Impact of smoking and smoking cessation on overweight and obesity: Scotland-wide, cross-sectional study on 40,036 participants

Relationship between perception of body image on obesity and smoking status by age group in women: Findings of a seven-year Korean National Survey

INTRODUCTION

This descriptive study examined the relationship between body image perception and smoking status among women aged 19-64 years in Korea, using data from the Korea National Health and Nutrition Examination Survey (KNHANES).

METHODS

This study is a secondary analysis of data gathered from the KNHANES between 2014 and 2020, encompassing 12515 women aged 19-64 years. The final study group consisted of 742 current smokers (CS), 132 hidden smokers (HS), and 11641 non-smokers (NS). Hidden smokers were defined as participants who reported being non-smokers but had urine cotinine levels >50 ng/mL. The participants were divided into three age categories: 19-29, 30-49, and 50-64 years. A multiple logistic regression analysis was used to assess the relationship between body image perception and smoking status, by age group.

RESULTS

Baseline statistics indicated that smokers (both CS and HS) generally had a lower socioeconomic status across all age groups. The highest rate of obesity perception was observed in the CS group, followed by the HS group, in both groups of women aged 19-29 and 30-49 years. However, only women aged 19-29 years in the CS group were more likely to perceive themselves as obese than those in the NS group (AOR=2.60; 95% CI: 1.49-4.52; p=0.001). Furthermore, factors such as current smoking status (AOR=2.32; 95% CI: 1.28-4.23; p=0.006), higher body mass index (AOR=2.95; 95% CI: 2.59-3.37; p<0.001), and perceived health status as poor (AOR=3.82; 95% CI: 2.11-6.92; p<0.001), significantly influenced the perception of obesity in this age group.

CONCLUSIONS

This study identified a notable relationship between obesity perception and smoking among women aged 19-29 years only. These findings suggest that interventions aimed at weight reduction or modifying the perception of obesity, could potentially aid smoking cessation efforts in young women.

The association of smoking with different eating and dietary behaviours: A cross-sectional analysis of 80 296 United Kingdom adults

BACKGROUND AND AIMS

Smokers typically have a lower body mass index (BMI) than non-smokers, while smoking cessation is associated with weight gain. In pre-clinical research, nicotine in tobacco smoking suppresses appetite and influences subsequent eating behaviour; however, this relationship is unclear in humans. This study measured the associations of smoking with different eating and dietary behaviours.

DESIGN

A cross-sectional analysis of data from health assessments conducted between 2004 and 2022.

SETTING

An independent healthcare-based charity within the United Kingdom.

PARTICIPANTS

A total of 80 296 men and women (mean ± standard deviation [SD]: age, 43.0 ± 10.4 years; BMI, 25.7 ± 4.2 kg/m2; 62.5% male) stratified into two groups based on their status as a smoker (n = 6042; 7.5%) or non-smoker (n = 74 254; 92.5%).

MEASUREMENTS

Smoking status (self-report) was the main exposure, while the primary outcomes were selected eating and dietary behaviours. Age, sex and socioeconomic status (index of multiple deprivation [IMD]) were included as covariates and interaction terms, while moderate-to-vigorous exercise and sleep quality were included as covariates only.

FINDINGS

Smokers had lower odds of snacking between meals and eating food as a reward or out of boredom versus non-smokers (all odds ratio [OR] ≤ 0.82; P < 0.001). Furthermore, smokers had higher odds of skipping meals, going more than 3 h without food, adding salt and sugar to their food, overeating and finding it hard to leave something on their plate versus non-smokers (all OR ≥ 1.06; P ≤ 0.030). Additionally, compared with non-smokers, smoking was associated with eating fried food more times per week (rate ratio [RR] = 1.08; P < 0.001), eating fewer meals per day, eating sweet foods between meals and eating dessert on fewer days per week (all RR ≤ 0.93; P < 0.001). Several of these relationships were modified by age, sex and IMD.

CONCLUSIONS

Smoking appears to be associated with eating and dietary behaviours consistent with inhibited food intake, low diet quality and altered food preference. Several of these relationships are moderated by age, sex and socioeconomic status.

Association of overweight and obesity with coronary risk factors and the presence of multivessel disease in patients with obstructive coronary artery disease - A nationwide registry study

Background

The growing prevalence of obesity is expected to increase the burden of coronary artery disease. This study examined the prevalence of overweight and obesity in patients with a first-time diagnosis of obstructive coronary artery disease in a contemporary population. The association of body-mass-index (BMI) with age, traditional risk factors, and the presence of multivessel disease were explored.

Methods and results

Using the Danish Nationwide registries, we identified 49,733 patients with a first-time diagnosis of obstructive coronary artery disease in the period 2012-2018. We investigated the association between BMI and coronary risk factors by multivariate logistic regression. Mean age was 65.8 ± 11.8 years, mean BMI was 27.5 kg/m2 ± 7.2, and 73.2 % were men. 66.3 % had a BMI ≥25 kg/m2 and 1.3 % were underweight. The prevalence of patients with BMI ≥25 kg/m2 decreased with increasing age and was 69 % in patients <50 year vs. 46.2 % in patients ≥80 years (p < 0.001). In all age groups, higher odds of BMI ≥25 kg/m2 were observed in males, former smokers, and patients with hypertension. In multivariate logistic regression, BMI ≥25 kg/m2 was not associated with presence of multivessel disease (p = 0.74).

Conclusion

In this large, nationwide study, 66.3 % of patients with first time diagnosis of obstructive coronary disease had BMI ≥25 kg/m2. Young patients had higher BMI and were more likely to be current smokers. Overweight or obesity was independently associated with the presence of diabetes and hypertension. BMI ≥25 kg/m2 was not independently associated with the presence of multivessel disease.

Estimating causality between smoking and abdominal obesity by Mendelian randomization

BACKGROUND AND AIMS

Smokers tend to have a lower body weight than non-smokers, but also more abdominal fat. It remains unclear whether or not the relationship between smoking and abdominal obesity is causal. Previous Mendelian randomization (MR) studies have investigated this relationship by relying upon a single genetic variant for smoking heaviness. This approach is sensitive to pleiotropic effects and may produce imprecise causal estimates. We aimed to estimate causality between smoking and abdominal obesity using multiple genetic instruments.

DESIGN

MR study using causal analysis using summary effect estimates (CAUSE) and latent heritable confounder MR (LHC-MR) methods that instrument smoking using genome-wide data, and also two-sample MR (2SMR) methods.

SETTING

Genome-wide association studies (GWAS) summary statistics from participants of European ancestry, obtained from the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN), Genetic Investigation of Anthropometric Traits (GIANT) Consortium and the UK Biobank.

PARTICIPANTS

We used GWAS results for smoking initiation (n = 1 232 091), life-time smoking (n = 462 690) and smoking heaviness (n = 337 334) as exposure traits, and waist-hip ratio (WHR) and waist and hip circumferences (WC and HC) (n up to 697 734), with and without adjustment for body mass index (adjBMI), as outcome traits.

MEASUREMENTS

Smoking initiation, life-time smoking, smoking heaviness, WHR, WC, HC, WHRadjBMI, WCadjBMI and HCadjBMI.

FINDINGS

Both CAUSE and LHC-MR indicated a positive causal effect of smoking initiation on WHR (0.13 [95% confidence interval (CI) = 0.10, 0.16 and 0.49 (0.41, 0.57), respectively] and WHRadjBMI (0.07 (0.03, 0.10) and 0.31 (0.26, 0.37). Similarly, they indicated a positive causal effect of life-time smoking on WHR [0.35 (0.29, 0.41) and 0.44 (0.38, 0.51)] and WHRadjBMI [0.18 (0.13, 0.24) and 0.26 (0.20, 0.31)]. In follow-up analyses, smoking particularly increased visceral fat. There was no evidence of a mediating role by cortisol or sex hormones.

CONCLUSIONS

Smoking initiation and higher life-time smoking may lead to increased abdominal fat distribution. The increase in abdominal fat due to smoking is characterized by an increase in visceral fat. Thus, efforts to prevent and cease smoking can have the added benefit of reducing abdominal fat.

