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

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.

Brain-wide pleiotropy investigation of alcohol drinking and tobacco smoking behaviors

To investigate the pleiotropic mechanisms linking brain structure and function to alcohol drinking and tobacco smoking, we integrated genome-wide data generated by the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN; up to 805,431 participants) with information related to 3,935 brain imaging-derived phenotypes (IDPs) available from UK Biobank (N=33,224). We observed global genetic correlation of smoking behaviors with white matter hyperintensities, the morphology of the superior longitudinal fasciculus, and the mean thickness of pole-occipital. With respect to the latter brain IDP, we identified a local genetic correlation with age at which the individual began smoking regularly (hg38 chr2:35,895,678-36,640,246: rho=1, p=1.01×10 -5 ). This region has been previously associated with smoking initiation, educational attainment, chronotype, and cortical thickness. Our genetically informed causal inference analysis using both latent causal variable approach and Mendelian randomization linked the activity of prefrontal and premotor cortex and that of superior and inferior precentral sulci, and cingulate sulci to the number of alcoholic drinks per week (genetic causality proportion, gcp=0.38, p=8.9×10 -4 , rho=-0.18±0.07; inverse variance weighting, IVW beta=-0.04, 95%CI=-0.07 - -0.01). This relationship could be related to the role of these brain regions in the modulation of reward-seeking motivation and the processing of social cues. Overall, our brain-wide investigation highlighted that different pleiotropic mechanisms likely contribute to the relationship of brain structure and function with alcohol drinking and tobacco smoking, suggesting decision-making activities and chemosensory processing as modulators of propensity towards alcohol and tobacco consumption.

Prevalence of Obesity Among Electronic Cigarette and Tobacco Users in the United States: Results from the 2018 Wave of the Behavioral Risk Factor Surveillance System

Objective: Tobacco use and obesity are leading causes of preventable death in the U.S. E-cigarette use is on the rise; however, obesity prevalence among e-cigarette users is unknown. The present study characterized obesity prevalence among e-cigarette and tobacco users in a national sample of U.S. adults. Method: Data were obtained from the 2018 Behavioral Risk Factor Surveillance System. Approximately 249,726 participants provided data on e-cigarette and tobacco use, height, weight, and demographics, and were categorized as follows: Ever vaped, ever smoked; Ever vaped, never smoked; Never vaped, ever smoked; Never vaped, never smoked. Results: Obesity prevalence (BMI ≥30 kg/m2) differed significantly across groups: 33.0% (ever vaped, ever smoked); 27.7% (ever vaped, never smoked); 33.1% (never vaped, ever smoked); 32.1% (never vaped, never smoked), p < .001. Groups also differed demographically. Logistic regressions adjusted for demographics revealed subjects in the never vaped, ever smoked group were significantly more likely to have obesity relative to those in the never vaped, never smoked group (p < 0.001) with vaping status having no main effect. Secondary analyses using never smokers as the reference found current smokers were less likely to have obesity and former smokers were more likely to have obesity, p < .001. Discussion: The present study is the first to characterize U.S. obesity prevalence among e-cigarette and tobacco users. Obesity prevalence was lower in the ever vaped, never smoked group; however, this finding appears to be attributable to demographic variables. As e-cigarette use becomes more common, future research should examine the development and maintenance of obesity among users.

Exploring Disparities for Obesity in Korea Using Hierarchical Age-Period-Cohort Analysis With Cross-Classified Random Effect Models

BACKGROUND

This research article investigates the age, period, and birth cohort effects on prevalence of obesity in the Korean population, with the goal of identifying key factors to inform effective public health strategies.

METHODS

We analyzed data from the Korea National Health and Nutrition Examination Survey, spanning 2007-2021, including 35,736 men and 46,756 women. Using the hierarchical age-period-cohort (APC) analysis with cross-classified random effects modeling, we applied multivariable mixed logistic regression to estimate the marginal prevalence of obesity across age, period, and birth cohort, while assessing the interaction between APC and lifestyle and socioeconomic factors.

