a significantly higher risk of TB development compared with those who continued to smoke (aHR 1.327; 95% CI 1.119–1.715). Conclusions Our findings suggest that smoking is a risk factor for TB and weight maintenance (neither gaining or losing) after quitting smoking might reduce the risk of TB development.
... and CO [2.59 (1.15-5.79)]. Several studies have indicated that smoking behaviour is closely related to body weight and obesity [54], and shown that body weight of past smokers was heavier than that of never smokers [55]. The mechanisms underlying the impact of smoking on weight include varying energy intake, physical activity, metabolic rate, and inflammatory status linked to smoking status [54]. ...
... Several studies have indicated that smoking behaviour is closely related to body weight and obesity [54], and shown that body weight of past smokers was heavier than that of never smokers [55]. The mechanisms underlying the impact of smoking on weight include varying energy intake, physical activity, metabolic rate, and inflammatory status linked to smoking status [54]. Also, it has been reported that smoking affects fat distribution in the abdominal area by various biological mechanisms such as the dysregulation of the hypothalamic-pituitary-adrenal axis [56]. ...
... We focused on the association comparing "former" versus "current" smoking status, given extensive literature demonstrating that smoking cessation is related to weight gain. We hypothesized that former smokers would have higher body weights relative to current smokers (Filozof, Fernandez Pinilla, and Fernandez-Cruz 2004;Flegal et al. 1995;Williamson et al. 1991). Because smoking cessation is more common among people with more socioeconomic resources (Broms et al. 2004), we anticipate a naïve analysis would include spatial confounding. ...
... In contrast, for the individually varying smoking status variable, spatial modeling approaches generally led to parameter estimates that were closer to the non-spatial estimate under the "ideal" model. In addition, we note that the direction of the associations is consistent with prior literature on the relations between smoking cessation and obesity (Filozof, Fernandez Pinilla, and Fernandez-Cruz 2004;Flegal et al. 1995). This suggests that even in a study that does not have property values available, adjustment for spatial variability has the potential to substantially reduce bias. ...
Preprint
In the presence of unmeasured spatial confounding, spatial models may actually increase (rather than decrease) bias, leading to uncertainty as to how they should be applied in practice. We evaluated spatial modeling approaches through simulation and application to a big data electronic health record study. Whereas the risk of bias was high for purely spatial exposures (e.g., built environment), we found very limited potential for increased bias for individual-level exposures that cluster spatially (e.g., smoking status). We also proposed a novel exposure-penalized spline approach that selects the degree of spatial smoothing to explain spatial variability in the exposure. This approach appeared promising for efficiently reducing spatial confounding bias.
... Some smokers report that they smoke as a method of weight control (Nichter et al., 2004). Indeed, smokers have a notably lower body mass index than nonsmokers and gain weight when they quit (Filozof et al., 2004;Jo et al., 2002;Mineur et al., 2011). These effects on body weight have been attributed to nicotine in tobacco, because nicotine decreases food intake in animal models. ...
... These effects on body weight have been attributed to nicotine in tobacco, because nicotine decreases food intake in animal models. In humans, nicotine has some effects on peripheral energy metabolism (Filozof et al., 2004;Jo et al., 2002) and this was also observed in the model nematode Caenorhabditis elegans (Sobkowiak et al., 2016). ...
Preprint
Full-text available
Nicotine decreases food intake, and smokers often report that they smoke to control their weight. To see whether similar phenomena could be observed in the model organism Caenorhabditis elegans , we challenged drug-naïve nematodes with a chronic low (0.01 mM) and high (1 mM) nicotine concentration for 55 h (from hatching to adulthood). After that, we recorded changes in their behavior in a nicotine gradient, where they could choose a desired nicotine concentration. By using a combination of behavioral and morphometric methods, we found that both nicotine and food modulate worm behavior. In the presence of food the nematodes adapted to the low nicotine concentration, when placed in the gradient, chose a similar nicotine concentration like C. elegans adapted to the high nicotine concentration. However, in the absence of food, the nematodes adapted to the low nicotine concentration, when placed in the gradient of this alkaloid, chose a similar nicotine concentration like naïve worms. The nematodes growing up in the presence of high concentrations of nicotine had a statistically smaller body size, compared to the control condition, and the presence of food did not cause any enhanced slowing movement. These results provide a platform for more detailed molecular and cellular studies of nicotine addiction and food intake in this model organism.
... Although cigarette smoking and tobacco use have been primarily reported to occur because of the psychoactive properties of nicotine, robust evidence suggests that tobacco is also used for its effects on body weight. Smokers exhibit lower body weight gain compared with nonsmokers, and smoking cessation leads to a robust weight gain that contributes to relapse (Audrain-McGovern & Benowitz 2011;Filozof et al. 2004;Komiyama et al. 2013). ...
... L. Bellinger et al. 2010;Grunberg et al. 1986;Rupprecht et al. 2018;Winders & Grunberg 1990). The increase in food intake in nicotine animals during abstinence from nicotine is consistent with previous studies in both animals and humans Faraday et al. 2001;Filozof et al. 2004;Stamford et al. 1986). We found that water intake did not change with chronic nicotine use, which is consistent with previous studies that reported that chronic nicotine did not alter water intake in animals (Clarke & Kumar 1984;Levin et al. 1987). ...
Article
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Rationale Nicotine consumption in both human and animal studies has been strongly associated with changes in feeding-related behaviors and metabolism. The current dogma is that nicotine is an anorexic agent that decreases food intake and increases metabolism, leading to decreased body weight gain. However, there are conflicting reports about the acute effects of nicotine on hunger in humans. No study has reported nicotine-induced decreases in food intake within minutes of consumption, suggesting that our understanding of the pharmacological effects of nicotine on appetite and feeding may be incorrect. Objectives The aim of this study was to elucidate effects of acute nicotine intake on feeding and drinking behavior. Methods Adult male Wistar rats were trained to intravenously self-administer nicotine. Microstructural and macrostructural behavioral analyses were employed to look at changes in food and water intake at different timescales. Results At the macrostructural level (hours to days), nicotine decreased body weight gain, decreased feeding, and was associated with increases in feeding and body weight gain during abstinence. At the microstructural level (seconds to minutes), nicotine increased feeding and drinking behavior during the first 5 min after nicotine self-administration. This effect was also observed in animals that passively received nicotine, but the effect was not observed in animals that self-administered saline or passively received saline. Conclusions These results challenge the notion that the initial pharmacological effect of nicotine is anorexigenic and paradoxically suggest that an acute increase in food intake minutes after exposure to nicotine may contribute to the long-term anorexigenic effects of nicotine.
... In prospective population surveys and trials, weight gain and fear of weight gain is associated with reluctance to quit smoking and remain abstinent, especially among women and initially heavier smokers, [20][21][22] with a meta-analysis study reporting an average of 4.67 kg (95% CI: 3.96 to 5.38) gained after 12 months of abstinence. 23 There is evidence that PA is effective for preventing longterm weight gain after smoking cessation, 24 not only by increased energy expenditure and metabolic rate, but also through self-regulation of energy intake, particularly emotional snacking. ...
Article
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Introduction: Smoking reduction can lead to increased success in quitting. This study aims to determine if a client-focused motivational support package for smoking reduction (and quitting) and increasing (or otherwise using) physical activity (PA) can help smokers who do not wish to quit immediately to reduce the amount they smoke, and ultimately quit. This paper reports the study design and methods. Methods and analysis: A pragmatic, multicentred, parallel, two group, randomised controlled superiority clinical trial, with embedded process evaluation and economics evaluation. Participants who wished to reduce smoking with no immediate plans to quit were randomised 1:1 to receive either (1) tailored individual health trainer face-to-face and/or telephone support to reduce smoking and increase PA as an aid to smoking reduction (intervention) or (2) brief written/electronic advice to reduce or quit smoking (control). Participants in both arms of the trial were also signposted to usual local support for smoking reduction and quitting. The primary outcome measure is 6-month carbon monoxide-confirmed floating prolonged abstinence following participant self-reported quitting on a mailed questionnaire at 3 and 9 months post-baseline. Participants confirmed as abstinent at 9 months will be followed up at 15 months. Ethics and dissemination: Approved by SW Bristol National Health Service Research Committee (17/SW/0223). Dissemination will include publication of findings for the stated outcomes, parallel process evaluation and economic evaluation in peer-reviewed journals. Results will be disseminated to trial participants and healthcare providers. Trial registration number: ISRCTN47776579; Pre-results.
... This indicates that racial disparities in post-cessation weight gain may be pronounced several years after quitting. It is also possible that other factors, which may not be directly related to the immediate resulting biological mechanisms of smoking cessation 26 , are contributors to weight gain among African Americans over time. Exploring psychosocial and environmental factors among African American ex-smokers may be necessary to understand observed racial disparities in long-term weight gain upon smoking cessation. ...
Article
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African Americans have disproportionate rates of post-cessation weight gain compared to non-Hispanic whites, but few studies have examined this weight gain in a multiracial sample of smokers receiving evidence-based treatment in a community setting. We examined race differences in short-term weight gain during an intervention to foster smoking cessation plus weight management. Data were drawn from the Best Quit Study, a randomized controlled trial conducted via telephone quitlines across the U.S. from 2013-2017. The trial tested the effects on cessation and weight gain prevention of adding a weight control intervention either simultaneously with or sequentially after smoking cessation treatment. African Americans (n=667) and whites (n=1721) self-reported smoking status and weight during ten intervention calls. Random effects longitudinal modeling was used to examine predictors of weight change over the intervention period (average 16 weeks). There was a significant race x treatment effect; in the simultaneous group, weight increased for African Americans at a faster rate compared to whites (b=0.302, SE=0.129, p<0.05), independent of smoking status, age, baseline obesity, and education. After stratifying the sample, the effect of treatment group differed by race. Education level attenuated the rate of weight gain for African Americans in the simultaneous group, but not for whites. African Americans receiving smoking and weight content simultaneously gained weight faster than whites in the same group; however, the weight gain was slower for African Americans with higher educational attainment. Future studies are needed to understand social factors associated with treatment receptivity that may influence weight among African American smokers.
... Another negative impact associated with tobacco consumption is observed on individual's alertness, retentiveness, and also the blood pressure (Carlisle et al. 2004), which is consequent to effect of the substance on the body's sympathetic system (Westman 1995). Tobacco consumption can result in reduced insulin sensitivity and/or the development of insulin resistance, in short-term use (Frati et al. 1996, Filozof et al. 2004. This is because tobacco consumption results in high circulating levels of insulin-antagonistic hormones such as growth hormone, cortisol, catecholamines, and high circulating levels of free fatty acids which can alter insulin mediated glucose uptake (Balhara 2012). ...
Article
Full-text available
Context Tobacco consumption may pose a very serious threat to the physiological state of the body; yet, fewer records have been documented in that regard. Objective We investigated the impact of aqueous extract of tobacco leaves on the lipid profile, the tissue, and serum levels of the liver and kidney of male Wister rats. Materials and methods Rats (n = 52; weight =33 − 47g; ∼ 2½ weeks old) were acclimatized for 7 days and administered aqueous extract of tobacco leaves at 100, 200, 400, 0 mg/kg of body weight (to group A, B, C, D) for 30 days. Results Compared with the control group, the kidney tissue and serum (i.e., urea and creatinine) were not influenced, in contrast, indices of the liver such as AST, ALT, and ALP, dose-dependently increased. Changes such as coagulative necrosis resulted in the infiltration of mononuclear inflammatory cells and the vacuolar degeneration of the liver. Beside the reduction in the high-density lipoprotein of the rats, there was an increase in the concentration of triglycerides, very low-density lipoprotein, low-density lipoprotein, and the total cholesterol. Conclusion Thus, extract of tobacco leaves can greatly influence the body lipid profile, beside the serum and tissues of the liver.