Associations between body mass index and smoking behaviour: A cross-sectional study of the German adult population

BACKGROUND

Both smoking and high body weight are risk factors for disease, hence, the association between smoking and body weight is an important health issue. Furthermore, concern about weight gain after quitting smoking is for many smokers a barrier to smoking cessation. The present study aims to explore the association between body mass index (BMI) and current tobacco smoking status in the population of Germany, and smoking and quitting behaviour amongst smokers (and recent ex-smokers =<12 months since quitting).

METHODS

Cross-sectional analysis of two waves of data collected from March through June 2021 through a representative face-to-face household survey in Germany (N = 3 997 respondents aged ≥18). The associations between smoking and quitting behaviours and BMI were analysed through four regression models adjusted for socio-demographic, socio-economic, and smoking characteristics of respondents.

RESULTS

Long-term ex-smokers (>= 12 months since quitting smoking) were more likely to have a higher BMI compared to never smokers (β = 0.64, 95% confidence interval (CI) = 0.10-1.19). There was no statistically significant association between current smoking status or recent ex-smoking status and BMI (β = -0.29,95 %CI = -0.75-0.17 and β = -0.53, 95 %CI = -2.45-1.40). Among current smokers, no statistically significant association was found between BMI and the motivation to stop smoking (OR = 1.01, 95 %CI = 0.99-1.03). Neither number of cigarettes smoked a day nor outcome of most recent quit attempt were related to BMI (β = 0.01, 95 %CI = -0.04-0.05 and OR = 0.41, 95 %CI = 0.05-3.05).

CONCLUSION

In the German population long-term ex-smoking but not current and recent ex-smoking was associated with increased BMI. Future research should further explore the association between smoking behaviour and abdominal obesity, preferably using a more accurate measure for abdominal obesity than BMI.

Pre-diagnostic cigarette smoking and risk of second primary cancer: The Melbourne Collaborative Cohort Study

Enhanced survival following a diagnosis of cancer has led to a steep rise in the number of individuals diagnosed with a second primary cancer. We examined the association between pre-cancer cigarette smoking and risk of second cancer in 9785 participants diagnosed with first invasive cancer after enrolment in the Melbourne Collaborative Cohort Study. Follow-up was from date of first invasive cancer until diagnosis of second primary invasive cancer, death, or 31 July 2019, whichever came first. Data on cigarette smoking was collected at enrolment (1990-94) along with information on other lifestyle factors including body size, alcohol intake and diet. We estimated hazard ratios (HR) and 95 % confidence intervals (CI) for incident second cancer with several smoking measures, adjusted for potential confounders. After a mean follow-up of 7.3 years, 1658 second cancers were identified. All measures of smoking were associated with increased risk of second cancer. We observed a 44 % higher risk of second cancer for smokers of ≥ 20 cigarettes/day (HR=1.44, 95 % CI: 1.18-1.76), compared with never smokers. We also observed dose-dependent associations with number of cigarettes smoked (HR=1.05 per 10 cigarettes/day, 95 % CI: 1.01-1.09) and duration of smoking (HR=1.07 per 10 years, 95 % CI: 1.03-1.10). The risk of second cancer increased by 4 % per 10 pack-years of smoking (HR=1.04, 95 % CI: 1.02-1.06; p < 0.001). There was suggestive evidence of stronger associations with number of cigarettes smoked and pack-years of smoking for women (p_interaction<0.05), particularly for the highest risk categories of both variables. These associations with pre-diagnostic smoking were markedly stronger for second cancers known to be smoking-related than for others (p_homogeneity<0.001). Our findings for pre-diagnostic cigarette smoking indicated increased risk of second primary cancer for cancer sites considered smoking-related, highlighting the importance of assessing smoking habits in cancer survivors.

Modifiable determinants of central obesity among the rural black population in the DIMAMO HDSS, Limpopo, South Africa

Background

Central obesity is a leading risk factor for cardiometabolic diseases, in which body fat accumulates to a particular extent, and may negatively impact on health. The prevalence of abdominal obesity has increased over the last 10 years and currently surpasses that of overall obesity. There is a scarcity of data on the determinants of central obesity, especially among populations residing in rural Africa. The aim of the present study was thus to determine sociodemographic and lifestyle factors that are associated with central obesity.

Methods

This was a cross-sectional, retrospective study. The present study used secondary data from the AWI-Gen phase 1 study. The study comprised 791 participants, of which 242 were men and 549 were women aged 40 years and above. The participants were selected by convenient sampling. Data were analyzed using the Statistical Package for Social Sciences version 27. A comparison of proportions was performed using the chi-square test, while a comparison of means was performed using an unpaired Student t-test. The association between sociodemographic and lifestyle factors with central obesity was analyzed using bivariate correlation, partial correlation, and binary regression analysis, and the statistical significance was set at a p-value of <0.05.

Results

The proportion of central obesity in the total population was 59.9%, and significantly more women were centrally obese (79.6 vs. 15.3%, p = <0.001) as compared to men. Married status correlated positively and significantly with central obesity in both bivariate and partial correlations. Moreover, binary logistic regression further confirmed the positive association between married status and central obesity. Single status correlated negatively and significantly with central obesity. The correlation remained unchanged even after controlling for age and gender. Binary logistic regression showed that unemployment correlated significantly with central obesity. The proportion of smokers was also significantly higher in participants without central obesity than in those with central obesity (87.2 vs. 34.0%, p = <0.001). Smoking correlated negatively and significantly with central obesity in bivariate and partial correlations. In addition, binary logistic regression further confirmed the negative association between smoking and central obesity.

Conclusion

The present study shows that in this population, central obesity is determined by gender, unemployment, and marital status.

Understanding the role of smoking and chronic excess alcohol consumption on reduced caloric intake and the development of sarcopenia

This narrative review provides mechanistic insight into the biological link between smoking and/or chronic excess alcohol consumption, and increased risk of developing sarcopenia. Although the combination of excessive alcohol consumption and smoking is often associated with ectopic adipose deposition, this review is focused on the context of a reduced caloric intake (leading to energy deficit) that also may ensue due to either lifestyle habit. Smoking is a primary cause of periodontitis and chronic obstructive pulmonary disease that both induce swallowing difficulties, inhibit taste and mastication, and are associated with increased risk of muscle atrophy and mitochondrial dysfunction. Smoking may contribute to physical inactivity, energy deficit via reduced caloric intake, and increased systemic inflammation, all of which are factors known to suppress muscle protein synthesis rates. Moreover, chronic excess alcohol consumption may result in gut microbiota dysbiosis and autophagy-induced hyperammonemia, initiating the up-regulation of muscle protein breakdown and down-regulation of muscle protein synthesis via activation of myostatin, AMPK and REDD1, and deactivation of IGF-1. Future research is warranted to explore the link between oral healthcare management and personalised nutrition counselling in light of potential detrimental consequences of chronic smoking on musculoskeletal health outcomes in older adults. Experimental studies should investigate the impact of smoking and chronic excess alcohol consumption on the gut-brain axis, and explore biomarkers of smoking-induced oral disease progression. The implementation of behavioural change interventions and health policies regarding smoking and alcohol intake habits may mitigate the clinical and financial burden of sarcopenia on the healthcare system.

The Effect of Smoking Cessation on Body Weight and Other Metabolic Parameters with Focus on People with Type 2 Diabetes Mellitus

Smokers with diabetes mellitus substantially lower their risks of microvascular and macrovascular diabetic complications, in particular cardiovascular disease, by quitting smoking. However, subsequent post-smoking-cessation weight gain may attenuate some of the beneficial effects of smoking cessation and discourage attempts to quit. Weight gain can temporarily exacerbate diabetes and deteriorate glycemic control and metabolic profile. The molecular mechanisms by which quitting smoking leads to weight gain are largely associated with the removal of nicotine's effects on the central nervous system. This review addresses mechanisms of post-smoking-cessation weight gain, by reviewing the effects of nicotine on appetite, food intake, eating behaviour, energy expenditure, fat oxidation and appetite-regulating peptides. We also highlight correlations between post-cessation weight gain and risk of type 2 diabetes, consequences of weight gain in people with type 2 diabetes and the role of pharmacotherapies, which combine treatment of nicotine addiction and promotion of weight control.