RESULTS

Our findings reveal an inverted U-shaped age effect on obesity, influenced by smoking history (P for interaction = 0.020) and physical activity (I for interaction < 0.001). The period effect was positive in 2020 and 2021, while negative in 2014 (P for period effect < 0.001). A declining trend in obesity prevalence was observed in birth cohorts from 1980s onward. Notably, disparities in obesity rates among recent birth cohorts have increased in relation to smoking history (P for interaction = 0.020), physical activity (P for interaction < 0.001), and residence (P for interaction = 0.005). Particularly, those born after 1960 were more likely to be obese if they were ex-smokers, physical inactive, or lived in rural areas.

CONCLUSION

These findings highlight growing disparities in obesity within birth cohorts, underscoring the need for targeted health policies that promote smoking cessation and physical activity, especially in rural areas.

Association between weight gain following smoking cessation and development of hypertension in the future

Although quitting smoking lowers the risk of developing chronic conditions, it usually leads to weight gain. Literature on the association between weight gain after quitting smoking and the future development of hypertension is scarce. Among 234 596 individuals who visited our health center, 856 who had quit smoking for whom data were available at least 6 years after smoking cessation were included. We evaluated changes in blood pressure and antihypertensive drug prescription rate at 1 and 6 years after smoking cessation. We also compared weight and blood pressure between the smoking cessation and continued smoking groups after 6 years. Multiple regression analyses were performed to identify predictors of changes in systolic and diastolic blood pressures using covariates affecting blood pressure. Since a median weight gain of 1.8 kg was observed at 1 year after smoking cessation, we divided the participants into high and low-weight gain groups. No significant intergroup difference in the antihypertensive drug prescription rate was observed after 6 years. The high weight gain group showed significant increases in systolic and diastolic blood pressures after 6 years. Multiple regression analyses revealed that systolic blood pressure was affected by age and high weight gain, while diastolic blood pressure was affected by high weight gain. Our findings suggest that weight gain following smoking cessation leads to blood pressure elevation: the smoking cessation group gained more weight and had higher blood pressure than the continued smoking group. Therefore, weight loss guidance may be useful for individuals who want to quit smoking. Participants in the high weight gain group showed significant increases in systolic and diastolic blood pressures at 6 years after smoking cessation that were significantly different from those observed in participants in the low weight gain group and the continued smoking group.

"Healthier health in more ways than one": Perspectives on a program for changing both smoking and obesity-related health behaviors

INTRODUCTION

Individuals with obesity who smoke cigarettes have increased risk of morbidity and mortality. The goal of the current study was to inform the development of a multiple health behavior change intervention designed to facilitate smoking cessation while also targeting weight gain.

METHODS

Four qualitative focus groups were conducted with individuals who smoked cigarettes and had overweight or obesity (n = 16) to explore the combined effects of smoking and obesity, past attempts to quit smoking or lose weight, and preferences for a combined health intervention.

RESULTS

Focus groups converged on five themes including: the interactive effects of weight and smoking; lack of experience with evidence-based weight loss approaches; a desire and expectation to lose weight quickly; rapid weight gain during past attempts at smoking cessation; and interest in a multiple health behavior change intervention with weight management preceding smoking cessation and an emphasis on planning for the future and receiving encouragement and support.

CONCLUSIONS

Groups provided insight into key topics to highlight in a combined intervention and key issues that have interfered with success in both domains.

Development and Evaluation of a Health Behavior Change Clinic in Primary Care: An Interdisciplinary Partnership

Providing effective healthy behavior change interventions within primary care presents numerous challenges. Obesity, tobacco use, and sedentary lifestyle negatively impact the health quality of numerous medical patients, particularly in underserved patient populations with limited resources. Primary Care Behavioral Health (PCBH) models, which incorporate a Behavioral Health Consultant (BHC), can offer point-of-contact psychological consultation, treatment, and also provide opportunities for interdisciplinary psychologist-physician clinical partnerships to pair a BHC's health behavior change expertise with the physician's medical care. Such models can also enhance medical training programs by providing resident physicians with live, case-based learning opportunities when partnered with a BHC to address patient health behaviors. We will describe the development, implementation, and preliminary outcomes of a PCBH psychologist-physician interdisciplinary health behavior change clinic within a Family Medicine residency program. Patient outcomes revealed significant reductions (p < .01) in weight, BMI, and tobacco use. Implications and future directions are discussed.