... Overall, the findings from this study implicate diet behavior (specifically low calorie and low sugar diet behavior) in body shape and appetite-related motivation for smoking, Indeed, directly addressing weight-related cessation barriers during smoking cessation treatment is recommended (Filozof et al., 2004). For example, certain smokers, especially those engaging in dieting behavior, might benefit from psychoeducation regarding how restrictive eating in general, whether or not used in conjunction with cigarettes as an appetite suppression aid, increases the likelihood of binge eating (Fairburn et al., 2003). ...
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Smokers report weight and appetite control as motivators to smoking continuance. These concerns are particularly salient for smokers who use cigarettes to suppress appetite and manage weight. Dieting may influence weight, shape, and appetite-related smoking motivation; however, this has not yet been examined. This study tested associations between five diet types and smoking motivation to control weight, shape, and appetite among adult daily cigarette smokers (N = 550). A multivariate analysis was used to test the incremental association between diet types and Smoking-Related Weight and Eating Episodes Test (SWEET) subscales, adjusting for age, body mass index, sex, and cigarette dependence. Smokers who diet (n = 83, 15.1%) reported higher scores on all SWEET subscales compared to smokers not on a diet. Low-calorie dieting was associated with greater smoking motivation to cope with body dissatisfaction, and low-sugar dieting was associated with greater motivation for smoking to prevent withdrawal-related appetite increases. Treatment implications for smoking cessation are discussed.
... They also found that smoking cessation was associated with weight gain [5]. Numerous cohort studies have shown that people who stop smoking gain weight [6][7][8][9][10][11][12]. ...
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The literature is uncertain about the extent to which those who attend cardiac rehabilitation (CR) gain weight while trying to quit smoking. This study aimed to determine the extent of CR-based smoking cessation provision and whether CR, as delivered in routine practice, is associated with helping patients quit smoking and avoid weight gain. Data from the UK National Audit of Cardiac Rehabilitation database, between April 2013 and March 2016, were used. Smoking status is categorised as smokers and quitters assessed by patient self-report. Outcomes included body weight, blood pressure, depression, and physical activity. A multiple linear regression model was constructed to understand the effect of continuing smoking or quitting smoking on CR outcomes. CR outcome scores were adjusted by the baseline CR score for each characteristic. An e-survey collected information about the smoking cessation support offered to patients attending CR. A total of 2052 smokers (58.59 ± 10.49 years, 73.6% male) and 1238 quitters (57.63 ± 10.36 years, 75.8% male) were analysed. Overall, 92.6% of CR programmes in the United Kingdom (UK) offer smoking cessation support for CR attenders. Quitting smoking during CR was associated with a mean increase in body weight of 0.4 kg, which is much less than seen in systematic reviews. Quitters who attended CR also had better improvements in physical activity status and psychosocial health measures than smokers. As delivered in routine practice, CR programmes in the UK adhere to the guideline recommendations for smoking cessation interventions, help patients quit smoking, and avoid weight gain on completion of CR
... Several studies have found an association between smoking cessation and weight gain. [40][41][42] Nicotine-induced weight loss is a result of reduced appetite signaling. Conversely, both active and passive smoking increase the risk of type 2 diabetes mellitus and abdominal fat accumulation. ...
Article
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Objective: This randomized controlled trial examined the efficacy and safety of N-acetylcysteine as an adjunctive treatment for smoking cessation. Methods: Heavy smokers were recruited from smoking cessation treatment for this 12- week randomized controlled trial. Eligible tobacco use disorder outpatients (n=34) were randomized to N-acetylcysteine or placebo plus first-line treatment. Abstinence was verified by exhaled carbon monoxide (COexh). The assessment scales included the Fagerström Test for Nicotine Dependence, the Hamilton Depression Rating Scale, the Hamilton Anxiety Rating Scale, the Minnesota Nicotine Withdrawal Scale, and the Medication Adherence Rating Scale. We also assessed anthropometrics, blood pressure, lipid profile, and soluble tumor necrosis factor receptor (sTNF-R) levels 1 and 2. Results: First-line treatment for smoking cessation plus adjunctive N-acetylcysteine or placebo significantly reduced COexh (p < 0.01). In the N-acetylcysteine group, no significant changes were found in nicotine withdrawal symptoms, depressive and anxiety symptoms, anthropometric measures, blood pressure, or glucose compared to placebo. However, there was a significant reduction in sTNF-R2 levels between baseline and week 12 in the N-acetylcysteine group. Conclusions: These findings highlight the need to associate N-acetylcysteine with first-line treatment for smoking cessation, since combined treatment may affect inflammation and metabolism components. Clinical trial registration: NCT02420418
... Since smoking is known to be related to the onset of inflammatory responses and the progression of thrombosis through increased oxidative stress and endothelial dysfunction, smoking cessation prevents the progression of atherothrombosis by rapidly reversing hemostatic and inflammatory markers [2]. However, people who quit smoking were exposed to the risk of weight gain resulting from smoking cessation [3]. Smoking cessation increases food intake and decreases energy expenditure via the effects of nicotine deficiency [4]. ...
Article
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Smoking cessation reduces the cardiovascular risk but increases body weight. We investigated the risk of subsequent myocardial infarction and ischemic stroke according to weight gain after smoking cessation, using a nationwide population based cohort. We enrolled 3,797,572 Korean adults aged over 40 years who participated in national health screenings between 2009 and 2010. Subjects who quit smoking were classified into three subgroups according to the weight change between baseline and 4 years prior. Myocardial infarctions and ischemic strokes were followed until the end of 2015. We compared the hazard ratios among smoking cessation subgroups, non-smokers, and current smokers. The mean changes in weight (1.5 ± 3.9 kg) of the smoking cessation group were higher than those of the other groups (p < 0.0001). A total of 31,277 and 46,811 subjects were newly diagnosed with myocardial infarction and ischemic stroke, respectively. Regardless of weight change, all subgroups of smoking cessation had significantly less risk than current smokers. The subgroup of smoking cessation with weight gain over 4kg showed the lowest risk for myocardial infarctions (hazard ratio 0.646, 95% confidence interval 0.583–0.714, p < 0.0001) and ischemic strokes (hazard ratio 0.648, 95% confidence interval 0.591–0.71, p < 0.0001) after multivariable adjustment. In conclusion, weight gain after smoking cessation did not adversely affect the cardiovascular protective effect.
... 13 Postcessation weight gain usually occurs within the first few months after quitting smoking, and JCN sometimes persists over time. 14 Weight gain negatively affects various metabolic conditions of the body, 15,16 which might increase the risk of PD because changes induced by weight gain are related to the pathogenesis of PD. 4,17 Thus, we hypothesized that weight gain following smoking cessation offsets the benefit of smoking on PD risk. However, it is unknown how postcessation weight gain is expected to modify the risk of PD in ex-smokers. ...
Article
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Background and purpose: To determine whether the postcessation weight gain modifies the protective effect of smoking on the development of Parkinson's disease (PD). Methods: This nationwide cohort study included 3,908,687 Korean males aged ≥40 years who underwent at least 2 health checkups biennially between 2009 and 2015. They were grouped into current smokers; quitters with body mass index (BMI) increase, maintenance, and decrease; and never smokers. The occurrence of incident PD was tracked, and Cox proportional-hazard models were used to adjust for potential confounding factors. We also analyzed the impact of weight change regardless of smoking status in the study population. Results: There were 6,871 incident PD cases observed during the 13,059,208 person-years of follow-up. The overall risk of PD was significantly lower in quitters than in never smokers [hazard ratio (HR)=0.78, 95% confidence interval (CI)=0.70-0.86]. The risk of PD was still lower in quitters with BMI increase (HR=0.80, 95% CI=0.65-0.98) and in those with BMI maintenance (HR=0.77, 95% CI=0.68-0.87). This tendency was also observed in quitters with BMI decrease (HR=0.76, 95% CI=0.55-1.06), although it was not as robust as in the other two groups. With respect to weight change alone, BMI increase (HR=1.10, 95% CI=1.02-1.18) but not BMI decrease (HR=1.06, 95% CI=0.98-1.14) significantly increased the PD risk compared to BMI maintenance. Conclusions: Postcessation weight gain in males did not offset the protective impact of smoking on PD development, although overall weight gain predicted an increased risk of PD.
... Individuals with AN may smoke as a way to control or lose weight, 52 and temporary weight gain does occur with smoking cessation. 53 However, a positive phenotypic correlation need not be accompanied by a r g in the same direction (or genetic contributors to the phenotypic association at all). Still, there is plausible support for the negative r g . ...
... One study found that middle-aged shift workers were in particular less physically active . As these unhealthy lifestyle behaviors are also in shift workers related to obesity and diabetes (Cappuccio et al. 2010;Chiolero et al. 2008;Filozof et al. 2004;Jeon et al. 2007;O'Brien et al. 2020;Patel and Hu 2008;Willi et al. 2007), they may mediate the relationships between shift work, and obesity and diabetes. However, studies investigating the mediating role of lifestyle in the relationship between shift work and obesity and diabetes are currently lacking (O'Brien et al. 2020). ...
Article
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Purpose Shift work has been related to obesity and diabetes, but the potential mediating role of lifestyle is yet unknown. Our aim was to investigate this mediating role of physical activity, diet, smoking, and sleep quality in the relationships between shift work, and obesity and diabetes. Methods In this cross-sectional study, 3188 shift workers and 6395 non-shift workers participated between 2013 and 2018 in periodical occupational health checks. Weight and height were objectively measured to calculate obesity (BMI ≥ 30 kg/m ² ). Diabetes status, physical activity, diet, smoking, and sleep quality were assessed using standardized questionnaires. Structural equation models adjusted for relevant confounders were used to analyze the mediating role of lifestyle in the relationships between shift work, and obesity and diabetes. Results Shift workers were more often obese (OR: 1.37, 95% CI 1.16–1.61) and reported more often to have diabetes (OR:1.35, 95% CI 1.003–1.11) than non-shift workers. Shift workers had lower physical activity levels, ate fruit and vegetables less often, smoked more often, and had poorer sleep quality ( p < 0.05). Mediation analysis revealed that shift workers had a higher odds of obesity (OR: 1.07, 95% CI 1.01–1.15) and diabetes (OR: 1.13, 95% CI 1.02–1.27) mediated by poorer sleep quality. Lower physical activity levels (OR: 1.11, 95% CI 1.05–1.19) and lower intake of fruit and vegetables (OR: 1.04, 95% CI 1.01–1.15) were also mediators in the relationship between shift work and obesity, but not in the relationship between shift work and diabetes ( p ≥ 0.05). Conclusion These results imply that interventions targeting diet, physical activity and in particular sleep problems specifically developed for shift workers could potentially reduce the adverse health effects of shift work.
... It has been proposed that long-term smoking interferes with glucose tolerance, insulin sensitivity, and insulin resistance and leads to hyperinsulinemia. 44 Studies of smoking to reduce weight in young people 45,46 suggest more harmful and few, if any, beneficial effects. Indeed, the adverse effects on metabolic and hormonal changes due to smoking contribute to multiple noncommunicable diseases. ...