Prenatal Effects of Nicotine on Obesity Risks: A Narrative Review

Nicotine usage by mothers throughout pregnancy has been observed to relate to numerous deleterious effects in children, especially relating to obesity. Children who have prenatally been exposed to nicotine tend to have lower birth weights, with an elevated risk of becoming overweight throughout development and into their adolescent and adult life. There are numerous theories as to how this occurs: catch-up growth theory, thrifty phenotype theory, neurotransmitter or endocrine imbalances theory, and a more recent examination on the genetic factors relating to obesity risk. In addition to the negative effect on bodyweight and BMI, individuals with obesity may also suffer from numerous comorbidities involving metabolic disease. These may include type 1 and 2 diabetes, high cholesterol levels, and liver disease. Predisposition for obesity with nicotine usage may also be associated with genetic risk alleles for obesity, such as the DRD2 A1 variant. This is important for prenatally nicotine-exposed individuals as an opportunity to provide early prevention and intervention of obesity-related risks.

Smoking Cessation Among U.S. Adult Smokers With and Without Chronic Obstructive Pulmonary Disease, 2018

INTRODUCTION

More than 3 of 5 U.S. adults who have ever smoked cigarettes have quit. This study assesses the latest estimates of smoking cessation among U.S. adults with and without chronic obstructive pulmonary disease who have ever smoked cigarettes (ever smokers).

METHODS

Data from 161,233 ever smokers (12.8% with chronic obstructive pulmonary disease) in the 2018 Behavioral Risk Factor Surveillance System were analyzed in 2020. Weighted percentages of quit ratios (percentage of ever smokers who quit smoking), past-year quit attempts (≥1 day), and recent successful cessation (quit ≥6 months ago) by self-reported physician-diagnosed chronic obstructive pulmonary disease status were obtained from multivariable logistic regression analyses, with adjustment for sociodemographic characteristics, health risk behaviors, depression, and asthma.

RESULTS

Adults with chronic obstructive pulmonary disease who smoked had greater age-adjusted past-year quit attempts (68.8% vs 64.3%) but lower recent successful cessation (4.5% vs 5.8%) and quit ratio (53.2% vs 63.9%) than those without chronic obstructive pulmonary disease. After adjusting for covariates, adults with chronic obstructive pulmonary disease who smoked had a significantly higher percentage of past-year quit attempts but similar recent successful cessation and a significantly lower lifetime quit ratio than their counterparts without chronic obstructive pulmonary disease.

CONCLUSIONS

These findings suggest that individuals with chronic obstructive pulmonary disease who try to quit smoking may be less likely to succeed than those without chronic obstructive pulmonary disease. Evidence-based treatments for smoking cessation remain an important component of a comprehensive approach to helping all adults to quit and are a particularly important element of chronic obstructive pulmonary disease management and care.

Prevalence and Risk Factors of Central Obesity among Adults with Normal BMI in Shaanxi, China: A Cross-Sectional Study

(1) Background: The study aims to estimate the prevalence of normal weight with central obesity (NWCO) and to examine the relationship between NWCO and cardiovascular disease risk factors in adults of the province of Shaanxi. (2) Methods: A population-based cross-sectional survey was conducted among residents who were aged 18–80 years and had been living in Zhenba County, Shaanxi Province, for over six months in 2018. Descriptive data analysis and prevalence/frequency were conducted. Logistic regression analyses were used to detect the corresponding factors associated with central obesity. (3) Results: A total of 2312 participants (936 men and 1376 women) were analyzed. The prevalence of NWCO was 58.3%. NWCO was significantly associated with hypertension and dyslipidemia. Compared with normal weight non-central obesity (NWNO), the adjusted odds ratios (ORs) for hypertension were 1.47 (95% CI 1.10–1.98) in men and 1.55 (1.14–2.10) in women, and the corresponding odds ratios for dyslipidemia were 2.71 (1.77–4.13) in men and 1.84 (1.29–2.61) in women. Female sex, age over 58 years, and lower education level were also significantly predictors of abdominal obesity. (4) Conclusions: Body mass index alone as a measure of obesity is not sufficient for assessing health risks. Central obesity index should be used together for clinical assessment.

The association between fitness and obesity in diverse multi-ethnic college students

OBJECTIVE

We examined differences and associations between physical fitness and behavioral factors with obesity in a multi-ethnic student population. Participants: Study population included non-Hispanic whites (NHW, n = 1,454); Hispanics (n = 1,436) and Asians (n = 1,016) at a metropolitan university from Fall 2006 to Fall 2013. Methods: Analyses of Variance and regression analyses, utilizing cross-sectional data, measured the association between fitness, and behavior with obesity. Results: BMI differences (p < .05) were observed between NHW (23.17 ± 3.67), Hispanics (24.32 ± 3.67), and Asians (22.92 ± 4.12). Fitness parameters, relative VO2 max, % body fat, and total fitness score were significantly (p < .0001) associated with obesity. Stress was strongly significantly associated with obesity in Hispanics (p < .001) and somewhat in NHW. Conclusions: Obesity disparities persist in college. Physical fitness and stress management interventions should be targeted towards Hispanic and NHW college students, which may curb current and/or adult-onset obesity.

Prevalence of obesity among U.S. population with substance dependence

AIM

To investigate associations between substance dependence and obesity.

METHODS

Obesity (body mass index ≥ 30 kg/m²) status and the status of dependence on heroin, stimulant, marijuana, nicotine and alcohol (past-month status for nicotine and past-year status for all others) were identified from the U.S. National Survey on Drug Use and Health (NSDUH, 2015-2017) datasets. SAS Surveylogistic regression was used to estimate adjusted odds ratio (AOR) for the association between each substance dependence and obesity, adjusting for potentially confounding effects of sociodemographic factors and health condition.

RESULTS

It was estimated that 10.6 % of noninstitutional U.S. residents aged 12 years or older were nicotine-dependent, 3.0 % alcohol-dependent, 1.0 % marijuana-dependent, 0.6 % stimulant-dependent, and 0.2 % heroin-dependent. Heroin-dependent individuals had 59 % lower odds of obesity relative to their non-dependent counterparts (AOR = 0.41; 95 % CI: 0.28-0.60; p < 0.0001). Lower odds of obesity were also noted for marijuana-dependent (AOR = 0.64; 95 % CI: 0.56-0.73; p < 0.0001), nicotine-dependent (AOR = 0.68; 95 % CI: 0.64-0.72; p < 0.0001) and alcohol-dependent (AOR = 0.77, 95 % CI: 0.69-0.84; p < 0.0001) individuals, but not statistically significant for stimulant-dependent individuals (AOR = 0.84; 95 % CI: 0.68-1.02; p = 0.0825).

CONCLUSIONS

Heroin, marijuana, nicotine and alcohol dependence were associated with lower odds of obesity than their non-dependence counterparts. Main findings based on 2015-2017 NSDUH are consistent with findings from our prior report based on clinical trials data from National Institute on Drug Abuse Clinical Trials Network, and other epidemiological evidence in the literature. These findings can alert substance abuse treatment professionals to monitor weight change, especially among weight-concerned substance abusers.

Nicotine' actions on energy balance: Friend or foe?

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.

Insights into the association between smoking and obesity: the 2014 Indonesian Family Life Survey

BACKGROUND Various findings on the relationship between smoking and obesity have been demonstrated. This study aimed to investigate the association between smoking behavior and obesity in the Indonesian adult population. METHODS A cross-sectional analysis was conducted using data from the 2014 Indonesian Family Life Survey. A body mass index of ≥25 kg/m² was employed to define obesity. Smoking behavior was assessed in terms of smoking status and its attributes. The potential confounders of gender, age, education, residential environment, economic status, physical activity, and education level were adjusted using logistic regression.  RESULTS Study subjects were 28,949 adults aged ≥20 years. Current smoking was a protective factor of obesity (adjusted odds ratio [aOR] = 0.53; 95% confidence interval [CI] = 0.48–0.58), whereas previous smoking habit showed no association with obesity (aOR = 0.96; 95% CI = 0.84–1.09). The risk of current smokers having obesity was lower than that of nonsmokers as smoking duration increased (aOR = 0.46–0.63). By contrast, the risk of obesity was relatively higher among former smokers than current smokers as the duration of quitting increased (aOR = 1.46–2.20). Heavy smokers had a higher risk of obesity than light smokers among former (aOR = 1.85; 95% CI = 1.27–  2.67) and current smokers (aOR = 1.38; 95% CI = 1.23–1.65). CONCLUSIONS Overall, smoking negatively affected obesity among the Indonesian adult population. By contrast, quitting smoking was associated with an increased risk of obesity. Thus, weight management along with smoking cessation intervention should be prescribed.