Determinants of smoking related weight-concern in smokers participating in a community-based cessation program

BACKGROUND

Concern about weight gain is a barrier to smoking-cessation, but determinants of postcessation weight-concern have not been comprehensively assessed in the context of community-based cessation programs.

METHODS

This cross-sectional analysis used baseline data from a cessation trial of 392 adults randomized to physical activity (PA) or general wellness counseling as adjunctive treatment for smoking. Outcomes were 1) smoking behaviors to control weight and 2) anticipating relapse due to weight gain. Independent variables were PA and perceptions, sociodemographics, psychosocial measures, smoking behavior and perceptions, diet, and BMI. From bivariable models examining main and sex interaction effects, significant variables were entered into a linear (control) or logistic (relapse) regression model to identify key determinants.

RESULTS

For both measures, weight-concern was greater (p < .05) for female smokers (standardized b = 0.52, SE = 0.10; OR = 0.29, 95 % CI = 0.17-0.49), White (b = 0.12, SE = 0.05; OR = 0.39, 95 % CI = 0.23-0.66), and less motivated to quit (b = -0.14, SE = 0.05; OR = 0.77, 95 % CI = 0.59-1.0). Higher scores for smoking to control weight were associated with less PA (b = -0.10, SE = 0.05) and higher BMI (b = 0.21, SE = 0.05). For men, higher BMI was associated with greater anticipation of relapse (OR = 2.54, 95 % CI = 1.42-4.56).

CONCLUSIONS

Among adults attempting cessation, women, White smokers, and those less motivated to quit were more likely to smoke for weight control and to relapse due to weight gain. Higher BMI was associated with greater anticipation of relapse for men, but not women. Weight-concerns, for both measures, were not related to smoking history, psychosocial functioning, PA engagement or attitudes, or dietary variables. Results suggest potential cessation intervention targets for weight-concerned smokers.

Weighing cessation: Rising adiposity of current smokers in NHANES

BACKGROUND

Rising rates of obesity may have interacting effects with smoking given associated cardiovascular risks and cessation-associated weight gain. This study aimed to assess the change in body mass index (BMI) magnitude and prevalence of obesity and central adiposity over time among current smokers and to compare with that of former and never smokers to describe how the obesity and tobacco epidemics interrelate.

METHODS

Using data from the National Health and Nutrition Examination Survey (NHANES) 1976-2018, survey-weighted, internally standardized analyses were used to look at outcomes of BMI, BMI category, and central adiposity by smoking status. A nonparametric test assessed trend over time.

RESULTS

The standardized proportion of current smokers with obesity increased from 11.6% in NHANES II to 36.3% in continuous NHANES 2017-2018; at the latest assessment this proportion was significantly lower than for former smokers. Mean BMI among current smokers also increased, from 24.7 kg/m2 to 28.5 kg/m2 among current smokers, which is significantly lower than among former smokers and never smokers at the latest time point. The standardized proportion of current smokers with central adiposity also increased, from 34.3% to 54.1%; again, at the latest time point the proportion was lower than for former smokers or never smokers.

CONCLUSION

Between 1976 and 2018, smoking rates decreased while adiposity increased among current, former, and never smokers. Over a third of current smokers meet BMI criteria for obesity and over half have an elevated waist circumference. It is imperative that weight management strategies be incorporated into smoking cessation approaches.

Overweight and obesity in adulthood, sociodemographic factors, lifestyle, and the early burden of noncommunicable diseases among Americans: NHANES 2007-2018

OBJECTIVES

To evaluate the association between nutritional status in early adulthood and the burden of noncommunicable diseases (NCDs); To evaluate the influence of sociodemographic factors and lifestyle on the outcomes of BMI kg/m2  ≤24.9, ≥25.0, and ≥30.0; to estimate the population attributable fraction (PAF) to BMI elevated at 25 years old in the burden of NCDs in American adults.

METHODS

We used data from 15 721 American adults participating in the National Health and Nutrition Examination Survey from 2007 to 2018. The Hazard Ratio (HR), Incidence Rate Ratio (IRR), and 95% confidence intervals (CI) were estimated in the proportional risk regression models of Cox (entire population) and Poisson (restricted to non-patients), respectively. The proportionality of the risk between the burden of NCDs and BMI at 25 years old was drawn by the Kaplan-Meier curve, and the PAF was calculated. All analyses were adjusted taking into account the sample weights.