Article
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Background: Adolescent overweight and obesity (AOO) is a global public health problem and risk for noncommunicable diseases. Understanding context-specific risks is crucial for interventions. Objective: Determine the prevalence of AOO in the Indonesian National Health Survey (INHS) 2013, assess the 5-year trend from 2013 to 2018, and identify risks. Methods: We selected adolescents aged 10 to 19 years (n = 174 290) from the INHS 2013 and used hierarchical logistic regression to identify gender-specific risks for those aged 15 to 19 years (n = 77 534). Change in AOO was assessed by comparison to INHS 2018 reports. Results: The national AOO prevalence increased over 5 years by 48% in young adolescents (13-15 years) and 85% in older ones (16-18 years). High prevalence areas included the urban location of Jakarta (20.9%) and the remote rural region of Papua (19.4%). Overall, AOO risks were being sedentary, male, lower education, married, younger adolescent, and school enrollment, with urban residence and higher wealth being persistent risks for all analyses. Data for depressive symptoms were available for older adolescents whose additional risks were being sedentary, depressive symptoms, and high-fat diet. Male risks were being sedentary and lower education, and female risks were being married, depressive symptoms, high-fat intake, and lower education. Higher intake of fruits and vegetables and fewer sweets did not protect against AOO if a high-fat diet was consumed. Conclusions: Adolescent overweight and obesity in Indonesia is rapidly increasing, especially in older adolescents and males, and with gender-specific risks. Customized multisectoral interventions to identify strategies for lifestyle change are urgently needed.
... Minor tobacco alkaloids are naturally occurring compounds [5] that are structurally [6] and functionally [7][8][9] analogous to nicotine, the primary psychoactive component in cigarettes, and have been the subject of research on novel therapeutics for smoking cessation [10], cognitive disorders including Alzheimer's disease [11][12][13] and Parkinson's disease [14], traumatic brain injury [15], inflammatory bowel disease [16] and psoriasis (Rock Creek Pharmaceuticals), as well as a novel strategy for pain management [17]. Previous research investigating the role of nicotine on body weight has repeatedly demonstrated that cigarette smoking and/or nicotine administration produces sustained weight loss and reduced food intake [18][19][20][21][22]. The similarities between the alkaloids and nicotine indicate there may be potential for the MTAs to reduce body weight, making them prime candidates for novel obesity pharmacotherapies. ...
Article
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Obesity is a leading cause of preventable death in the United States. Currently approved pharmacotherapies for the treatment of obesity are associated with rebound weight gain, negative side effects, and the potential for abuse. There is a need for new treatments with fewer side effects. Minor tobacco alkaloids (MTAs) are potential candidates for novel obesity pharmacotherapies. These alkaloids are structurally related to nicotine, which can help reduce body weight, but without the same addictive potential. The purpose of the current study was to examine the effects of three MTAs (nornicotine, anatabine, and anabasine) and nicotine on weight gain, body composition, chow intake, and physical activity. We hypothesized that the MTAs and nicotine would reduce weight gain through reductions in chow intake and increases in physical activity. To test this, male Sprague Dawley rats were housed in metabolic phenotyping chambers. Following acclimation to these chambers and to (subcutaneous (sc)) injections of saline, animals received daily injections (sc) of nornicotine, anabasine, anatabine, or nicotine for one week. Compared to saline-injected animals that gained body weight and body fat during the treatment phase, injections of nornicotine and anatabine prevented additional weight gain, alongside reductions in body fat. Rats receiving anabasine and nicotine gained body weight at a slower rate relative to rats receiving saline injections, and body fat remained unchanged. All compounds reduced the intake of chow pellets. Nornicotine and nicotine produced consistent increases in physical activity 6 h post-injection, whereas anabasine’s and anatabine’s effects on physical activity were more transient. These results show that short-term, daily administration of nornicotine, anabasine, and anatabine has positive effects on weight loss, through reductions in body fat and food intake and increases in physical activity. Together, these findings suggest that MTAs are worthy of further investigations as anti-obesity pharmacotherapies.
... Smokers usually gain weight when they withdraw from smoking. This weight gain may be due to nicotine withdrawal, increased food intake, and less energy expenditure (Filozof et al. 2004). Proper diet and adequate physical activity are helpful strategies for smokers planning to quit smoking. ...
Chapter
The prevalence of obesity, cancer, and diabetes are increasing at an alarming rate worldwide. It is important to understand the causes of these diseases to better understand their required prevention and treatment. Obesity is considered a heterogenic disease caused by several factors, especially consistent intake of high-calorie foods with little or no physical activity. Obesity has been associated with cancer and diabetes. Approximately 1 out of 3 cancer deaths are due to high body mass index (BMI), low intake of fruits and vegetables, sedentary lifestyle, lack of physical activity, tobacco addiction, and alcoholism. This chapter explains different biological, environmental, and behavioral factors that physiologically interact to potentiate these diseases in healthy individuals. Mitigating obesity, cancer, and diabetes, which are often caused by several factors, require a comprehensive approach. Functional approach, non-pharmacological approach, and nutritional counseling would play significant roles in the management of these diseases.
... The combination of inexpensive, high caloric, fat-laden foods and decreased physical activity over the last few decades are often listed as significant contributors to the prevalence of obesity (20). In addition, the cessation of smoking may be a contributor to the obesity pandemic, as weight gain is a common consequence of smoking cessation (20,24). As the etiological factors that lead to obesity are multifactorial and often difficult to counteract, efforts on improving treatments and vaccines for individuals with obesity are essential. ...
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To combat the immense toll on global public health induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), new vaccines were developed. While these vaccines have protected the populations who received them from severe SARS-CoV-2 infection, the effectiveness and durability of these vaccines in individuals with obesity are not fully understood. Our uncertainty of the ability of these novel vaccines to induce protective immunity in humans with obesity stems from historical data that revealed obesity-associated immune defects to influenza vaccines. This review analyzes the efficacy of SARS-CoV-2 vaccines in humans with obesity. According to the vaccine safety and efficacy information for the Pfizer, Moderna, and Johnson & Johnson formulations, these vaccines showed a similar efficacy in both individuals with and without obesity. However, clinical trials that assess BMI and central obesity showed that induced antibody titers are lower in individuals with obesity when compared to healthy weight subjects, highlighting a potential early waning of vaccine-induced antibodies linked to obesity rates. Thus, the desired protective effects of SARS-CoV-2 vaccination were potentially diminished in humans with obesity when compared to the healthy weight population, but further studies outlining functional implications of the link between obesity and lower antibody titers need to be conducted to understand the full impact of this immune phenomenon. Further, additional research must be completed to truly understand the immune responses mounted against SARS-CoV-2 in patients with obesity, and whether these responses differ from those elicited by previously studied influenza viruses.
... Our study reported that ex-smokers were inclined to exhibit obesity. Related evidence indicated that weight gain usually occurred after smoking cessation leading to declined metabolic rate, increased caloric intake and changes in food preferences 18 . Furthermore, one related study in the US reported that weight gain among smokers who quit was more than that gained among current smokers, approximately 4.4 kg among males and 5.0 kg among females over a 10-year period 19 . ...
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Obesity is an essential health issue leading to noncommunicable diseases (NCDs) as well as atherosclerotic cardiovascular diseases. We aimed to determine the trends in obesity prevalence among Royal Thai Army (RTA) personnel and their associated factors using the health examination of RTA personnel database. A series of cross-sectional studies were conducted from 2017 to 2021. A self-report guide was created using a standardized case report form to obtain demographic characteristics and determine behavioral risk factors. Obesity was defined as BMI $$\ge$$ ≥ 25 kg/m ² , and a total of 512,476 RTA personnel nationwide were included. Obesity prevalence rose from 42.1% (95% CI 41.7–42.4) in 2017 to 44.2% (95% CI 43.9–44.5) in 2021 ( p for trend < 0.001). A significant surge was observed in obesity prevalence among young RTA personnel aged 18–24 years from 23.7% in 2017 to 28.4% in 2021 ( p for trend < 0.001). Higher age individuals, male participants and RTA personnel residing in Bangkok tended to have a significantly higher risk for obesity. Further, regular exercise was a protective factor for obesity. Our data emphasized that obesity among the RTA personnel has been continuously rising over one half-decade, especially among young adults.
... We also exclude individuals ≥45 years and at the extreme high end of the BMI range (≥42) due to increased risk for pregnancy complications, and thus higher likelihood of dropping out [78,79]. Smokers and those who quit smoking <6 months prior to recruitment are excluded given data that show smoking is associated with increased risk for pregnancy complications [80,81] and smoking cessation affects eating patterns and weight [82][83][84]. Individuals with untreated depression (i.e., not on a stable class/dose of antidepressant for ≥6 months or with Edinburgh Scores >12 based on first trimester clinic screening) are excluded due to documented relationships between depression, appetite changes, and eating behaviors [85,86]. ...
Article
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Background Excess gestational weight gain (EGWG) is associated with multiple pregnancy complications and health risks for birthing people and their infants. Likewise, postpartum weight retention (PPWR), or not losing all pregnancy weight, has long-term health consequences. EGWG among people who enter pregnancy with overweight or obesity have worse obstetric outcomes and increased PPWR compared to women who gain within Institute of Medicine guidelines. Methods This study protocol describes the details of a blinded, randomized clinical trial of GROWell: Goals for Reaching Optimal Wellness, a mHealth tool designed to improve diet quality among people who enter pregnancy with overweight or obese BMIs to help them achieve appropriate GWG and safe postpartum pregnancy weight loss. Individuals with overweight and obesity will be randomly assigned to an attention control or intervention arm. The intervention group will receive personalized, goal-oriented text messages regarding dietary choices, while the attention control group will receive text messages about healthy pregnancy, labor, delivery, and early infancy. Both groups will complete online surveys at baseline, follow up, 3 and 6 months postpartum. Results and discussion Currently, 162 subjects have been enrolled. Outcomes associated with GWG and pregnancy are expected in late 2023, while outcomes on postpartum weight retention GROWell adherence are expected in late 2024. The results of this trial will support the use of an evidence-based mHealth tool to be integrated into clinical practice to reduce EGWG and PPWR among pregnant people with overweight and obese BMIs, a resource that is currently lacking. Trial registration ClinicalTrials.gov identifier: NCT04449432. Registered on June 26, 2020.
... Another interesting point is the one related to maternal smoke. Prenatal smoking exposure has some effects on energy metabolism (33) and causes several adverse health outcomes, including the development of metabolic disorders in adulthood (49). Although evidence from human and animal studies suggested that cigarette smoking during pregnancy influences DNA methylation patterns in mother and offspring (50), the potential pathways mediating nicotine's effects via epigenetic mechanisms are still unclear. ...
Article
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Background Maternal metabolic insults as well as Gestational Diabetes Mellitus (GDM) influence the fetal health and may affect ‘offspring’s susceptibility to chronic diseases via epigenetic modifications. GDM, the most common metabolic disorder in pregnancy, can be considered the result of complex interactions between genetic and environmental factors. A critical point in this view is the identification of genes which are epigenetically modified under the influence of GDM. The melanocortin 4 receptor ( MC4R) gene plays a crucial role in nutritional health by suppressing appetite and participating in energy control regulation. The correlations between pregnant ‘women’s metabolic profiles and placental epigenetic modifications of this gene have been poorly investigated. Objective The aim of this study was to evaluate the effect of GDM and maternal clinical parameters at the third trimester of pregnancy to DNA methylation levels in the placenta at CpG sites of MC4R gene. Design and Methods Socio-demographic and clinical characteristics, Mediterranean diet adherence, smoking habits, and physical activity were assessed at the third trimester of pregnancy of 60 Caucasian pregnant women, of which 33 with GDM. Clinical parameters of the newborns were recorded at birth. MC4R DNA methylation on maternal and fetal sides of the placenta was analyzed using bisulfite pyrosequencing. Results MC4R DNA methylation levels at CpG1 and CpG2 were lower on the fetal side of the placenta in GDM-affected women than in non-GDM-affected recruits ( p = 0.033). Moreover, DNA methylation levels on the maternal side at CpG1 were positively related to glucose concentration at 2-h oral glucose tolerance test (OGTT). On the other hand, CpG2 DNA methylation was positively related to both 1-h and 2-h during OGTT. Maternal DNA methylation level at CpG2 was also associated with low density lipoprotein cholesterol (LDL-C) at the third trimester of pregnancy (rho = 0.340, p < 0.05), while CpG1 methylation was negatively related to maternal weight variations at delivery (rho = −0.316, p < 0.05). Significant associations between MC4R DNA methylation on the maternal side and lipid profile at third trimester of pregnancy in women smokers were found. Conclusion Our results suggest that MC4R methylation profile in the placenta is related to maternal metabolic and nutritional conditions, potentially affecting fetal programming and the future metabolic health of the newborn.