Effects of lifestyle on physical health in Slovak university students

Overweight and obesity in childhood and young people represent a large global health problem. Therefore, the main aim of the study was to assess the prevalence of overweight/obesity by body mass index (BMI) and its associated lifestyle factors among university students in Slovakia. The BMI index was examined in relation to nine life factors for both sexes, respectively, in a sample of 200 (108 men and 92 women) young university students from Slovakia. The data were obtained using anthropometric measurements and by means of a questionnaire. The results for BMI values confirmed that both sexes were classified into the “about right” weight category. Analysis of the BMI values and questionnaire data showed different results for both sexes. While the type of daily activity and type of physical activity were associated with greater obesity for men, in women, tobacco intake was an important.

Factors associated with improving diet and physical activity among persons with excess body weight

BACKGROUND

As overweight and obesity are highly prevalent in Eastern Europe, the study examined the trends and factors associated with self-reported weight reducing behaviours among individuals with excess body weight in Estonia.

METHODS

Study used nationally representative cross-sectional data from 2006 to 2016 including 4302 men and 3627 women aged 20-64 years with excess body weight (BMI ≥ 25). Trends in the prevalence of changing eating habits and physical activity and their sociodemographic and health-related correlates were studied using descriptive statistics and multivariable logistic regression.

RESULTS

Among overweight or obese respondents, 41% of men and 48% of women reported improvements in dietary habits and 19% of men and women reported increase in physical activity during the past 12 months in 2016. Positive trend for 2006-2016 regarding both outcomes was observed for men whereas no statistically significant differences were found for women. Women and those with lower than tertiary education had higher odds for reporting change in eating habits whereas older age and smoking or excessive alcohol consumption reduced the odds. Improvement in physical activity was more likely among younger respondents, women, ethnic Estonians and those with tertiary education, whereas poorer health and smoking reduced the odds. Weight-related advice from health professionals or family had strong effect on both outcomes.

CONCLUSION

Socio-demographic and health profiles differentiate the self-reported behavioural change among persons with excess body weight. Advice from either health professionals or family may have a potential to facilitate positive changes in eating habits and physical activity among those individuals.

The prevalence of obesity and overweight, associated demographic and lifestyle factors, and health status in the adult population of Jeddah, Saudi Arabia

BACKGROUND

Obesity is a risk factor for many chronic diseases, and its prevalence and trends vary among populations. Saudi Arabia shows a greater rise in prevalence than many other countries. We aimed to study the association between several chronic disorders, demographic, and lifestyle factors with increased body mass index (BMI) in the adult population of Jeddah.

METHODS

Data were obtained from a door-to-door cross sectional study. A three-stage stratified cluster sampling technique was adopted. Individuals in selected households agreeing to participate were interviewed to complete a predesigned questionnaire covering demographic and lifestyle variables, medical history, and family history of chronic diseases. This was followed by anthropometric and blood pressure measurements. A random capillary plasma glucose (RPG) was measured, followed by further testing using fasting plasma glucose and glycated hemoglobin (HbA1c) to verify whether participants were normal, diabetic, or prediabetic. Multiple logistic regression analyses were used to adjust for confounding factors.

RESULTS

A total of 1419 individuals were included in the study: 667 men and 752 women. The prevalence of overweight and obesity was 35.1 and 34.8%, respectively, in men, and 30.1% and 35.6%, respectively, in women. Both overweight and obesity increased in prevalence to 60 years of age, and decreased in the oldest age group in both sexes. After adjusting for age, risk of obesity in men was increased with having a postgraduate degree [odds ratio (OR), 95%CI = 2.48, 1.1-5.61] and decreased with increased physical activity (OR, 95%CI = 0.49, 0.26-0.91). Risk of prediabetes and diabetes was increased in obese women (OR, 95%CI = 2.94, 1.34-6.44, and 3.61, 1.58-8.26 respectively), that of hypertension in obese men (OR, 95%CI =2.62, 1.41-4.87), and that of dyslipidemia in both sexes (OR, 95%CI = 2.60, 1.40-4.83 in men, and 2.0, 1.01-3.85 in women). A family history of dyslipidemia was associated with reduced risk of obesity among women (OR, 95%CI = 0.33, 0.12-0.92), whereas, in people with above normal weight (BMI ⩾25), there was increased risks of prediabetes, diabetes, and dyslipidemia among women (OR, 95%CI = 2.50, 1.21-5.17; 3.20, 1.45-7.03, and 1.88, 1.02-3.49, respectively ), and of hypertension among men (OR, 95%CI = 1.80, 1.00-3.23).

CONCLUSIONS

The prevalence of overweight and obesity in the Saudi population remain high, indicating ineffectiveness or lack of preventive measures. Risk of prediabetes, diabetes, dyslipidemia, and hypertension increased with increasing BMI, with some sex differences in these associations.

Examining the Associations of Smoking Behavior and Obesity Among Older Adults in China: Should We Consider Food Consumption Behaviors?

Objective: This research investigates the associations between smoking frequency and body mass index (BMI) among older adults in China with and without the inclusion of food consumption behaviors. Method: Applying three waves of the Chinese Longitudinal Healthy Longevity Survey (2009, 2012, and 2014), with 12,312 observations from 4,104 participants, gender-stratified panel ordered logistic regressions were performed. Food consumption included intake frequency and types of fruits, vegetables, staple food, cooking oil, and meat. Results: Among male older adults, more frequent smoking behavior was associated with lower BMI with the inclusion of food consumption behaviors. However, more frequent smoking behavior was not associated with BMI among female participants with the inclusion of food consumption behaviors. Former smoking status was not associated with BMI in all models. Discussion: The findings suggest the need of food consumption behaviors when researchers study the associations between smoking frequency and obesity. Gender gaps also should be considered.

Interactions of Behavioral Changes in Smoking, High-risk Drinking, and Weight Gain in a Population of 7.2 Million in Korea

OBJECTIVES

To identify simultaneous behavioral changes in alcohol consumption, smoking, and weight using a fixed-effect model and to characterize their associations with disease status.

METHODS

This study included 7 000 529 individuals who participated in the national biennial health-screening program every 2 years from 2009 to 2016 and were aged 40 or more. We reconstructed the data into an individual-level panel dataset with 4 waves. We used a fixed-effect model for smoking, heavy alcohol drinking, and overweight. The independent variables were sex, age, lifestyle factors, insurance contribution, employment status, and disease status.

RESULTS

Becoming a high-risk drinker and losing weight were associated with initiation or resumption of smoking. Initiation or resumption of smoking and weight gain were associated with non-high-risk drinkers becoming high-risk drinkers. Smoking cessation and becoming a high-risk drinker were associated with normal-weight participants becoming overweight. Participants with newly acquired diabetes mellitus, ischemic heart disease, stroke, and cancer tended to stop smoking, discontinue high-risk drinking, and return to a normal weight.

CONCLUSIONS

These results obtained using a large-scale population-based database documented interactions among lifestyle factors over time.

Modeling Associations between Chemosensation, Liking for Fats and Sweets, Dietary Behaviors and Body Mass Index in Chronic Smokers

Chronic smokers have a greater risk for altered chemosensation, unhealthy dietary patterns, and excessive adiposity. In an observational study of chronic smokers, we modeled relationships between chemosensation, fat/carbohydrate liking, smoking-associated dietary behaviors, and body mass index (BMI). Also tested in the model was liking for sweet electronic cigarette juice (e-juice). Smokers (n = 135, 37 ± 11 years) were measured for: Taste genetics (intensity of 6-n-propylthiouracil-PROP); taste (NaCl and quinine intensities) and olfactory (odor identification) function; liking for cherry e-juice; and weight/height to calculate BMI. Smokers survey-reported their food liking and use of smoking for appetite/weight control. Structural equation models tested direct and indirect relationships between chemosensation, fat/carbohydrate liking, dietary behaviors, and BMI. In good-fitting models, taste intensity was linked to BMI variation through fat/carbohydrate liking (greater PROP intensity→greater NaCl intensity→greater food liking→higher BMI). Olfactory function tended to predict sweet e-juice liking, which, in turn, partially mediated the food liking and BMI association. The path between smoking-associated dietary behaviors and BMI was direct and independent of chemosensation or liking. These findings indicate that taste associates with BMI in chronic smokers through liking of fats/carbohydrates. Future research should determine if vaping sweet e-juice could improve diet quality and adiposity for smokers.