RESULTS

Health disparities (sex, age, race/ethnicity, education, poverty index, and education level), and lifestyle (physical activity, smoking, and alcohol consumption) influenced the current nutritional status. Cumulative survival in overweight and obese groups decreased considerably over time (p < .0001). Being overweight and obese in adulthood may increase the risk of early NCDs (HR: 1.68, 95% CI: 1.54-1.84 and HR: 2.87, 95% CI: 2.56-3.21, respectively). About 22.72% (95% CI: 19.99-25.36, p < .001) of the burden NCDs could have been avoided if overweight at age 25 had been prevented.

CONCLUSIONS

Monitoring weight change from young adulthood can provide a sensitive and useful clinical measure for early detection of adverse trends in NCDs risk.

Behavioral activation for smoking cessation and the prevention of smoking cessation-related weight gain: A randomized trial

BACKGROUND

Post-cessation weight gain (PCWG) is an obstacle to smoking cessation. This trial evaluated a behavioral intervention targeting alternative rewards to smoking and high calorie snacking to promote smoking cessation while mitigating PCWG.

METHODS

Adult smokers (n = 288; 119 females, 169 males) received eight weeks of transdermal nicotine and were randomized to eight sessions of behavioral activation for smoking cessation and the mitigation of PCWG (BAS+) or standard smoking cessation counseling (SC). Primary outcomes were 7-day point prevalence abstinence and PCWG 26 weeks after the target quit date. Change in caloric intake from pre-treatment through the 26-week follow-up was a secondary outcome. Data were collected from September 2016 to February 2021, and analyses were completed in July 2022.

RESULTS

BAS+ and SC did not differ in smoking abstinence rates at the 26-week follow-up (OR=0.80, 95%CI 0.50-1.27, p = 0.34; 18% versus 23%). There were no significant differences in PCWG between BAS+ and SC who were 7-day point prevalence abstinent (β = -0.29, 95%CI -2.13 to 1.65, p = 0.77; 2.60 versus 2.20 pounds, respectively) or among those continuously abstinent (5.78 versus 5.34 pounds, respectively). There were no significant differences in caloric intake between BAS+ and SC from baseline to the 26-week follow-up (β = 110.65, 95%CI -96.72 to 318.02, p = 0.30; -19.1 versus -116.9 kcals/day, respectively).

CONCLUSIONS

The results do not support the efficacy of BAS+ for smoking cessation and the prevention of PCWG. These findings join a growing body of research highlighting the challenge of minimizing PCWG and promoting smoking abstinence.

Bariatric surgery and weight loss in the short- and long-term: Evidence from NHANES 2015-2018

The present study aimed to examine short- and long-term weight change in a nationally representative sample of US adults who reportedly underwent bariatric surgery. Individuals aged 20-64 at survey from the US National Health and Nutrition Examination Survey 2015-2018 were included in the analyses (n = 6776). The primary comparison groups include 62 participants who underwent bariatric surgery, 1531 eligible but did not receive surgery, and 5183 not eligible for bariatric surgery. After adjusting for demographic characteristics and comorbidity, adults who reported receiving bariatric surgery were 5.0 times (4.0-6.0) more likely to achieve at least 20% weight loss from maximum weight relative to those who were eligible but reported no surgery. The likelihood appeared to be higher when surgery was performed within 10 years (short-term, PR 5.5, 95% CI: 4.0, 7.0) relative to surgeries that were performed for 10 or more years (long-term, PR 3.6, 95% CI: 2.0, 5.3). In this nationally representative sample of US adults, respondents who received bariatric surgery achieved substantial and significant weight loss compared with those who were eligible and did not receive bariatric surgery. Weight loss appeared to be most apparent in the short term and persisted over the long term.

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.

Lifestyle and socioeconomic determinants of diabetes: Evidence from country-level data

Objective

The objectives of the study is to investigate the global socioeconomic risk factors associated with diabetes prevalence using evidence from available country-level data.

Design

A cross-sectional study based on (2010 & 2019) countrywide Health Nutrition and Population Statistics data.

Population

People ages 20–79 who have diabetes.

Setting

One hundred and thirty-two countries or territories in the world.