... In a similar line, changes in nutrition 41 , alcohol intake 42 , or exercise 43 have a strong interrelationship with smoking and smoking cessation. Smoking has appetite suppressive effects that often leads to weight loss 44 . Therefore, it is not surprising that we observed a significant increase in weight throughout the study. ...
Article
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Smoking increases systemic inflammation and circulating endothelin-1 (ET-1), both of which contribute to an elevated risk of cardiovascular disease (CVD). The present study sought to test the hypothesis that a 12-week smoking cessation intervention would contribute to a long-term reduction in circulating ET-1, tumor necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6). 30 individuals participated in a 12-week evidence-based smoking cessation program at Augusta University. Serum cotinine, plasma inflammatory cytokines, and plasma ET-1 were determined at baseline, immediately after the 12-week cessation program (end of treatment, EOT), and 12-months (12M) following the cessation program. Serum cotinine was significantly reduced ( p < 0.001) at EOT and 12M following the smoking cessation program. Compared to BL (7.0 ± 1.6 pg/mL), TNF-α was significantly reduced at EOT (6.3 ± 1.5 pg/mL, p = 0.001) and 12M (5.2 ± 2.7 pg/mL, p < 0.001). ET-1 was significantly lower at EOT (1.9 ± 0.6 pg/mL, p = 0.013) and at 12M (2.0 ± 0.8 pg/mL, p = 0.091) following smoking cessation compared with BL (2.3 ± 0.6 pg/mL). BL concentrations of cotinine were significantly associated with basal ET-1 (r = 0.449, p = 0.013) and the change in cotinine at 12M following smoking cessation was significantly associated with the change in plasma ET-1 at 12M (r = 0.457, p = 0.011). Findings from the present pilot investigation demonstrate that a 12-week smoking cessation program reduces circulating concentrations of ET-1 and TNF-α for at least a year. The reduction in serum cotinine was associated with the decrease in circulating ET-1. The attenuation in ET-1 and inflammation may in part, contribute to the lower risk of CVD that is observed with smoking cessation.
... 3 The main limitation of this study is its cross-sectional design, which limits the evaluation of some associations, such as the higher likelihood of former smokers having obesity and diabetes. Although there is evidence regarding the relationship between smoking cessation and weight gain, 49 the results should be interpreted considering the study design, due to the possibility of reverse causality. Additionally, other aspects potentially associated with CVD were not investigated in the present research. ...
... Additionally, the risk of MACE in long-term quitters was close to that in never smokers. It is well established that people gain weight after smoking cessation because nicotine is an appetite suppressant (26). Results from the National Health and Nutrition Examination Survey (NHANES) showed that a 10-year smoking cessation attributed a mean weight gain of 4.9 kg (8). ...
Article
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Objective: The aim of this study was to explore the association of lifelong smoking status with risk of major adverse cardiovascular events (MACE) accounting for weight change in a Chinese cohort. Methods: The cohort of the People's Republic of China-United States of America (PRC-USA) Collaborative Study of Cardiovascular and Cardiopulmonary Epidemiology was established in 1983 to 1984, resurveyed during 1987 to 1988 and 1993 to 1994, and followed up to 2005. A total of 5,849 participants who survived in 1993 to 1994 were classified into never smokers, long-term quitters, short-term quitters, short-term relapsers and new smokers, long-term relapsers and new smokers, and persistent smokers according to the information on lifelong smoking status collected in all three surveys. The associations of lifelong smoking status with MACE in the subsequent 10 years were explored with Cox proportional hazards models. Results: During a median follow-up of 10.2 years, 694 participants had MACE. Compared with persistent smokers, the multivariable-adjusted hazard ratio of developing MACE was 0.83 (95% CI: 0.61-1.12) for short-term quitters, 0.75 (95% CI: 0.54-1.02) for long-term quitters, and 0.68 (95% CI: 0.54-0.85) for never smokers (ptrend = 0.001). In comparison, the hazard ratio was 1.03 (95% CI: 0.77-1.35) for long-term relapsers and new smokers and 0.78 (95% CI: 0.46-1.22) for short-term relapsers and new smokers (ptrend = 0.018). These associations were not significantly altered by further adjusting for weight change in the past 10 years. Conclusions: Lifelong smoking status is significantly associated with risk of MACE. As time duration increased, health benefit to quitters would become close to that of never smokers, and harms to relapsers and new smokers would become close to that of persistent smokers.
... Numerous physiological, behavioral, environmental, psychological, cognitive, and social factors are involved in the success or failure of smoking cessation in the general population [18][19][20][21] . However, there have been no studies to examine CKD-specific factors related to smoking cessation. ...
Article
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Introduction: Adverse effects of smoking on kidney function have been demonstrated in both general populations and in populations with chronic kidney disease (CKD). Therefore, quitting smoking can have a significant impact on the mortality and disease progression of CKD. This study examined and compared factors associated with quitting status of smoking, in patients with and without CKD, among Korean adult male smokers, using the Korea National Health and Nutrition Examination Survey from 2008 to 2019, excluding 2013. Methods: Wald test with multiple logistic regression was performed to investigate factors associated with quitting smoking in both CKD and non-CKD groups, along with the interaction effects between groups. Results: Of the 15747 eligible individuals, 909 had CKD, of whom 703 (weighted percentage: 74.4%) were quitters. In the non-CKD group, 8393 (weighted percentage: 50.4%) succeeded in quitting. Regular exercise was the only factor associated with quitting in both groups. The adjusted odd ratios with confidence intervals were 1.29 (95% CI: 1.17-1.42) and 2.84 (95% CI: 1.52-5.31) in the non-CKD and CKD groups, respectively (interaction p=0.0153). Unlike in the CKD group, marriage and higher systolic blood pressure were also associated with quitting, and lifetime smoking amount and secondhand smoke exposure at home were negatively associated with smoking cessation in the non-CKD group. Conclusions: Exercise was the only factor associated with quitting smoking in the CKD group.
Article
Aims: Tobacco smoking is a major health problem associated with lung and liver damage. Lung and liver damage secondary to tobacco smoking is mediated through nicotine-induced oxidative stress. Therefore, we hypothesized that antioxidant treatment with tiron may improve nicotine-induced lung and liver damage. Materials and methods: Rats were divided into six groups, a control, nicotine (10 mg/kg/day, i.p.; for 8 weeks) and tiron (100 or 200 mg/kg/day, i.p.; for 8 weeks) with or without nicotine administration. Key findings: Tiron improved survival rate and attenuated lung and liver damage as reflected by decreased total and differential cell counts, lactate dehydrogenase (LDH) activity in bronchoalveolar lavage fluid (BALF) and decreased alanine aminotransferase (ALT), aspartate aminotransferase (AST) and alkaline phosphatase (ALP) in serum; also histopathological examination confirmed the protective effect of tiron in lung and liver tissues of nicotine treated rats. Tiron attenuated dyslipidemia, which is associated with nicotine. These ameliorative effects of tiron may be mainly due to its antioxidant effect as proved by a significant decrease in malondialdehyde (MDA) content, reactive oxygen species (ROS) and total nitrite/nitrate (NOx) levels, and increase in reduced glutathione (GSH) level, catalase (CAT) and superoxide dismutase (SOD) activities. This is likely related to suppression of protein levels of NADPH oxidase enzyme (NOX1), inducible nitric oxide synthase (iNOS), nuclear factor kappa B (NF-κB) and tumor necrosis factor alpha (TNF-α); and up-regulation of protein levels of nuclear factor erythroid-2 (Nrf2). Significance: This makes tiron (synthetic analogue of vitamin E) good candidate for future use to minimize nicotine's hazards among smokers.
Chapter
In Deutschland rauchten bei der letzten Mikrozensuserhebung (2017) 26,4 % der Männer und 18,6 % der Frauen, die älter als 15 Jahre sind. Rauchen gilt heute in den Industriestaaten als der bedeutsamste einzelne Risikofaktor für eine Vielzahl von schwerwiegenden Erkrankungen und einen vorzeitigen Tod. Sehr wenige klinische Studien untersuchten bislang das Rauchverhalten bei Patientinnen mit einer Bulimie oder Anorexie. Wie die Untersuchung von Rauchmotiven zeigte, wiesen Frauen mit einer Essstörung im Vergleich zu einer depressiven Kontrollgruppe eine signifikant höhere Motivation auf, zu rauchen. Rauchen wird als Mittel zur Gewichtskontrolle eingesetzt und dient zur Bewältigung von Angst und Stress. Bulimie-Patientinnen haben ein erhöhtes Risiko zu rauchen und entwickeln häufig eine starke Tabakabhängigkeit. Insbesondere bei Adipositas stellt die Tabakentwöhnung einen wesentlichen Faktor zur Reduzierung von Morbidität und Mortalität dar.
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Background Schizophrenia and antipsychotic use are associated with clinically significant weight gain and subsequent increased mortality. Despite weight loss medications (WLMs) licensed by regulatory bodies (FDA, EMA, and MHRA) being available, current psychiatric guidelines recommend off-label alternatives, which differ from non-psychiatric guidelines for obesity. Objective Evaluate the efficacy of licensed WLMs on treating antipsychotic-induced weight gain (AIWG) and obesity in schizophrenia and psychosis (OSP). Method A literature search was conducted using Medline, EMBASE, PsycINFO and Cochrane Library online databases for human studies using licensed WLMs to treat AIWG and OSP. Results Three RCTs (two liraglutide, one naltrexone-bupropion), one unpublished open-label trial (naltrexone-bupropion), and seven observational studies (five liraglutide, one semaglutide, one multiple WLMs) were identified. Results for liraglutide showed statistically significant improvement in weight, BMI, waist circumference, HbA1c, cholesterol, and LDL readings on meta-analysis. Evidence was mixed for naltrexone-bupropion with no detailed studies conducted for setmelanotide, or stimulants. Conclusion Evidence is strongest for liraglutide compared to other licensed WLMs. The findings, particularly the inclusion of human trial data, provide evidence for liraglutide use in treating AIWG and OSP, which would better align psychiatric practice with non-psychiatric practices around obesity. The findings also identify continued literature gaps regarding other licensed WLMs.
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To reveal the impacts of smoking on genetic architecture of human body weight, we conducted a genome-wide association study on 5,336 subjects in four ethnic populations from MESA (The Multi-Ethnic Study of Atherosclerosis) data. A full genetic model was applied to association mapping for analyzing genetic effects of additive, dominance, epistasis, and their ethnicity-specific effects. Both the unconditional model (base) and conditional model including smoking as a cofactor were investigated. There were 10 SNPs involved in 96 significant genetic effects detected by the base model, which accounted for a high heritability (61.78%). Gene ontology analysis revealed that a number of genetic factors are related to the metabolic pathway of benzopyrene, a main compound in cigarettes. Smoking may play important roles in genetic effects of dominance, dominance-related epistasis, and gene-ethnicity interactions on human body weight. Gene effect prediction shows that the genetic effects of smoking cessation on body weight vary from different populations.
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In the presence of unmeasured spatial confounding, spatial models may actually increase (rather than decrease) bias, leading to uncertainty as to how they should be applied in practice. We evaluated spatial modelling approaches through simulation and application to a big data electronic health record study. Whereas the risk of bias was high for purely spatial exposures (e.g. built environment), we found very limited potential for increased bias for individual‐level exposures that cluster spatially (e.g. smoking status). We also proposed a novel exposure‐penalized spline approach that selects the degree of spatial smoothing to explain spatial variability in the exposure. This approach appeared promising for efficiently reducing spatial confounding bias.