Adolescent smoking: The relationship between cigarette consumption and BMI

Background

Studies relating cigarette smoking and body weight yield conflicting results. Weight-lowering effects in women and men have been associated with smoking, however, no effects on weight have been proven. This study examined the association between cigarette smoking and relative weight in adolescent males and females as they age into young adults.

Methods

Data from the National Longitudinal Survey of Youth—a nationally representative survey conducted annually—was used for this analysis. The sample consists of 4225 males and females observed annually from 1997 at age 12 to 17 through 2011 at age 27 to 31. Hierarchical generalized models (HGM) assess the impact of smoking on the likelihood of having higher BMI controlling for demographic, household and environmental impacts. The second estimation considers the possibility that smoking is endogenous and utilizes a multinomial instrument (IV) for smoking level.

Results

HGM models reveal a negative association between cigarette smoking and BMI for both males and females. Individuals who smoke more have lower BMI compared to infrequent or non-smokers. General health rating, region of residence and income were used instrument for smoking in a linear two-stage IV specification. The instrument is highly correlated with BMI and results mirror the HGM. Finally, models run on early, middle and advanced adolescents show that the relationship diminishes over time. The relationship between BMI and smoking decreases as females age but increases for males.

Conclusions

Empirical models confirm an association cigarette consumption and BMI in both males and females. This negative relationship varies with age. It is important to identify health risks—obesity—and modifiable risk factors—smoking—that contribute to health disparities among adolescents. However, the increase in one risky behavior leading to the decrease in the prevalence of the other, complicates the issue. The higher prevalence of frequent cigarette uses among both adolescents and young adults of lower BMI suggest that smoking could be used curb or suppress appetite.

•

The weight impact of tobacco use by adolescents, unlike adults, has not been conclusively determined.

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This study examines the relationship between cigarette use and the body weight (BMI) of high school aged youth.

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Since smoking can be considered endogeneous in weight studies, smoking is instrumented in a two-stage process.

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Cigarette use is associated with higher BMI, but magnitudes vary by age.

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Models run on early, middle and older adolescents show that the relationship diminishes over time.

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The relationship between BMI and smoking decreases as females age but increases for males.

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Overweight and obese adolescents were more frequent tobacco users.

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Results suggest that electronic and conventional tobacco has similar BMI associations when used independently.

Smoking modifies the effect of two independent SNPs rs5063 and rs198358 of NPPA on central obesity in the Chinese Han population

Obesity is the third most risk factors of death in the middle-income and high-income countries. Whether DNA polymorphisms in CORIN and NPPA genes were associated with obesity, and if these associations could be modified by smoking in the Chinese Han population were unknown, hence a group of 1507 participants were recruited and genotyped for 12 tag single-nucleotide polymorphisms (SNPs) of CORIN and NPPA genes. Regression models were used to test the associations of SNPs with obesity. The potential SNP-smoking interactions were detected in regression models. NPPA SNPs rs5063 and rs198358 were associated with the body mass index (BMI) (P = 0.0053 and 0.0037, respectively). Rs198358 was associated with obesity in both univariate- and multivariable-adjusted analyses (P = 0.0138 and 0.0173, respectively). Rs5063 was associated with central obesity in both univariate- and multivariable-adjusted analyses (P = 0.0454 and 0.0361, respectively). Significant interactions between cigarette smoking and rs5063 and rs198358 were detected (P = 0.0019 and 0.0006, respectively). In subgroup analyses, rs5063 and rs198358 were associated with central obesity in smokers (P = 0.0081 and 0.0037, respectively). The results of our study demonstrated that the effect of NPPA SNPs rs5063 and rs198358 on central obesity might be modified by smoking in the Chinese Han population. Further studies are needed to confirm the associations and elucidate the underlying mechanisms.

Association of current and former smoking with body mass index: A study of smoking discordant twin pairs from 21 twin cohorts

Background

Smokers tend to weigh less than never smokers, while successful quitting leads to an increase in body weight. Because smokers and non-smokers may differ in genetic and environmental family background, we analysed data from twin pairs in which the co-twins differed by their smoking behaviour to evaluate if the association between smoking and body mass index (BMI) remains after controlling for family background.

Methods and findings

The international CODATwins database includes information on smoking and BMI measured between 1960 and 2012 from 156,593 twin individuals 18–69 years of age. Individual-based data (230,378 measurements) and data of smoking discordant twin pairs (altogether 30,014 pairwise measurements, 36% from monozygotic [MZ] pairs) were analysed with linear fixed-effects regression models by 10-year periods. In MZ pairs, the smoking co-twin had, on average, 0.57 kg/m² lower BMI in men (95% confidence interval (CI): 0.49, 0.70) and 0.65 kg/m² lower BMI in women (95% CI: 0.52, 0.79) than the never smoking co-twin. Former smokers had 0.70 kg/m² higher BMI among men (95% CI: 0.63, 0.78) and 0.62 kg/m² higher BMI among women (95% CI: 0.51, 0.73) than their currently smoking MZ co-twins. Little difference in BMI was observed when comparing former smoking co-twins with their never smoking MZ co-twins (0.13 kg/m², 95% CI 0.04, 0.23 among men; -0.04 kg/m², 95% CI -0.16, 0.09 among women). The associations were similar within dizygotic pairs and when analysing twins as individuals. The observed series of cross-sectional associations were independent of sex, age, and measurement decade.

Conclusions

Smoking is associated with lower BMI and smoking cessation with higher BMI. However, the net effect of smoking and subsequent cessation on weight development appears to be minimal, i.e. never more than an average of 0.7 kg/m².

Role of obesity in smoking behaviour: Mendelian randomisation study in UK Biobank

OBJECTIVE

To determine whether body mass index, body fat percentage, and waist circumference influence smoking status and intensity.

DESIGN

Mendelian randomisation study.

SETTING

UK Biobank, with replication of results from the Tobacco and Genetics (TAG) consortium.

PARTICIPANTS

European descent participants from the UK Biobank cohort (n=372 791) and the TAG consortium (n=74 035).

MAIN OUTCOME MEASURES

Risk of current and past smoking, number of cigarettes smoked per day, age of smoking initiation.

RESULTS

The Mendelian randomisation analysis indicated that each standard deviation increment in body mass index (4.6) increased the risk of being a smoker (odds ratio 1.18 (95% confidence interval 1.13 to 1.23), P<0.001). This association was replicated in the TAG consortium data (1.19 (1.06 to 1.33), P=0.003). Furthermore, each standard deviation increment in body mass index was estimated to increase smoking intensity by 0.88 cigarettes per day (95% confidence interval 0.50 to 1.26, P<0.001) in UK Biobank and 1.27 cigarettes per day in the TAG consortium (0.46 to 2.07, P=0.002). Similar results were also seen for body fat percentage and waist circumference in both UK Biobank and the TAG consortium data.

CONCLUSIONS

These results strongly suggest that higher adiposity influences smoking behaviour and could have implications for the implementation of public health interventions aiming to reduce the prevalence of these important risk factors.

Predictors of Continued Smoking and Interest in Cessation Among Older Female Smokers

OBJECTIVES

Older female smokers are highly vulnerable, yet little is known about their attitudes, beliefs, and behaviors regarding smoking cessation.

METHODS

Southeast region Women's Health Initiative participants identified as smokers on at least one prior assessment were surveyed in 2012 regarding current tobacco use.

RESULTS

Most of these current and former smokers ( N = 409, 63% response) were non-Hispanic White (81.7%) and had some college (80%), with mean age of 75.1 years. Current smoking was confirmed by 56%, and while 61% of these reported a past-year quit attempt, less than half used quit aids. Of current smokers, 57.5% intended to quit within 6 months (26.6% within 30 days), and 68% were interested in joining a cessation study.