Primary outcome measure

Diabetes prevalence rates were determined from (2010 & 2019) countrywide Health Nutrition and Population Statistics (Health Stats, World Bank Group).

Results

In 2010, a 1% increase in per capita income and total tobacco consumption is associated with a 0.92% (95% CI 0.64% to 1.19%) and 0.02% (95% CI 0.006% to 0.047%) increase in diabetes prevalence respectively; and a 1% increase in alcohol consumption is associated with a -0.85% (95% CI -1.17% to -0.53%) decrease in diabetes prevalence. Statistically significant socioeconomic and lifestyle indices positively associated with diabetes prevalence included gross national income; overweight prevalence (BMI>25 kg/m²); and tobacco consumption. Statistically significant inverse associations with global diabetes prevalence included total population size; unemployment and alcohol consumption. The 2019 data was removed due to sparsity of data.

Conclusion

Statistically significant global lifestyle and socioeconomic determinants of diabetes prevalence include alcohol consumption; tobacco consumption; overweight prevalence; per capita income; total population and unemployment rates. Determinants of diabetes include modifiable risk factors which are consistent at both the micro and macro level and include tobacco consumption and overweight prevalence. Factors which are non-modifiable and warrant further investigation include total population and unemployment rates, which were inversely associated with diabetes prevalence and are a product of other underlying factors. Other determinants such as alcohol consumption was also inversely associated with diabetes prevalence, but has been observed to have both negative and positive associations with diabetes at the micro-level. These associations were dependent upon the amount of alcohol consumed. Global cut-off point of alcohol consumption is critical to establish global policies to reduce diabetes prevalence. Overall, the use of cross-sectional based study for country level aggregate data is a critical tool that should be considered when making global joint strategies or policies against diabetes in both data analysis and decision making.

10-Year Weight Gain in 13,802 US Adults: The Role of Age, Sex, and Race

Purpose

The primary objective of the present investigation was to identify 10-year weight gain patterns in 13,802 US adults and also to determine the extent that differences in 10-year weight gains were associated with the key demographic variables: age, sex, and race.

Methods

The study design was cross-sectional and included the years 2011-2018. Data for 2019-2020 were not available because of COVID. A multistage random sampling strategy was employed. Specifically, individual sample weights and randomly selected clusters and strata were used with each statistical model, allowing the results to be generalized to the US adult population.

Results

Mean (±SE) 10-year weight gain was 4.2 ± 0.2 kg or 6.6 ± 0.2% of initial body weight. A total of 51% of the participants gained 5% or more body weight, 36% gained 10% or more, and 16% gained 20% or more across the 10-years. Age was linearly and inversely associated with 10-year weight gain, expressed in kg (F = 166.4, P < 0.0001) or percent weight gain (F = 246.9, P < 0.0001), after adjusting for sex and race. For each 1-year increase in age, 10-year weight gain decreased by 0.20 ± 0.02 kg and 0.28 ± 0.02 percent. After adjusting for age and race, 10-year weight gain (kg) was significantly greater (F = 73.6, P < 0.0001) in women (5.4 ± 0.3) than in men (2.6 ± 0.2). Weight gain also differed across races, kg (F = 27.7, P < 0.0001) and % (F = 28.5, P < 0.0001). Non-Hispanic Blacks gained more weight and NH Asians gained less weight than the other races.

Conclusion

Without question, 10-year weight gain is a serious problem within the US adult population. Younger adults, women, and Non-Hispanic Blacks, particularly Black women, seem to experience the highest levels of 10-year weight gain. Consequently, obesity and weight gain prevention programs focusing on these at-risk individuals should be a public health priority.

Delayed Finalization of Sodium Targets in the United States May Cost Over 250 000 Lives by 2031

BACKGROUND

The US Food and Drug Administration (FDA) proposed 2- and 10-year voluntary sodium-reduction targets for >150 packaged- and prepared-food categories in 2016 and finalized the short-term targets in 2021.

METHODS

We modeled the health benefits of implementing the newly finalized sodium targets, and the net health losses because of the 4.3-year delay in finalizing the sodium targets in different compliance scenarios in adults aged ≥30, using the National Health and Nutrition Examination Survey (NHANES) 2015 to 2016 cycle. The health impact was estimated by multiplying the projected reduction in population sodium intake by the annual health benefits resulting from every 1000-mg reduction in daily sodium intake.