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Aim Office workers spend the majority of their working time in sedentary positions which put them at a higher risk of obesity and cardiovascular diseases. The present study was performed to assess the relationship between sex and body mass index (BMI) with the parameters of lipid profile and FBS in a group of office workers. Methods Five hundred and six office workers were studied. A questionnaire on demographic variables, smoking habits, alcohol consumption, consumption of dairy products, vegetables, and oils, and detailed occupational history was completed. The standing height and weight of the participants were measured. Fasting blood samples were taken and parameters of lipid profile and fast blood sugar (FBS) were measured. Data were analyzed using version 21.0 of the SPSS software. Results About 64% of the subjects were overweight/obese. The prevalence of overweight/obesity was not different between males and females. Male participants and overweight/obese participants had significantly higher TG and FBS and lower HDL than the females and those with normal BEI, respectively. No statistically significant differences were observed in the means of lipid profile parameters and FBS between smoker and nonsmoker participants and between those with different consumption of dairy products or vegetables. The most prevalent abnormal findings were observed for LDL (52%), HDL (40%), TG (26%), TC (21%), and FBC (Kooshki et al., 2021), respectively. Conclusions BMI and male sex were directly associated with TG and FBS and inversely associated with HDL. Neither sex nor BMI was associated with LDL.
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One of the foremost emerging and important aspect people were following these days are fitness. The people are suffering from obesity which led to extreme medical disease. The body Fat Percentage (BFP) is the one of the most widely used method used to calculate the fitness level of the human. This study proposes the method to predict the BFA using the regression method. It also prescribes how people can maintain proper diet for being healthy and stay fit. Based on the prediction result, the web application provide people with the prescribed module like gym, proper diet, doctor consultation etc. The people can choose their respective module according to their fitness level. Also, the doctor consultant module is implemented using support vector machine (SVM) which classify the people according to the level of fitness and also the appropriate choice of doctor. The prediction result reveals the proposed model efficiency
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In this research, we evaluated the relationship between obesity rates and altitude using a cross-county study design. We applied a geographically weighted regression (GWR) to examine the spatially varying association between adult obesity rates and altitude after adjusting for four predictor variables including physical activity. A significant negative relationship between altitude and adult obesity rates were found in the GWR model. Our GWR model fitted the data better than OLS regression (R2 = 0.583), as indicated by an improved R2 (average R2 = 0.670; range: 0.26–0.77) and a lower Akaike Information Criteria (AIC) value (14,736.88 vs. 15,386.59 in the OLS model). These approaches, evidencing spatial varying associations, proved very useful to refine interpretations of the statistical output on adult obesity. This study underscored the geographic variation in relationships between adult obesity rates and mean county altitude in the United States. Our study confirmed a varying overall negative relationship between county-level adult obesity rates and mean county altitude after taking other confounding factors into account.
Thesis
Cigarette consumption and excess weight are the two leading causes of premature death and disability in the US. Smoking cessation has well-documented health benefits. However, 80% of quitters experience an unintended consequence of quitting: post-cessation weight gain. Currently, the health message provided to smokers is that it is never too late to quit, without addressing the weight concern that many have. I outline three papers in this dissertation to study the interaction of smoking behaviors and body weight. The first paper examines the age-specific changes in BMI and BMI distribution among US adults, adjusting for smoking and socioeconomic status (SES). I examine population representative annual BMI change across two time periods (1997 to 2007 and 2007 to 2017) by age, gender, SES and smoking status using a synthetic cohort approach. I also assess the changes in BMI distribution among age-specific groups. Information on BMI change and BMI distribution change can help us identify age-groups that are more susceptible to excess weight gain. The second study investigates the tradeoff between the health benefits of quitting smoking and the harm due to post-cessation weight gain. I estimate the break-even weight gain, i.e. the weight individuals would need to gain to offset the benefits of smoking cessation. A potentially attainable break-even weight gain exists for certain combinations of quit-age and BMI. The break-even weight gain decreases with quit-age. The break-even weight gain for white males with an initial BMI of 30 is 29.9 kg if they quit at 50 but decreases to 4.2 kg if they quit 80. I identify subgroups with higher initial BMI and higher cigarette consumption as high-risk to receive negative net health benefits from quitting. Smoking cessation should be coupled with weight management programs to maximize health gains. Lastly, I explore interventions that could reduce post-cessation weight gain and estimate the potential increase of overall welfare in the population. Employing an agent-based model, I simulate three interventions on a nationally representative sample of US smokers: pharmacotherapy, physical activity intervention and alternative tobacco product (electronic cigarette). These interventions affect both smoking cessation rates and post-cessation weight gain. Model results show that electronic cigarette is the dominant intervention that increases life-years saved and reduces obesity prevalence.
Article
With the recent rapid increase in obesity worldwide, metabolic syndrome (MetS) has gained significant importance. MetS is a cluster of obesity-related cardiovascular risk factors including abdominal obesity, atherogenic dyslipidemia, high blood pressure and impaired glucose tolerance. MetS is highly prevalent and strongly associated with an increased risk of developing diabetes and cardiovascular disease, putting a great burden on human society. Therefore, it is very important to reduce MetS risk, which can improve patients' cardiovascular prognosis. The primary and most effective strategy to control each component of MetS is lifestyle change such as losing body weight, keeping regular exercise, adopting a healthy diet, quitting smoking and alcohol drinking in moderation. Many studies have shown that lifestyle modification has improved all components of MetS, and reduces the incidence of diabetes and cardiovascular disease. Here, the Korean Society of CardioMetabolic Syndrome has summarized specific and practical methods of lifestyle modification in the management of MetS in the healthcare field.
Article
Objective: We examined lifestyle factors with midlife weight change according to history of gestational diabetes mellitus (GDM) in a large longitudinal female cohort. Research design and methods: In the Nurses' Health Study II, we categorized changes in lifestyle within 4-year periods and estimated their associations with concurrent changes in body weight (kilograms) among parous women after age 40 years by GDM history status (N = 54,062; 5.3% with a history of GDM) for the following: diet quality (Alternate Healthy Eating Index [AHEI]), leisure-time physical activity (PA), alcohol consumption, and smoking status. Results: Over a median follow-up of 13 years, average 4-year weight gain was 1.10 and 1.33 kg for women with and without prior GDM, respectively. Women with improved diet quality had favorable 4-year weight change, particularly those with a history of GDM (AHEI change [95% CI] from low to high -2.97 kg [-4.34, -1.60] vs. -1.19 kg [-1.41, -0.96] for GDM vs. non-GDM, respectively; P heterogeneity = 0.04). Increasing PA was associated with weight maintenance for GDM women only (PA increase [95% CI] from low to high 0.26 kg [-0.25, 0.77] vs. 0.90 kg [0.80, 1.01] for GDM vs. non-GDM, respectively; P heterogeneity = 0.02). For both GDM and non-GDM women, weight change did not differ significantly with change in alcohol consumption, while women who quit smoking had significant weight gain (4.38 kg for GDM and 3.85 kg for non-GDM). Conclusions: Improvements in diet quality and PA were related to less weight gain in midlife among parous women, and the benefit of such improvements on weight management was particularly pronounced among women with a history of GDM.
Article
Research has uncovered factors that underlie the weight gain associated with cessation of smoking. Here, scientists consider the implications of this finding from the perspectives of gut biology and of smoking. Gut microbes implicated in weight gain after the cessation of smoking.
Article
Background: Most people who stop smoking gain weight. This can discourage some people from making a quit attempt and risks offsetting some, but not all, of the health advantages of quitting. Interventions to prevent weight gain could improve health outcomes, but there is a concern that they may undermine quitting. Objectives: To systematically review the effects of: (1) interventions targeting post-cessation weight gain on weight change and smoking cessation (referred to as 'Part 1') and (2) interventions designed to aid smoking cessation that plausibly affect post-cessation weight gain (referred to as 'Part 2'). Search methods: Part 1 - We searched the Cochrane Tobacco Addiction Group's Specialized Register and CENTRAL; latest search 16 October 2020. Part 2 - We searched included studies in the following 'parent' Cochrane reviews: nicotine replacement therapy (NRT), antidepressants, nicotine receptor partial agonists, e-cigarettes, and exercise interventions for smoking cessation published in Issue 10, 2020 of the Cochrane Library. We updated register searches for the review of nicotine receptor partial agonists. Selection criteria: Part 1 - trials of interventions that targeted post-cessation weight gain and had measured weight at any follow-up point or smoking cessation, or both, six or more months after quit day. Part 2 - trials included in the selected parent Cochrane reviews reporting weight change at any time point. Data collection and analysis: Screening and data extraction followed standard Cochrane methods. Change in weight was expressed as difference in weight change from baseline to follow-up between trial arms and was reported only in people abstinent from smoking. Abstinence from smoking was expressed as a risk ratio (RR). Where appropriate, we performed meta-analysis using the inverse variance method for weight, and Mantel-Haenszel method for smoking. Main results: Part 1: We include 37 completed studies; 21 are new to this update. We judged five studies to be at low risk of bias, 17 to be at unclear risk and the remainder at high risk. An intermittent very low calorie diet (VLCD) comprising full meal replacement provided free of charge and accompanied by intensive dietitian support significantly reduced weight gain at end of treatment compared with education on how to avoid weight gain (mean difference (MD) -3.70 kg, 95% confidence interval (CI) -4.82 to -2.58; 1 study, 121 participants), but there was no evidence of benefit at 12 months (MD -1.30 kg, 95% CI -3.49 to 0.89; 1 study, 62 participants). The VLCD increased the chances of abstinence at 12 months (RR 1.73, 95% CI 1.10 to 2.73; 1 study, 287 participants). However, a second study found that no-one completed the VLCD intervention or achieved abstinence. Interventions aimed at increasing acceptance of weight gain reported mixed effects at end of treatment, 6 months and 12 months with confidence intervals including both increases and decreases in weight gain compared with no advice or health education. Due to high heterogeneity, we did not combine the data. These interventions increased quit rates at 6 months (RR 1.42, 95% CI 1.03 to 1.96; 4 studies, 619 participants; I2 = 21%), but there was no evidence at 12 months (RR 1.25, 95% CI 0.76 to 2.06; 2 studies, 496 participants; I2 = 26%). Some pharmacological interventions tested for limiting post-cessation weight gain (PCWG) reduced weight gain at the end of treatment (dexfenfluramine, phenylpropanolamine, naltrexone). The effects of ephedrine and caffeine combined, lorcaserin, and chromium were too imprecise to give useful estimates of treatment effects. There was very low-certainty evidence that personalized weight management support reduced weight gain at end of treatment (MD -1.11 kg, 95% CI -1.93 to -0.29; 3 studies, 121 participants; I2 = 0%), but no evidence in the longer-term 12 months (MD -0.44 kg, 95% CI -2.34 to 1.46; 4 studies, 530 participants; I2 = 41%). There was low to very low-certainty evidence that detailed weight management education without personalized assessment, planning and feedback did not reduce weight gain and may have reduced smoking cessation rates (12 months: MD -0.21 kg, 95% CI -2.28 to 1.86; 2 studies, 61 participants; I2 = 0%; RR for smoking cessation 0.66, 95% CI 0.48 to 0.90; 2 studies, 522 participants; I2 = 0%). Part 2: We include 83 completed studies, 27 of which are new to this update. There was low certainty that exercise interventions led to minimal or no weight reduction compared with standard care at end of treatment (MD -0.25 kg, 95% CI -0.78 to 0.29; 4 studies, 404 participants; I2 = 0%). However, weight was reduced at 12 months (MD -2.07 kg, 95% CI -3.78 to -0.36; 3 studies, 182 participants; I2 = 0%). Both bupropion and fluoxetine limited weight gain at end of treatment (bupropion MD -1.01 kg, 95% CI -1.35 to -0.67; 10 studies, 1098 participants; I2 = 3%); (fluoxetine MD -1.01 kg, 95% CI -1.49 to -0.53; 2 studies, 144 participants; I2 = 38%; low- and very low-certainty evidence, respectively). There was no evidence of benefit at 12 months for bupropion, but estimates were imprecise (bupropion MD -0.26 kg, 95% CI -1.31 to 0.78; 7 studies, 471 participants; I2 = 0%). No studies of fluoxetine provided data at 12 months. There was moderate-certainty that NRT reduced weight at end of treatment (MD -0.52 kg, 95% CI -0.99 to -0.05; 21 studies, 2784 participants; I2 = 81%) and moderate-certainty that the effect may be similar at 12 months (MD -0.37 kg, 95% CI -0.86 to 0.11; 17 studies, 1463 participants; I2 = 0%), although the estimates are too imprecise to assess long-term benefit. There was mixed evidence of the effect of varenicline on weight, with high-certainty evidence that weight change was very modestly lower at the end of treatment (MD -0.23 kg, 95% CI -0.53 to 0.06; 14 studies, 2566 participants; I2 = 32%); a low-certainty estimate gave an imprecise estimate of higher weight at 12 months (MD 1.05 kg, 95% CI -0.58 to 2.69; 3 studies, 237 participants; I2 = 0%). Authors' conclusions: Overall, there is no intervention for which there is moderate certainty of a clinically useful effect on long-term weight gain. There is also no moderate- or high-certainty evidence that interventions designed to limit weight gain reduce the chances of people achieving abstinence from smoking.