CONCLUSIONS

Older female smokers were highly motivated to quit, yet profoundly underutilized proven quit aids. Results support high acceptability of cessation interventions for this undertreated population.

A hierarchical Bayesian tri-variate analysis on factors associated with anthropometric measures in a large sample of children and adolescents: the CASPIAN-IV study

BACKGROUND

This study aimed to assess determinants of anthropometric measures in a nationally representative sample of Iranian children and adolescents.

METHODS

This nationwide study was conducted among 13,280 students, aged 6-18 years, who were randomly selected from 30 provinces in Iran. Anthropometric measures were determined by calibrated instruments. Demographic and socio-economic (SES) variables, lifestyle behaviors, family history of chronic disease and prenatal factors were studied, as well. A hierarchical Bayesian tri-variate analysis was used to assess the factors associated with obesity measures of the body mass index (BMI), waist-to-height ratio (WHtR) and wrist circumference (WrC).

RESULTS

The results showed that the BMI was associated with SES score, family history of obesity, family history of diabetes mellitus, physical inactivity, screen time, duration of sleep, breakfast consumption, birth weight, breastfeeding, junk food and place of residence (urban-rural). All these factors were also significantly associated with WrC except for consumption of junk food. Many of these factors had a partial but significant relationship with WHtR.

CONCLUSIONS

Various factors contribute to obesity. Preventive and educational programs on manageable factors such as increasing physical activity, eating breakfast and limiting TV or screen time could be helpful in controlling obesity in schoolchildren and reducing associated complications.

Central obesity and normal-weight central obesity among adults attending healthcare facilities in Buffalo City Metropolitan Municipality, South Africa: a cross-sectional study

BACKGROUND

Central obesity (CO) confers a significant threat on the cardio-metabolic health of individuals, independently of overall obesity. Disparities in the measures of fat distribution lead to misclassification of individuals who are at risk of cardio-metabolic diseases. This study sought to determine the prevalence and correlates of central obesity and normal-weight central obesity among adults attending selected healthcare facilities in Buffalo City Metropolitan Municipality (BCMM), South Africa, assess their health risk and examine the association between central obesity and cardio-metabolic diseases among adults with normal weight, measured by body mass index (BMI).

METHODS

A cross-sectional survey of 998 adults was carried out at the three largest outpatient clinics in BCMM. Overall and central obesity were assessed using BMI, waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHTR). The WHO STEPwise questionnaire was used for data collection. Blood pressure and blood glucose were measured. Normal-weight central obesity was defined as CO among individuals with normal weight, as assessed by BMI. Health risk levels were assessed using the National Institute for Health and Clinical Excellence (NICE) BMI-WC composite index. Bivariate and multivariate analyses were used to determine the prevalence of CO, normal-weight central obesity and the predictors of CO.

RESULTS

The mean age of participants was 42.6 (± 16.5) years. The prevalence of CO was 67.0, 58.0 and 71.0% by WC, WHR and WHTR, respectively. The prevalence of normal-weight central obesity was 26.9, 36.9 and 29.5% by WC, WHR and WHTR, respectively. About 41% of the participants had a very high health risk, 13% had increased risk or high risk and 33% had no health risk. Central obesity was significantly associated with hypertension but not associated with diabetes among those with normal weight (by BMI). Female sex, age over 30 years, marriage, secondary or tertiary level of education, non-smoking status, diabetes and hypertension significantly predicted central obesity among the study participants.

CONCLUSION

The prevalence of central obesity among the study participants is high, irrespective of the defining criteria. One in three adults of normal weight had central obesity. Body mass index should therefore not be used alone for clinical assessment by healthcare workers in the study setting.

Continuous outcome logistic regression for analyzing body mass index distributions

Body mass indices (BMIs) are applied to monitor weight status and associated health risks in populations.  Binary or multinomial logistic regression models are commonly applied in this context, but are only applicable to BMI values categorized within a small set of defined ad hoc BMI categories.  This approach precludes comparisons with studies and models based on different categories.  In addition, ad hoc categorization of BMI values prevents the estimation and analysis of the underlying continuous BMI distribution and leads to information loss.  As an alternative to multinomial regression following ad hoc categorization, we propose a continuous outcome logistic regression model for the estimation of a continuous BMI distribution.  Parameters of interest, such as odds ratios for specific categories, can be extracted from this model post hoc in a general way.  A continuous BMI logistic regression that describes BMI distributions avoids the necessity of ad hoc and post hoc category choice and simplifies between-study comparisons and pooling of studies for joint analyses.  The method was evaluated empirically using data from the Swiss Health Survey.

The prevalence, risk factors and clinical correlates of obesity in Chinese patients with schizophrenia

Obesity is a common comorbidity in schizophrenia. Few studies have addressed obesity in Chinese schizophrenia patients. The aims of this current study were to evaluate the prevalence, risk factors and clinical correlates of obesity in Chinese patients with schizophrenia. A total of 206 patients were recruited from a hospital in Beijing. Their clinical and anthropometric data together with plasma glucose and lipid parameters were collected. Positive and Negative Syndrome Scale (PANSS) was rated for all patients. Overall, 43 (20.9%) patients were obese and 67 (32.5%) were overweight. The obese patients had significantly higher glucose levels, triglyceride levels than non-obese patients. Females and patients with type 2 diabetes mellitus had increased risk for obesity. Correlation analysis showed that BMI was associated with sex, education levels, negative symptoms, total PANSS score, triglyceride levels and type 2 diabetes mellitus. Further stepwise regression analysis showed that sex, type 2 diabetes, education level, triglyceride and amount of smoking/day were significant predictors for obesity. Our study showed that the prevalence of obesity in Chinese patients with schizophrenia is higher than that in the general population. Some demographic and clinical variables are risk factors for obesity in schizophrenia.

Smoking Habits and Body Weight Over the Adult Lifespan in Postmenopausal Women

INTRODUCTION

The inter-relationships between smoking habits and weight gain are complex. However, few studies have examined the association of smoking habits with weight gain over the life course.

METHODS

Major smoking parameters and weight gain over time were examined in a large cohort of postmenopausal women aged 50-79 years at enrollment between 1993 and 1998 (N=161,808) and followed through 2014 (analyses conducted in 2016). Cross-sectional analyses were used to assess the association of smoking and body weight at baseline. Retrospective data were used to correlate smoking status with body weight over a 45-year period prior to enrollment. In addition, the association of smoking with weight gain over 6 years of follow-up was examined.

RESULTS

At baseline, women who had quit smoking prior to enrollment weighed 4.7 kg more than current smokers and 2.6 kg more than never smokers. Former, never, and current smokers all gained weight over the 45-year period from age 18 years to time of enrollment (average age, 63 years): 16.8, 16.4, and 14.6 kg, respectively. In prospective analyses, women who were current smokers at baseline but who quit smoking during follow-up gained more than 5 kg by Year 6 compared with current smokers at baseline who continued to smoke. Among long-term quitters, greater intensity of smoking and more recent quitting were associated with greater weight gain.

CONCLUSIONS

These results suggest that excess weight gain associated with smoking cessation occurs soon after quitting and is modest relative to weight gain in never smokers over the adult lifespan.

Optimism, Cynical Hostility, Falls, and Fractures: The Women's Health Initiative Observational Study (WHI-OS)

Traits of optimism and cynical hostility are features of personality that could influence the risk of falls and fractures by influencing risk-taking behaviors, health behaviors, or inflammation. To test the hypothesis that personality influences falls and fracture risk, we studied 87,342 women enrolled in WHI-OS. Optimism was assessed by the Life Orientation Test-Revised and cynical hostility, the cynicism subscale of the Cook-Medley questionnaire. Higher scores indicate greater optimism and hostility. Optimism and hostility were correlated at r = -0. 31, p < 0.001. Annual self-report of falling ≥2 times in the past year was modeled using repeated measures logistic regression. Cox proportional hazards models were used for the fracture outcomes. We examined the risk of falls and fractures across the quartiles (Q) of optimism and hostility with tests for trends; Q1 formed the referent group. The average follow-up for fractures was 11.4 years and for falls was 7.6 years. In multivariable (MV)-adjusted models, women with the highest optimism scores (Q4) were 11% less likely to report ≥2 falls in the past year (odds ratio [OR] = 0.89; 95% confidence intervals [CI] 0.85-0.90). Women in Q4 for hostility had a 12% higher risk of ≥2 falls (OR = 1.12; 95% CI 1.07-1.17). Higher optimism scores were also associated with a 10% lower risk of fractures, but this association was attenuated in MV models. Women with the greatest hostility (Q4) had a modest increased risk of any fracture (MV-adjusted hazard ratio = 1. 05; 95% CI 1.01-1.09), but there was no association with specific fracture sites. In conclusion, optimism was independently associated with a decreased risk of ≥2 falls, and hostility with an increased risk of ≥2 falls, independent of traditional risk factors. The magnitude of the association was similar to aging 5 years. Whether interventions aimed at attitudes could reduce fall risks remains to be determined. © 2016 American Society for Bone and Mineral Research.