RESULTS

Under certain assumptions, the FDA's finalization of the short-term targets in Oct 2021 and possible finalization of the long-term targets by April 2024 is projected to save up to 445 979 (95% CI, 17 349-787 352) lives in the coming 10 years. The net number of unnecessary deaths because of FDA's delay is projected to be as high as 264 644 (95% CI, 10 295-467 215) according to our prediction.

CONCLUSIONS

These findings highlight the enormous health costs due to the FDA's delay in finalizing the sodium-reduction targets, and the great potential health benefits of industry compliance with the FDA's finalization of its short- and long-term targets in the coming 10 years.

A Systematic Review and Meta-Analysis of Smoking and Circulating Sex Hormone Levels Among Premenopausal Women

It is established that higher pre-diagnostic circulating androgen and estrogen levels are associated with increased breast cancer risk in premenopausal and postmenopausal women. Pooled analyses in postmenopausal women report higher androgen and estrogen levels in current heavy cigarette smokers compared to nonsmokers. However, evidence among premenopausal women has been inconsistent. We conducted a systematic review and meta-analysis to estimate differences in standardized mean hormone levels among current premenopausal smokers compared to nonsmokers. We reviewed and collated publications with sex hormone levels by smoking status among healthy, premenopausal women who were nonusers of exogenous hormones, including oral contraceptives, using PubMed through December 2019. A random effects meta-analysis was conducted to combine the standardized mean differences (SMD) and 95% confidence intervals (CIs) for estradiol, progesterone, testosterone, dehydroepiandrosterone, dehydroepiandrosterone-sulfate, and sex hormone-binding globulin by smoking status. Findings were summarized by menstrual cycle phase and overall. Nineteen published peer-reviewed articles were included. Significantly increased testosterone levels among smokers compared to nonsmokers were identified from cross-sectional studies with varied menstrual phase timing (SMD 0.14; 95% CI 0.0005, 0.29) and significantly increased dehydroepiandrosterone-sulfate levels were found over all phases (SMD 0.12; 95% CI 0.01, 0.22). However, substantial heterogeneity existed in these studies. This meta-analysis suggests that smoking may increase blood androgen levels in healthy premenopausal women which may increase breast cancer risk; however, the differences were modest. Larger and covariate-adjusted studies with standardized collection over the menstrual cycle are needed to better understand this relationship and to reduce heterogeneity. Implications: Existing research has described associations between high pre-diagnostic estradiol and androgen levels with breast cancer risk among premenopausal women and has established active smoking as a breast cancer risk factor. However, the smoking and circulating sex hormone associations among premenopausal women remain inadequately studied. In this meta-analysis, we identified an association between smoking and higher mean testosterone and dehydroepiandrosterone-sulfate levels with consideration of menstrual phase, providing additional information on smoking's potential pathway to premenopausal breast cancer.

Lifelong smoking status, weight gain, and subsequent risk of major adverse cardiovascular events: Long-term follow-up of a middle-aged Chinese population

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 (p_trend = 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 (p_trend = 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.

Interventions for preventing weight gain after smoking cessation

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.

Brain-derived neurotrophic factor gene variants and obesity in former smokers

OBJECTIVE

From genome-wide association studies, brain-derived neurotrophic factor (BDNF) locus on chromosome 11 was the only SNP associated with both smoking and body mass index (BMI) in European, African and Asian population. This study aims to explore the unique genetic predisposition to obesity in former smokers by examining the effects of BDNF on BMI and waist circumference (WC).

METHODS

The study design is case-control study with a cohort validation in supplementary. We included 15,072 ethnic Chinese participants in the Guangzhou Biobank Cohort Study (GBCS) with data of four BDNF SNPs related to both BMI and smoking behavior. We used baseline smoke exposure data in 2003-2007 and follow-up outcomes of general obesity (by BMI) and central obesity (WC) in 2008-2012. Odds ratios (ORs) and 95% confidence intervals (CIs) for general obesity and central obesity associated with these SNPs were derived from logistic regression.