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Introduction: Compared with the number of studies in adults, body weight in relation to tobacco use has been understudied in the adolescent population. This study aimed to examine the association between underweight, overweight and tobacco use in low- and middle-income countries. Methods: Data were derived from the Global School-Based Student Health Survey (GSHS). Data from 71176 adolescents aged 12-15 years residing in 23 countries were analyzed. The Centers for Disease Control and Prevention (CDC) 2000 growth charts were used to identify underweight, normal weight, and overweight/ obesity. Weighted age- and gender-adjusted prevalence of weight categories and tobacco use was calculated. Multivariate logistic regression analysis was performed to estimate the association between weight categories and tobacco use for each country, controlling for covariates. Pooled odds ratios and confidence intervals were computed using random- or fixed-effects meta-analyses. Results: A significant association between weight categories and tobacco use was evident in only a few countries. Adolescents reporting tobacco use in French Polynesia, Suriname, and Indonesia, had 72% (95% CI: 0.15-0.56), 55% (95% CI: 0.24-0.84), and 24% (95% CI: 0.61-0.94) lower odds of being underweight, respectively. Adolescents reporting tobacco use in Uganda, Algeria, and Namibia, had 2.30 (95% CI: 1.04-5.09), 1.71 (95% CI: 1.25-2.34), and 1.45 (95% CI: 1.00-2.12) times greater odds of being overweight/obese, but those in Indonesia and Malaysia had 33% (95% CI: 0.50-0.91) and 16% (95% CI: 0.73-0.98) lower odds of being overweight/obese. Conclusions: The association between tobacco use and BMI categories is likely to be different among adolescents versus adults. Associating tobacco use with being thin may be more myth than fact and should be emphasized in tobacco prevention programs targeting adolescents.
Article
The identification of individuals at high risk of developing hypertension can be of great value to improve the efficiency of primary prevention strategies for hypertension. The objective of this study was to develop a risk prediction model for incident hypertension based on prospective longitudinal data from a general Japanese population. A total of 982 subjects aged 40–59 years without hypertension at baseline were followed up for 10 years (2002–12) for the incidence of hypertension. Hypertension was defined as systolic blood pressure (SBP) ≥ 140 mmHg, diastolic blood pressure (DBP) ≥ 90 mmHg, or the use of antihypertensive agents. The risk prediction model was developed using a Cox proportional hazards model. A simple risk scoring system was also established based on the developed model. During the follow-up period (median 10 years, interquartile range 5–10 years), 302 subjects (120 men and 182 women) developed new-onset hypertension. The risk prediction model for hypertension consisted of age, sex, SBP, DBP, use of glucose-lowering agents, body mass index (BMI), parental history of hypertension, moderate-to-high alcohol intake, and the interaction between age and BMI. The developed model demonstrated good discrimination (Harrell’s C statistic=0.812 [95% confidence interval, 0.791–0.834]; optimism-corrected C statistic based on 200 bootstrap samples=0.804) and calibration (Greenwood-Nam-D’Agostino χ2 statistic=12.2). This risk prediction model is a useful guide for estimating an individual’s absolute risk for hypertension and could facilitate the management of Japanese individuals at high risk of developing hypertension in the future.
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Background Obesity among the elderly imposes a significant health and economic burden. The purpose of this study was to measure the obesity prevalence and income-related inequality among older adults in China and to explore the determinants of the inequity. Methods Data were obtained from 4,541 older adults (60 years and older) participating in the China Family Panel Study, 2018. Obesity was defined as body mass index (BMI) ≥28 kg/m ² . Normalized concentration index and concentration curve were calculated to measure the income-related inequality. Decomposition analysis was used to measure the contribution of each factor to the overall unfairness. Results The prevalence of obesity among the respondents was 7.99%. The 95% confidence interval for the overall prevalence was 7.20–8.78%. The normalized concentration index of obesity in the elderly was 0.075 (95% confidence interval: 0.047–0.103), indicating that obesity was more concentrated among the rich ( p < 0.05). Socioeconomic factors contributed the most to the overall inequality (68.73%). Health behavior factors explained 16.38% of the observed income-related inequality in obesity among the elderly in China. Conclusions In 2018, obesity was more concentrated among the elderly with higher incomes in China. The pro-poor income-related inequality was mainly due to the higher socioeconomic status of higher-income older adults. Health behaviors and psychosocial factors could also exacerbate the inequality. To prevent the heavy burden of obesity on the health and finances of older adults, more attention should be paid to those who are financially better off, especially those who smoke and are physically inactive, while extroverted older adults also need to be focused on. For developing countries, concern needs to be given to the obesity of the wealthy elderly as a result of economic development.
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Introduction DNA methylation in the CpG sites of intron 1 of HIF3A is associated with body mass index (BMI). This cross-sectional study investigated correlations between DNA methylation of HIF3A and BMI or adiposity parameters in the Japanese population. Method DNA methylation of HIF3A was quantified via pyrosequencing. Result DNA methylation of HIF3A differed only in women; DNA methylation level at cg27146050 was associated with visceral adipose tissue thickness and correlated with BMI and percent (%) body fat after excluding smokers. Conclusion Peripheral blood DNA methylation at the CpG site (cg27146050) of HIF3A correlated with VAT thickness in Japanese women.
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Fluoxetine's effect (30 mg, 60 mg, and placebo) on postcessation weight gain was studied among participants from a randomized, double-blind 10-week smoking cessation trial who met strict criteria for abstinence and drug levels. It was hypothesized that (a) fluoxetine would dose-dependently suppress postcessation weight gain and (b) drug discontinuation would produce dose-dependent weight rebound. During the on-drug phase, placebo participants gained weight linearly ( M = 2.61 kg), exceeding both fluoxetine groups (30-mg M = 1.33 kg, 60-mg M = 1.25 kg). Weight suppression was initially greater for 60 mg than 30 mg, but both were followed by weight gain. Six months off-drug produced greater dose-dependent weight rebound for 60 mg than 30 mg or placebo. Considering both on- and off-drug phases, weight gain for 60 mg of fluoxetine ( M = 6.5 kg) was comparable with that for placebo ( M = 4.7 kg) but greater than that for 30 mg ( M = 3.6 kg). Fluoxetine appears to forestall postcessation weight gain, allowing time for the weight-conscious smoker to focus on quitting smoking rather than on preventing weight gain. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Two studies were performed to investigate the association between body fat mass and fat oxidation. The first, a cross-sectional study of 106 obese women maintaining stable body weight, showed that these two variables were significantly correlated (r = 0.56, P less than 0.001) and the regression coefficient indicated that a 10-kg change in fat mass corresponded to a change in fat oxidation of approximately 20 g/d. The second, a prospective study, validated this estimate and quantifies the long-term adaptations in fat oxidation resulting from body fat loss. Twenty-four moderately obese women were studied under controlled dietary conditions at stable weight before and after mean weight and fat losses of 12.7 and 9.8 kg, respectively. The reduction in fat oxidation was identical to that predicted by the above regression. We conclude that changes in fat mass significantly affect fat oxidation and that this process may contribute to the long-term regulation of fat and energy balance in obese individuals.
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Thirteen sedentary adult females successfully quit smoking cigarettes for 48 days. Mean daily caloric consumption increased 227 kcal and mean weight gain was 2.2 kg. There were no measurable acute effects of smoke inhalation and no chronic net effects of smoking cessation on resting metabolic rate, as determined by oxygen consumption and respiratory exchange ratio. After 1 yr, subjects who continued to abstain gained an average of 8.2 kg. HDL-cholesterol increased 7 mg/dl in 48 days; however, this effect was lost in those who returned to smoking. Increased caloric consumption accounted for 69% of weight gained immediately following smoking cessation. Factors other than changes in caloric consumption and metabolic rate may be responsible for a significant proportion (31%) of the weight gained in individuals who quit smoking.
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The proportion of U.S. adults 35 to 74 years of age who were overweight increased by 9.6 percent for men and 8.0 percent for women between 1978 and 1990. Since the prevalence of smoking declined over the same period, smoking cessation has been suggested as a factor contributing to the increasing prevalence of overweight. To estimate the influence of smoking cessation on the increase in the prevalence of overweight, we analyzed data on current and past weight and smoking status for a national sample of 5247 adults 35 years of age or older who participated in the third National Health and Nutrition Examination Survey, conducted from 1988 through 1991. The results were adjusted for age, sociodemographic characteristics, level of physical activity, alcohol consumption, and (for women) parity. The weight gain over a 10-year period that was associated with the cessation of smoking (i.e., the gain among smokers who quit that was in excess of the gain among continuing smokers) was 4.4 kg for men and 5.0 kg for women. Smokers who had quit within the past 10 years were significantly more likely than respondents who had never smoked to become overweight (odds ratios, 2.4 for men and 2.0 for women). For men, about a quarter (2.3 of 9.6 percentage points) and for women, about a sixth (1.3 of 8.0 percentage points) of the increase in the prevalence of overweight could be attributed to smoking cessation within the past 10 years. Although its health benefits are undeniable, smoking cessation may nevertheless be associated with a small increase in the prevalence of overweight.
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Data from two surveys of the National Academy of Sciences-National Research Council Twin Registry, conducted 16 years apart, were used to determine characteristics of individuals that were predictive of excessive weight gain after smoking cessation. Over the follow-up, 2179 men quit smoking and averaged a weight gain of 3.5 kg. Quitters were grouped into four categories of weight change: lost weight, no change, gained weight, and excessive weight gain ("super-gainers"). In comparison with quitters reporting no change in weight, super-gainers were younger, were of lower socioeconomic status, and differed on a number of health habits before quitting (all Ps < .05). At follow-up, super-gainers reported changes in health habits that were significantly different from those seen in quitters reporting stable weight (all Ps < .05). Pairwise concordance for weight change in 146 monozygotic and 111 dizygotic twin pairs in which both twins quit smoking was significantly greater in monozygotic than dizygotic pairs (P < .01). These results indicate that super-gainers differ in important ways from those who do not gain weight after smoking cessation and that these weight changes may be influenced by underlying genetic factors.