The neurobiological and behavioral overlaps of nicotine and food addiction

Both cigarette smoking and obesity are significant public health concerns and are associated with increased risk of early mortality. It is well established that the mesolimbic dopamine pathway is an important component of the reward system within the brain and is implicated in the development of addiction. Indeed, nicotine and highly palatable foods are capable of altering dopamine release within this system, engendering addictive like responses in susceptible individuals. Although additional research is warranted, findings from animal and human literature have elucidated many of neuroadaptions that occur from exposure to nicotine and highly palatable foods, leading to a greater understanding of the underlying mechanisms contributing to these aberrant behaviors. In this review we present the findings taken from preclinical and clinical literature of the known effects of exposure to nicotine and highly palatable foods on the reward related circuitry within the brain. Further, we compare the neurobiological and behavioral overlaps between nicotine, highly palatable foods and obesity. Lastly, we examine the stigma associated with smoking, obesity and food addiction, and the consequences stigma has on the overall health and wellbeing of an individual.

Predictors of the occurrence of smoking discontinuation in novice adolescent smokers

BACKGROUND

While long-term cessation is an outcome of interest in adult smokers, little is known about discontinuing smoking in adolescent smokers. The objective was to identify the predictors of the occurrence of smoking discontinuation in novice smokers.

METHODS

Data were available for 620 adolescent smokers participating in a longitudinal study on the natural course of nicotine dependence. Data on smoking discontinuation (i.e., stopping smoking for ≥12 consecutive months) were collected in 20 cycles over five years from grade 7 to 11 (1999-2005). Data on 37 potential predictors representing a wide range of demographic, psychosocial, health, lifestyle, smoking-related, and context-related characteristics were collected once, 2 to 3 times, or 20 times. Pooled logistic regression was used to test the association between each potential predictor and smoking discontinuation, adjusting for potential confounders.

RESULTS

Forty percent of 620 participants discontinued smoking during follow up. Male sex [OR (95% confidence interval), 1.8 (1.3-2.4)], age [1.3 (1.1-1.5)], cigarette package warnings [0.6 (0.5-0.9)], team sports participation [1.4 (1.1-1.9)], family stress [0.7 (0.6-1.0)], worrying about weight [0.6 (0.5-0.9)], overweight [0.7 (0.5-1.0)], illicit drugs use [0.5 (0.4-0.7)], tolerance [0.6 (0.4-1.0)], and other nicotine dependence symptoms [1.0 (0.9-1.0)] were statistically significantly associated with smoking discontinuation.

CONCLUSIONS

Both individual and context-level factors were associated with smoking discontinuation.

IMPACT

Programs and policy targeting novice adolescent smokers may be more effective if factors associated with long-term smoking discontinuation are taken into consideration. In particular, young smokers may need help with dependence symptoms, body weight issues, family functioning, and polysubstance use. Cigarette package warnings may be effective in helping adolescents discontinue smoking. Cancer Epidemiol Biomarkers Prev; 23(6); 1090-101. ©2014 AACR.

Factors Associated with Adiposity, Lipid Profile Disorders and the Metabolic Syndrome Occurrence in Premenopausal and Postmenopausal Women

The aim of the study was the assessment of the dependencies between a woman’s menopausal status and adiposity, lipid profile and metabolic syndrome occurrence, as well as finding out whether the correlations between the socio-demographic profile and lifestyle elements and adiposity, lipid profile and the risk of MetS are the same before and after menopause. A cross-sectional study was carried out on 3636 women, aged between 40–59, which involved a questionnaire interview, anthropometric measurements and fasting blood samples, on the basis of which the concentration of triglycerides, cholesterol and glucose was estimated. Before menopause, a greater adiposity (BMIβ = 0.08; %BFβ = 0.07; WCβ = 0.06) was characteristic for women living in a stable relationship than for single women. Women who smoked in the past were characterized by a higher BMI (β = 0.09) and WC (β = 0.06) in comparison with women who have never smoked, while after menopause a greater adiposity (%BFβ = 0.12) and a worse lipid profile (TCβ = 0.08; LDLβ = 0.07; HDLβ = -0.05; TGβ = 0.14) were present in women currently smoking, in comparison to women who have never smoked. After menopause, in women who had two or more children, a greater adiposity (BMIβ = 0.07 and 0.09; %BFβ = 0.05 and 0.07) and a higher risk of MetS (OR = 1.22, 95%CI: 1.03–1.44) was observed compared to nulliparous women, than before menopause. In women with a higher level of education, the risk of MetS after menopause was significantly lower compared with women with a lower level of education (OR = 0.74, 95%CI: 0.61–0.90). Physical activity after menopause had a higher influence on the decrease in the women’s adiposity (BMIβ = -0.11 v. -0.06; %BFβ = -0.11 v. -0.06; WCβ = -0.14 v. -0.08), than before menopause. In women not undergoing hormone replacement therapy, some of the socio-demographic factors and lifestyle elements affected adiposity, lipid profile and the risk of MetS differently before and after menopause, which requires verification through long-term research.

Association between Smoking Status and Obesity in a Nationwide Survey of Japanese Adults

OBJECTIVE

A positive association between the number of cigarettes smoked per day and obesity has been reported, whereas how other smoking-related indices, such as pack-years and duration of smoking, are related with obesity has been less investigated. We analyzed the age-adjusted cross-sectional association between smoking and obesity in a general Japanese population.

METHODS

We used data from a nationwide epidemiological study of Japanese adults (N = 23,106). We compared the prevalence of obesity (defined as body mass index ≥ 25kg/m2) among groups classified by smoking behavior, pack-years, number of cigarettes per day, duration of smoking, and duration and time of smoking cessation.

RESULTS

In men, current smokers had a lower odds ratio (OR) for obesity of 0.80 (95% confidence interval (CI): 0.72-0.88) compared to non-smokers, whereas past smokers had a higher OR of 1.23 (95% CI: 1.09-1.37) compared to current smokers. In women, there were no differences in obesity between the three groups classified by smoking behavior. However, in both sexes, the prevalence of obesity tended to increase with pack-years and the number of cigarettes per day, but not with duration of smoking in current and past smokers. Further, in male smokers, the risks for obesity were markedly higher in short-term heavy smokers compared with long-term light smokers, even with the same number of pack-years. Regarding the impact of smoking cessation, female past smokers who quit smoking at an age > 55-years had an elevated OR of 1.60 (95% CI:1.05-2.38) for obesity.

CONCLUSIONS

In a general Japanese population, obesity is progressively associated with pack-years and number of cigarettes per day, but not with the duration of smoking. When investigating the association between obesity and cigarette smoking, the daily smoking burden and the duration of smoking require to be independently considered.

Smoking Cessation Carries a Short-Term Rising Risk for Newly Diagnosed Diabetes Mellitus Independently of Weight Gain: A 6-Year Retrospective Cohort Study

Background. The effects of smoking on human metabolism are complex. Although smoking increases risk for diabetes mellitus, smoking cessation was also reported to be associated with weight gain and incident diabetes mellitus. We therefore conducted this study to clarify the association between smoking status and newly diagnosed diabetes mellitus. Methods. An analysis was done using the data of a mass health examination performed annually in an industrial park from 2007 to 2013. The association between smoking status and newly diagnosed diabetes mellitus was analyzed with adjustment for weight gain and other potential confounders. Results. Compared with never-smokers, not only current smokers but also ex-smokers in their first two years of abstinence had higher odds ratios (ORs) for newly diagnosed diabetes mellitus (never-smokers 3.6%, OR as 1; current smokers 5.5%, OR = 1.499, 95% CI = 1.147-1.960, and p = 0.003; ex-smokers in their first year of abstinence 7.5%, OR = 1.829, 95% CI = 0.906-3.694, and p = 0.092; and ex-smokers in their second year of abstinence 9.0%, OR = 2.020, 95% CI = 1.031-3.955, and p = 0.040). Conclusion. Smoking cessation generally decreased risk for newly diagnosed diabetes mellitus. However, increased odds were seen within the first 2 years of abstinence independently of weight gain.