RESULTS

Of 15,072 participants (3169 men and 11,903 women), 1664 (11.0%) had general and 7868 (52.2%) had central obesity. In 1233 former smokers, the rs6265 GG, versus AA, genotype was associated with higher risks of general obesity (OR = 1.79, 95% CI = 1.06-3.01) and central obesity (OR = 2.08, 95% CI = 1.47-2.92) after adjustment. These associations were not significant in never or current smokers. In former heavy (≥20 cigarettes/day) smokers, the rs6265 GG genotype showed a higher odds for general obesity (OR = 2.15, 95% CI = 1.05-4.40), while no association was found in former light (1-9 cigarettes/day) smokers. Similar results were found for the association of rs6265 with central obesity and for the associations of other two BDNF SNPs (rs4923457 and rs11030104) with both general and central obesity.

CONCLUSIONS

We firstly identified the genetic predisposition (BDNF SNPs) to general and central obesity in former smokers, particularly in former heavy smokers. The different associations of the SNPs for general/central obesity in different smoke exposure groups may be related to the competitive performance of the sites and epigenetic modification, which needs further study.

Nicotine and energy balance: A review examining the effect of nicotine on hormonal appetite regulation and energy expenditure

Nicotine has been shown to decrease appetite, food intake (FI) and body weight, but the mechanisms are unclear. The purpose of this review was to examine research on the effects of nicotine on energy balance by exploring physiological mechanisms and hormone regulation related to FI, subjective appetite and energy expenditure (EE). We searched PubMed and MEDLINE, and included articles investigating the effects of nicotine on central appetite regulation, FI, leptin, peptide-YY (PYY), ghrelin, glucagon-like peptide-1 (GLP-1), adiponectin, cholecystokinin (CCK), orexin, and EE. A total of 65 studies were included in the qualitative synthesis and review. Our findings suggest that the decrease in appetite and FI may be attributed to nicotinic alterations of neuropeptide Y (NPY) and pro-opiomelanocortin (POMC) but the effect of nicotine on FI remains unclear. Furthermore, nicotine increases resting EE (REE) and physical activity EE (PAEE) in both smokers and non-smokers; and these increases may be a result of the catecholaminergic effect of nicotine. Decreases in body weight and appetite experienced by nicotine users results from increased EE and changes in the central hypothalamic regulation of appetite. There is not enough evidence to implicate a relationship between peripheral hormones and changes in appetite or FI after nicotine use. Although nicotine increases REE and PAEE, the effect of nicotine on other components of EE warrants further research. We conclude that further research evaluating the effect of nicotine on appetite hormones, FI and EE in humans is warranted.

Weight Gain After Smoking Cessation and Risk of Major Chronic Diseases and Mortality

IMPORTANCE

Smoking cessation is frequently followed by weight gain; however, whether weight gain after quitting reduces the health benefits of quitting is unclear.

OBJECTIVE

To examine the association between weight change after smoking cessation and the risk of cardiovascular diseases (CVD), type 2 diabetes, cancer, chronic obstructive pulmonary disease (COPD), and all-cause mortality.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study analyzed data from a nationally representative sample of Australian adults aged 18 years or older who were studied between 2006 and 2014. Smoking status and anthropometric measurements were self-reported annually. Cox proportional hazards regressions were used to determine the hazard ratios (HRs) for the association between changes in weight and body mass index (BMI) and the risk of CVD, type 2 diabetes, cancer, COPD, and mortality. Data were analyzed in January 2019.

EXPOSURES

Annual self-reported smoking status; years since quitting.

MAIN OUTCOMES AND MEASURES

Weight gain after quitting, incident CVD, type 2 diabetes, cancer, COPD, and all-cause mortality.

RESULTS

Of a total 16 663 participants (8082 men and 8581 women; mean [SD] age, 43.7 [16.3] years), those who quit smoking had greater increases in weight (mean difference [MD], 3.14 kg; 95% CI, 1.39-4.87) and BMI (MD, 0.82; 95% CI, 0.21-1.44) than continuing smokers. Compared with continuing smokers, the HRs for death were 0.50 (95% CI, 0.36-0.68) among quitters who lost weight, 0.79 (95% CI, 0.51-0.98) among quitters without weight change, 0.33 (95% CI, 0.21-0.51) among quitters who gained 0.1 to 5.0 kg, 0.24 (95% CI, 0.11-0.53) among quitters who gained 5.1 to 10 kg, and 0.36 (95% CI, 0.16-0.82) among quitters who gained more than 10 kg. The HRs for death were 0.61 (95% CI, 0.45-0.83) among quitters who lost BMI, 0.86 (95% CI, 0.51-1.44) among quitters without change in BMI, 0.32 (95% CI, 0.21-0.50) among quitters who gained up to 2 in BMI, and 0.26 (95% CI, 0.16-0.45) among quitters who gained more than 2 in BMI.