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To determine the risk factors for noninsulin dependent diabetes in a cohort representative of middle aged British men. Prospective study. 7735 men aged 40-59, drawn from one group practice in each of 24 towns in Britain. Known and probable cases of diabetes at screening (n = 158) were excluded. Non-insulin dependent diabetes (doctor diagnosed) over a mean follow up period of 12.8 years. There were 194 new cases of non-insulin dependent diabetes. Body mass index was the dominant risk factor for diabetes, with an age adjusted relative risk (upper fifth to lower fifth) of 11.6; 95% confidence interval 5.4 to 16.8. Men engaged in moderate levels of physical activity had a substantially reduced risk of diabetes, relative to the physically inactive men, after adjustment for age and body mass index (0.4; 0.2 to 0.7), an association which persisted in full multivariate analysis. A nonlinear relation between alcohol intake and diabetes was observed, with the lowest risk among moderate drinkers (16-42 units/week) relative to the baseline group of occasional drinkers (0.6; 0.4 to 1.0). Additional significant predictors of diabetes in multivariate analysis included serum triglyceride concentration, high density lipoprotein cholesterol concentration (inverse association), heart rate, uric acid concentration, and prevalent coronary heart disease. These findings emphasise the interrelations between risk factors for non-insulin dependent diabetes and coronary heart disease and the potential value of an integrated approach to the prevention of these conditions based on the prevention of obesity and the promotion of physical activity.
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To examine the temporal relationship between stopping smoking and total mortality rates among middle-aged women. Prospective cohort study with 12 years of follow-up. Registered nurses residing in the United States. 117,001 female registered nurses, ages 30 to 55 years, who were free of manifest coronary heart disease, stroke, and cancer (except nonmelanoma skin cancer) in 1976. Total mortality, further categorized into deaths from cardiovascular diseases, cancers, and violent deaths. A total of 2847 deaths (933 among "never smokers," 799 among former smokers, and 1115 among current smokers) occurred during 1.37 million person-years of follow-up. The multivariate relative risks for total mortality compared with never smokers were 1.87 (95% CI, 1.65 to 2.13) for current smokers and 1.29 (CI, 1.14 to 1.46) for former smokers. Participants who started smoking before the age of 15 years had the highest risks for total mortality (multivariate relative risk, 3.15; CI, 2.16 to 4.59), cardiovascular disease mortality (relative risk, 9.94; CI, 5.15 to 19.19), and deaths from external causes of injury (relative risk, 5.39; CI, 1.84 to 15.78). Compared with continuing smokers, former smokers had a 24% reduction in risk for cardiovascular disease mortality within 2 years of quitting. The excess risks for total mortality and both cardiovascular disease and total cancer mortality among former smokers approached the level of that for never smokers after 10 to 14 years of abstinence. The health benefits of cessation were clearly present regardless of the age at starting and daily number of cigarettes smoked. The risk of cigarette smoking on total mortality among former smokers decreases nearly to that of never smokers 10 to 14 years after cessation.
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The combination was superior to nicotine patch alone. Data from a preliminary report of long term bupropion treatment (52 weeks) showed that the drug was associated with significantly higher continuous abstinence rates than placebo only to 6 months. However, point prevalence abstinence rates were significantly higher with bupropion than placebo to 18 months. Bupropion 300 mg/day recipients reported nicotine withdrawal symptoms during treatment; however, the symptoms were significantly less severe with bupropion than placebo. Patients receiving bupropion 300 mg/day or bupropion in combination with nicotine patch for smoking cessation generally gained less body weight than placebo recipients. The benefits of bupropion for preventing weight gain persisted after the completion of long term, but not short term therapy. Bupropion was well tolerated in clinical trials, and the only adverse events that were significantly more common with bupropion than placebo were insomnia and dry mouth. Data published so far suggest that sustained release bupropion has a low potential for inducing seizures (seizure rate ≈0.1% in patients with depression). Conclusions: Bupropion is an effective and well tolerated smoking cessation intervention. Further studies with long term follow-up will be useful in determining whether abstinence rates are maintained with bupropion. In addition, clarification of its efficacy in comparison with other therapies used for smoking cessation would help to establish its clinical value. The reduced potential for weight gain with bupropion and the ability to use bupropion in combination with nicotine replacement therapy make the drug a useful treatment option for smoking cessation. Pharmacology The mechanism by which bupropion (amfebutamone) acts as an aid in smoking cessation is unknown. However, bupropion is thought to produce its therapeutic antidepressant effects via the inhibition of noradrenaline and/or dopamine reuptake. Bupropion does not affect serotonin reuptake. Bupropion showed dependence potential in animal models, but not at therapeutic dosages in individuals who abuse drugs or in healthy volunteers. Post-marketing surveillance data have shown that bupropion has a very low abuse potential. Maximum plasma concentrations of sustained release bupropion are reached approximately 3 hours after an oral 150mg dose. Bupropion is highly plasma protein bound, and is extensively metabolised to 3 active metabolites. A single 150mg dose of sustained release bupropion has a mean elimination half-life of 18 to 19 hours. Around 84% and 9% of an oral dose of bupropion was recovered in the urine and faeces, respectively, within 72 hours after administration. There is little available data on the effects of the concomitant administration of bupropion and other drugs on the metabolism of each drug. However, there is potential for interactions between bupropion and drugs that affect the cytochrome P450 (CYP) 2B6 isoenzyme. In addition, bupropion inhibits the activity of the CYP2D6 isoenzyme, which metabolises certain antidepressants (including tricyclic antidepressants and selective serotonin reuptake inhibitors), β-blockers, antiarrhythmics and antipsychotics. It is recommended that coadministration of bupropion and such drugs is approached with caution. There are no significant differences in the pharmacokinetics of sustained release bupropion between smokers and nonsmokers. Sustained release bupropion is bioequivalent to the immediate release formulation in humans. Therapeutic Efficacy Sustained release bupropion 300 mg/day for 7 or 9 weeks significantly increased smoking cessation rates (continuous abstinence and 7-day point prevalence rates) during treatment and at follow-up at 6 and 12 months versus placebo in 2 large well designed studies. Point prevalence rates at 12 months were ≤30.3% with bupropion, whereas values for placebo were ≤15.6%. In 1 trial, continuous abstinence rates at 12 months were 18.4% with bupropion and 5.6% with placebo. Furthermore, bupropion was associated with significantly higher quitting rates than nicotine patch in the only comparison. Combination therapy with bupropion and nicotine patch provided slightly higher abstinence rates than bupropion alone, although differences were not statistically significant. The combination was superior to nicotine patch alone. Data from a preliminary report of long term bupropion treatment (52 weeks) showed that the drug was associated with significantly higher continuous abstinence rates than placebo only to 6 months. However, point prevalence abstinence rates were significantly higher with bupropion than placebo to 18 months. Bupropion 300 mg/day recipients reported significant withdrawal symptoms during treatment; however, the symptoms were significantly less with bupropion than placebo. In the preliminary report of a long term (52 weeks’ treatment) study, bupropion recipients had significantly less craving for cigarettes than placebo recipients and craving was less likely to be the reason for relapse with bupropion than placebo. Bodyweight gain was generally less in patients receiving bupropion 300 mg/day or bupropion in addition to nicotine patch for smoking cessation than in placebo recipients. The benefits of bupropion for preventing weight gain persisted after the completion of long term, but not short term therapy. Tolerability Short term treatment with sustained release bupropion 300 mg/day was well tolerated in clinical trials of the drug for smoking cessation. The only adverse events that were significantly more common with bupropion than placebo were insomnia and dry mouth. Sustained release bupropion appears to have a lower propensity to cause seizures than the immediate release formulation (≈0.1 vs 0.4% for therapeutic dosages); however, no direct comparison of seizure rates between the formulations has been made. Immediate release bupropion was generally well tolerated in patients with pre-existing heart disease. The cardiovascular effects of bupropion have not been assessed in patients with unstable heart disease or recent myocardial infarction, although studies are ongoing. Dosage and Administration It is recommended that sustained release bupropion 300 mg/day (twice daily) is given for 7 to 12 weeks for smoking cessation in adults. A target quitting date should generally be set for within the first 2 weeks of treatment. Patients are able to continue smoking while they take bupropion. In patients requiring continuous treatment, bupropion can be continued for up to 6 months (US) or a year (Canada). Bupropion can be given with transdermal nicotine. Patients with hepatic or renal disease should be treated with reduced dosages of bupropion. Bupropion is contraindicated in patients with bulimia or anorexia nervosa and in patients with seizure disorders. In addition, bupropion should be given with caution to patients with risk factors for seizures. Mothers should not continue breastfeeding infants while taking bupropion.
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Orexins are two recently discovered neuropeptides that can stimulate food intake. As the chronic use of tobacco typically leads to a reduction in body weight, it is of interest to determine whether nicotine, the major biologically active tobacco ingredient, has an effect on orexin metabolism in the brain. Using a semiquantitative RT-PCR technique, the levels of messenger RNA (mRNA) for prepro-orexin, orexin A (OX1-R) and orexin B (OX2-R) receptors were 20–50% higher in rats receiving nicotine for 14 days at the level of 2–4 mg/kg·day compared with rats receiving saline solvent alone. In animals treated with nicotine at 4 mg/kg·day, the expression levels of mRNA for prepro-orexin, OX1-R, and OX2-R were significantly higher compared with those in either the free-feeding control or pair-fed saline control rats. RIA data indicated that both orexin A and orexin B peptide levels were significantly elevated (45–54%; P < 0.01) in the dorsomedial nucleus (DMH) of the nicotine-treated rats compared with either solvent-only or pair-fed controls. Additionally, orexin B was significantly elevated (83%; P < 0.01), over levels in both types of the control animals, in the paraventricular nucleus (PVN) region. In summary, we demonstrated that an inverse association between nicotine and food intake as well as body weight held with doses comparable to those consumed by average human smokers. Moreover, our data indicated that chronic exposure to nicotine can induce a long-term increase in the expression levels of prepro-orexin and their receptor mRNA in the rat hypothalamus and in the levels of orexin A in the DMH and orexin B in the DMH and PVN among the six hypothalamic regions that we examined.
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Background: Smoking relapse is common after successful pharmacologic treatment for smoking cessation. No previous studies have examined long-term drug therapy used expressly for prevention of smoking relapse. Objective: To evaluate the efficacy of bupropion to prevent smoking relapse. Design: Randomized, placebo-controlled trial. Participants: 784 healthy community volunteers who were motivated to quit smoking and who smoked at least 15 cigarettes per day. Intervention: The participants received open-label, sustained-release bupropion, 300 mg/d, for 7 weeks. Participants who were abstinent throughout week 7 of open-label treatment were randomly assigned to receive bupropion, 300 mg/d, or placebo for 45 weeks and were subsequently followed for an additional year after the conclusion of the medication phase. Participants were briefly counseled at all follow-up visits. At the end of open-label bupropion treatment, 461 of 784 participants (58.8%) were abstinent from smoking. Measurement: Self-reported abstinence was confirmed by an expired air carbon monoxide concentration of 10 parts per million or less. Results: The point prevalence of smoking abstinence was significantly higher in the bupropion group than in the placebo group at the end (week 52) of drug therapy (55.1% vs. 42.3%, respectively; P = 0.008) and at week 78 (47.7% vs. 37.7%; P = 0.034) but did not differ at the final (week 104) follow-up visit (41.6% vs. 40.0%). The median time to relapse was significantly greater for bupropion recipients than for placebo recipients (156 days vs. 65 days; P = 0.021). The continuous abstinence rate was higher in the bupropion group than in the placebo group at study week 24 (17 weeks after randomization) (52.3% vs. 42.3%; P = 0.037) but did not differ between groups after week 24. Weight gain was significantly less in the bupropion group than in the placebo group at study weeks 52 (3.8 kg vs. 5.6 kg; P = 0.002) and 104 (4.1 kg vs. 5.4 kg; P = 0.016). Conclusions: In persons who stopped smoking with 7 weeks of bupropion treatment, sustained-release bupropion for 12 months delayed smoking relapse and resulted In less weight gain.