Blood lead level and its association with body mass index and obesity in China - Results from SPECT-China study

We aimed to report environmental and blood lead level (BLL) in China, and investigate the relationship of BLL with body mass index (BMI) and obesity. 5558 subjects were enrolled from 16 sites in China. BLL was measured by atomic absorption spectrometry. Obesity was defined as BMI ≥ 30 kg/m². Median (interquartile range) of BLL was 44.00 μg/L (29.00–62.16) for men and 37.79 μg/L (25.13–54.35) for women, about twice higher than in U.S. population. Subjects in rural and high-economic-status areas had significantly greater BLL (P < 0.001). However, in these areas, the lead levels in drinking water, river water and rice were comparable to or significantly lower than those in urban and low-economic-status areas. After adjustment for age, urbanization, economic status and metabolic factors, BLL was independently associated with BMI in women (P for trend < 0.001), but not in men. In fully adjusted model, increased quartiles of BLL were associated with significantly increased odds ratios of obesity (P for trend < 0.01) in women. In conclusion, BLLs in Chinese adults were much higher than in developed countries. There was a sex-specific association between BLL and BMI. Elevated BLL does not appear to be associated with lead levels in drinking water or rice, suggesting some other exposure source.

Interaction of smoking and obesity susceptibility loci on adolescent BMI: The National Longitudinal Study of Adolescent to Adult Health

BACKGROUND

Adolescence is a sensitive period for weight gain and risky health behaviors, such as smoking. Genome-wide association studies (GWAS) have identified loci contributing to adult body mass index (BMI). Evidence suggests that many of these loci have a larger influence on adolescent BMI. However, few studies have examined interactions between smoking and obesity susceptibility loci on BMI. This study investigates the interaction of current smoking and established BMI SNPs on adolescent BMI. Using data from the National Longitudinal Study of Adolescent to Adult Health, a nationally-representative, prospective cohort of the US school-based population in grades 7 to 12 (12-20 years of age) in 1994-95 who have been followed into adulthood (Wave II 1996; ages 12-21, Wave III; ages 18-27), we assessed (in 2014) interactions of 40 BMI-related SNPs and smoking status with percent of the CDC/NCHS 2000 median BMI (%MBMI) in European Americans (n = 5075), African Americans (n = 1744) and Hispanic Americans (n = 1294).

RESULTS

Two SNPs showed nominal significance for interaction (p < 0.05) between smoking and genotype with %MBMI in European Americans (EA) (rs2112347 (POC5): β = 1.98 (0.06, 3.90), p = 0.04 and near rs571312 (MC4R): β 2.15 (-0.03, 4.33) p = 0.05); and one SNP showed a significant interaction effect after stringent correction for multiple testing in Hispanic Americans (HA) (rs1514175 (TNNI3K): β 8.46 (4.32, 12.60), p = 5.9E-05). Stratifying by sex, these interactions suggest a stronger effect in female smokers.

CONCLUSIONS

Our study highlights potentially important sex differences in obesity risk by smoking status in adolescents, with those who may be most likely to initiate smoking (i.e., adolescent females), being at greatest risk for exacerbating genetic obesity susceptibility.

Gender differences influence overweight smokers' experimentation with electronic nicotine delivery systems

INTRODUCTION

Overweight and obese tobacco users possess increased risk of cancer, diabetes, heart disease and chronic tobacco-related disease. Efforts to prevent tobacco-related health risk in this comorbid population would be informed by better understanding and monitoring of trends in the concurrent use of electronic nicotine delivery systems (ENDS) among smokers in the US marketplace.

METHOD

The California Longitudinal Smokers Study (CLSS) established a cohort of current cigarette smokers in 2011 who were surveyed for tobacco use and health behavior at baseline and again in 2012 at follow-up.

RESULTS

We observed a large increase in reported experimentation with ENDS. As hypothesized, overweight or obese smokers were more likely to report experimentation with ENDS, an increase that was also observed among women. Experimentation with ENDS was not associated with a reduction in use of cigarettes or a decrease in cigarette dependence in this high risk population of smokers.

CONCLUSIONS

Continued surveillance of this vulnerable population is needed to better understand how experimentation with new ENDS products may impact health, facilitate switching to non-combustible tobacco or facilitate persistent cigarette dependence.

Ten-year weight gain in smokers who quit, smokers who continued smoking and never smokers in the United States, NHANES 2003-2012

BACKGROUND/OBJECTIVES

Weight gain after quitting smoking is a common concern for smokers and can discourage quit attempts. The purpose of this analysis was to describe the long-term weight gain, smoking cessation attributable (SCA) weight gain and describe their relationship to cigarette consumption and body mass index (BMI) 10 years ago in a contemporary, nationally representative sample of smokers who continued to smoke and those who quit.

SUBJECTS/METHODS

In all, 12,204 adults ⩾36 years old were selected from the 2003-2012 National Health and Nutrition Examination Survey (NHANES). Ten-year weight gain for never, continuing and former smokers (who quit 1-10 years ago) was calculated by body mass index (BMI) 10 years ago and cigarettes per day (CPD). SCA weight gain was calculated by taking the difference between the adjusted mean 10-year weight gain of former smokers and that of continuing smokers.

RESULTS

Mean 10-year weight gain among continuing smokers was 3.5  versus 8.4 kg among former smokers; the SCA weight gain was 4.9 kg. After Bonferroni correction, there was no significant difference in overall weight gain between continuing and former smokers of 1-14 CPD, and SCA weight gain was lowest in this group (2.0 kg, confidence interval (CI): 0.3, 3.7). SCA weight gain was highest for former smokers of ⩾25 CPD (10.3 kg, CI: 7.4, 13.2) and for those who were obese (7.1 kg, CI: 2.9, 11.3) mostly because of lower than average weight gain or weight loss among continuing smokers in these groups.

CONCLUSIONS

In a current, nationally representative sample, baseline BMI and CPD were important factors that contributed to the magnitude of long-term weight gain following smoking cessation. Light to moderate smokers (<15 CPD) experienced little SCA weight gain, whereas heavy smokers (⩾25 CPD) and those who were obese before quitting experienced the most.

Inpatient smoking cessation therapy: truth or dare?

BACKGROUND

This study aims to answer the question to which extent even very heavy nicotine-dependent smokers can benefit from a 3-week inpatient smoking cessation program. A particular focus lies on analyzing the positive effects, which go above and beyond normally anticipated health benefits.

METHODS

This is a descriptive study observing 270 patients over a 1-year period consisting of recruitment, therapy, and two post-therapy follow-up visits at 6-month interval. Gender differences, changes in body weight, and factors relating to addiction and the nicotine withdrawal process are analyzed. In comparing successful participants-post-therapy nonsmokers-with less successful ones, our analysis identifies benefits and advantages an inpatient smoking cessation therapy can bring to even the heaviest smokers.

RESULTS

At the 12-month post-therapy follow-up visit, 42.6% of participants were identified as nonsmokers. A total of 34.0% of participants took up smoking again. No data is available on the remaining participants. Nonsmokers experienced significant reduction in nicotine craving and withdrawal symptoms. In terms of body weight, increases were found in both, men and women, nonsmokers and smokers.

CONCLUSION

Successful quitters fail to report of an unbearable strong desire to smoke. Such unfounded fear should be communicated. Weight gain remains an undesired side effect. Hence, it is crucial to diagnose individuals more prone to weight gain and offer coping strategies thus reducing the risk of developing obesity. Nevertheless, the outcome of the study should be an encouragement to also heavy smokers and empower them to undertake smoking cessation.