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Hyperinsulinemia, dyslipidemia, and endothelial dysfunction are characteristic findings in insulin-resistant individuals, and all of these abnormalities have been identified as increasing cardiovascular disease (CVD) risk. Smokers tend to be relatively insulin resistant, hyperinsulinemic, and dyslipidemic, with evidence of endothelial dysfunction, as compared with nonsmokers, and recent epidemiologic data have suggested that CVD in smokers is primarily seen in those individuals who also have the characteristic findings of insulin resistance. Based on these observations, it is argued that insulin resistance and its consequences represent a major mechanistic link between cigarette smoking and CVD. It is also postulated that the enhanced CVD risk in smokers, resulting from hyperinsulinemia, abnormalities of lipoprotein metabolism, and endothelial dysfunction, will primarily be present in those smokers who are insulin resistant. As a corollary, it is suggested that CVD risk in individuals who cannot, or will not, stop smoking can be reduced by therapeutic efforts aimed at attenuating the adverse effects of insulin resistance and its consequences.
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The effect of cigarette smoking on other cardiovascular risk factors, serum lipids, body weight, blood pressure and blood sugar was assessed in a randomized control trial of reduction or cessation of cigarette smoking. In the intervention group (n = 107), reported cigarette use fell from 28.5 ± 1.2 ( ± SEM) to 10.6 ± 1.2 cigarettes/day and serum thiocyanate, a biochemical indicator of the extent of tobacco exposure, decreased −42.8 ± 5.5 μmol/l (P < 0.001). Compared to the control group, the intervention group showed significant (P < 0.05) decreases in reported cigarette consumption and serum thiocyanate and significant (P < 0.05) increases in body weight and skinfold thickness. Change in thiocyanate correlated significantly (P < 0.05) and inversely with change in HDL-C, body weight and skinfold thickness, but not with change in LDL-C, triglycerides or blood pressure. These relationships remained significant even after adjusting in multivariate analysis, for initial measurements of these variables or regression to the mean. For those who quit smoking (n = 35) HDL-C increased 5.9 ± 1.7 mg/dl (P < 0.01). The usual inverse relationship between body weight and HDL-C does not exist with cessation of cigarette smoking. Thus, benefits of stopping cigarette smoking extend to favourable alterations in HDL-C and there are no adverse effects on blood pressure, fasting blood sugar, triglycerides or LDL-C.
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Objective: To summarize the Smoking Cessation Clinical Practice Guideline that provides recommendations for 3 groups of professionals: primary care clinicians, smoking cessation specialists, and health care administrators, insurers, and purchasers. Participants: An independent panel of scientists, clinicians, consumers, and methodologists selected by the US Agency for Health Care Policy and Research. Evidence: English-language, peer-reviewed literature published between 1975 and 1994 that addresses the assessment and treatment of tobacco dependence, nicotine addiction, and clinical practice. Consensus process: Four panel meetings were held over 2 years to evaluate meta-analytic and other results, to synthesize the results, and to develop recommendations. The Guideline was repeatedly reviewed and revised. Conclusions: The panel recommendations address 3 audiences. Major recommendations for primary care clinicians are to use officewide systems to identify smokers, treat every smoker with a cessation or motivational intervention, offer nicotine replacement except in special circumstances, and schedule follow-up contact to occur after cessation. Major recommendations to smoking cessation specialists are to use multiple individual or group counseling sessions lasting at least 20 minutes each with sessions spanning multiple weeks, offer nicotine replacement, and provide problem-solving and social support counseling. Major recommendations for health care administrators, insurers, and purchasers are that tobacco-user identification systems be used in all clinics and that smoking cessation treatment be supported through staff education and training, dedicated staff, changes in hospital policies, and the provision of reimbursement for tobacco-dependence treatment.
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Of 66 24–58 yr old smokers in 2 worksites, 67% participated in a smoking cessation program. 55% completed the program. Of those, 29% had quit smoking by posttest, and 17% were abstinent at the 6-mo follow-up. Different variables predicted participation, attrition, and outcome. Significant predictors of smokers who participated were length of cessation in previous abstinence attempts, number of years they smoked, and belief regarding personal vulnerability in contracting a smoking-related disease. Levels of pretest carbon monoxide and attitudes regarding adoption of smoking restrictions in the worksite predicted attrition. Posttest cessation was related to nicotine levels of cigarette brand smoked at pretest and pretest beliefs regarding postcessation weight gain. Abstinence at the 6-mo follow-up was predicted by number of co-workers who smoked and pretest concerns related to postcessation weight gain. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
Challenges the commonly-held assumption that prevention of weight gain after smoking cessation will prevent smoking relapse. The successes or failures of recent pharmacological and nonpharmacological treatments aimed at preventing postcessation weight gain are evaluated. No behavioral treatment has been shown to be successful in attenuating cessation-induced weight gain in healthy ex-smokers, but prospective studies have not reported that weight gain after cessation directly predicts relapse and that adjunct weight-control treatment may be associated with greater smoking relapse. Rather than developing intensive strategies for combating weight gain after smoking cessation, a more prudent approach for researchers may be to re-examine the fundamental relationship among smoking, eating, body weight, and weight-related attitudes. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
Objective: To determine whether attempts to prevent weight gain will increase success rates for stopping smoking. Design: 16 week, open, randomised study with 1 year follow up. Setting: Obesity unit. Subjects: 287 female smokers who had quit smoking before but started again because of weight concerns. Intervention: Combination of a standard smoking cessation programme with nicotine gum and a behavioural weight control programme including a very low energy diet. A control group was treated with the identical programme but without the diet. Main outcome measure: Sustained cessation of smoking. Results: After 16 weeks, 68/137 (50%) women had stopped smoking in the diet group versus 53/150 (35%) in the control group (P=0.01). Among these women, weight fell by mean 2.1 (95% confidence interval 2.9 to 1.3) kg in the diet group but increased by 1.6 (0.9 to 2.3) kg in the control group (P<0.001). After 1 year the success rates in the diet and control groups were 38/137 (28%) and 24/150 (16%) respectively (P<0.05), but there was no statistical difference in weight gain. Conclusions: Combining the smoking cessation programme with an intervention to control weight helped women to stop smoking and control weight.
Article
Background: Although the cessation of smoking reduces the increased risk for ischemic heart disease, it is associated with marked weight gain and presumably insulin resistance, both of which heighten the risk of coronary heart disease. Hypothesis: We investigated the isolated effect of nicotine on body weight and insulin resistance during smoking cessation. Methods: Eleven healthy, middle-aged heavy smokers were studied. Insulin sensitivity was assessed by an insulin-enhanced, frequently sampled intravenous glucose tolerance test with minimal model analysis. The subjects were studied at baseline (last day of smoking) (phase 1), at the end of the 6-week nicotine replacement program (phase 2), and after 8 weeks without smoking or nicotine replacement (phase 3). Results: The subjects started to gain weight during nicotine replacement (phase 2) (0.3 +/- 0.2 kg/week, mean +/- standard deviation) and continued to do so at a steady rate after nicotine replacement was stopped (0.2 +/- 0.2 kg/week) (p = 0.3). Insulin sensitivity decreased by 14 +/- 2.6% during nicotine replacement but increased by 16 +/- 5.1% (compared with phase 2) during phase 3, even though the weight gain continued (p = 0.047; 95% confidence interval: 0.05-5.73). Conclusions: Smoking cessation is associated with weight gain and improvement in insulin resistance. Nicotine is the main ingredient in cigarette smoke causing insulin resistance, but the withdrawal of another, unknown ingredient in cigarette smoke is responsible for the weight gain associated with smoking cessation.
Article
Epidemiological studies have shown an inverse relationship between cigarette smoking and body weight. In rodents, a negative correlation between nicotine and body weight has been reported, but this observation was largely derived from studies where relatively high doses of nicotine (∼12 mg/kg/day) were used. In the current study, we showed that a negative relationship also holds for low doses of nicotine that are comparable to that consumed by average human smokers (<6 mg/kg/day). We also demonstrated that 14 days of nicotine administration (4 mg/kg/day) reduced average daily food intake by 19.5% (P<0.01) in the free-feeding nicotine-treated group compared to saline controls. No significant differences in body weight were detected between the nicotine-treated and pair-fed groups. To determine whether the effects of nicotine on food intake and body weight were related to neuropeptide Y (NPY) expression, semi-quantitative reverse transcription-polymerase chain reaction (RT-PCR) and radioimmunoassay were utilized to measure NPY mRNA and peptide levels in various regions of the hypothalamus. Significantly higher levels of NPY mRNA (ca. 20–50%) and peptide (ca. 24–69%) were only detected in the nicotine-treated groups. In addition, significantly higher NPY contents were also obtained in two hypothalamic areas of pair-fed control animals. In summary, our data suggest that the pharmacological effects of nicotine on food intake and body weight may be mediated by changes in hypothalamic NPY levels, a neuropeptide that is pivotal to the hypothalamic regulation of food intake.
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This study examined the effect of cessation from smoking on body weight, body fat, resting metabolic rate (RMR), and caloric consumption. Twenty-six women aged 25 to 45 years (mean, 37.2 +/- 4.7) who smoked 20 or more cigarettes per day for the past 5 years served as volunteers. Twelve subjects abstained from smoking for a period of 60 days (EXSMOKERS). Six stopped smoking for 30 days, then resumed the habit for an additional 30 days (RESMOKERS). Eight subjects continued to smoke for the entire 60 days (SMOKERS). Additionally, 10 women who had never smoked served as nonsmoking controls (NONSMOKERS). Body weight was recorded weekly and body fat was calculated from body density as determined by hydrostatic weighing. RMR was assessed by open-circuit spirometry. Caloric intake was obtained from 3-day food records using a computerized nutrient data base. Group means for body weight, body fat, RMR, and caloric intake were compared using a repeated measures ANOVA with a Scheffe post hoc at day 0 (baseline), day 30, and day 60 of cessation from smoking. NONSMOKERS weighed significantly (P less than .05) more, but were no fatter than all smoker groups at day 0. Body weight significantly increased by 1.8 kg (EXSMOKERS) and 2.1 kg (RESMOKERS) at day 30 of cessation. By day 60 EXSMOKERS' body weight had increased an additional 1.8 kg to 61.6 +/- 6.4 kg, while return to smoking (RESMOKERS) resulted in a 3.1 kg loss of body weight to 57.9 +/- 7.9 kg.(ABSTRACT TRUNCATED AT 250 WORDS)
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Tobacco smoking reduces appetite and body weight (BW). Cessation of smoking leads to hyperphagia and weight gain. Daily food intake (FI) is a function of meal number (MN) and meal size (MZ), i.e., FI=MN×MZ. Under normal conditions, the female Fischer rat has a periodic reciprocal fluctuation between MZ and MN corresponding to phase of estrous cycle. Wide fluctuations between MZ and MN compensate each other to keep FI constant. Nicotine (5 mg/kg BW/day) was infused via osmotic minipump for 7 days. Controls received saline. FI, MZ, and MN were measured by an Automated Computerized Rat Eater Meter. Nicotine significantly decreased BW and FI via a decrease in MZ without compensatory increase of MN. Nicotine cessation led to hyperphagia, normalizing BW loss via an increase in MZ, which exceeded a compensatory decrease in MN. Nicotine significantly prolonged the estrous cycle by an extension of proestrous phase. Nicotine significantly lengthened the intermeal interval (IMI), delaying the start of the next meal and simultaneously decreasing subsequent MZ. Stopping nicotine led to normalization of IMI and MZ. Data show that nicotine alters the usual reciprocal regulation between MZ and MN and leads to a prolongation of the estrous cycle.