CONCLUSIONS AND RELEVANCE

This cohort study found that smoking cessation was accompanied by a substantial weight gain; however, this was not associated with an increased risk of chronic diseases or an attenuation of the mortality benefit of cessation.

Cigarette Use and Adolescent Metabolic and Bariatric Surgery

OBJECTIVE

This study aimed to track conventional cigarette smoking behaviors and associated correlates in adolescents with severe obesity who did or did not undergo metabolic and bariatric surgery to 4 years after surgery/baseline.

METHODS

Utilizing a prospective controlled design, surgical (n = 153; mean BMI = 52) and nonsurgical (n = 70; mean BMI = 47) groups that completed assessments before surgery/at baseline and at Years 2 and 4 post surgery (Year 4: n = 117 surgical [mean BMI = 38]; n = 56 nonsurgical [mean BMI = 48]) were compared. Separate logistic regression models tested correlates of Year 4 current smoking.

RESULTS

More than half of participants (surgical: 55%; nonsurgical: 60%) had ever smoked a cigarette, with current smoking increasing with time. Groups did not differ in Year 4 current smoking (surgical: 23%; nonsurgical: 33%), with ≈ 50% meeting criteria for "heavy" smoking (≥ half pack/day) and ≈ 40% smoking their first cigarette before ninth grade. Factors associated with higher odds of Year 4 current smoking included dysregulation (P < 0.001), internalizing symptoms (P = 0.01), alcohol use (P = 0.04), caregiver smoking (P < 0.001), friend smoking (P = 0.001), and perceiving low harm (P = 0.02), plus greater percent weight loss (P = 0.03) in the surgical group.

CONCLUSIONS

Smoking is a clinical health challenge for adolescents and young adults with severe obesity, including those who have undergone metabolic and bariatric surgery. Upstream identification, monitoring, and intervention to prevent smoking uptake and escalation in youth with obesity across settings should be prioritized.

Gender Differences in Factors Associated with Clinically Meaningful Weight Loss among Adults Who Were Overweight or Obese: A Population-Based Cohort Study

OBJECTIVES

The impact of heterogeneity on gender difference for achieving clinically meaningful weight loss (cmWL) remains unclear. Here, we explored the potential gender differences in factors associated with cmWL.

METHODS

A total of 60,668 participants with body mass index (BMI) ≥25 kg/m2 at study entry and available BMI values at follow-up were included in this study. cmWL was defined as a weight loss of ≥5% from the study entry to follow-up. The associations of social-demographic factors, personal history of chronic diseases, lifestyle behaviors, and history of BMI with cmWL were evaluated using logistic regression models.

RESULTS

During a median follow-up of 9.13 years, 26.6% of the participants had a cmWL (30.8% for females vs. 23.1% in males; p < 0.001). Participants with older age, obesity at study entry, being more physical activity compared to 10 years ago, being relapsed smokers or consistent current smokers, having a history of chronic diseases (i.e., diabetes, osteoporosis, and stroke), cancer diagnosis during the study period, and more than 10-year follow-up were more likely to achieve cmWL in both males and females (all p < 0.05). The new smoking quitters and participants with less active in physical activity compared to 10 years ago were less likely to achieve cmWL in both males and females (all p < 0.05). Specifically, males with a history of emphysema were more likely to reach cmWL, and for females, those being overweight at 20 years old and current drinkers were more likely to reach cmWL (p < 0.05). Sensitivity analyses demonstrated similar results.

CONCLUSION

Age, BMI status, physical activity, smoking status, family income, and health status were independent factors in males and females for weight management. However, further well-designed prospective studies are warranted to confirm our findings.

Cardiometabolic Morbidity and Mortality with Smoking Cessation, Review of Recommendations for People with Diabetes and Obesity

PURPOSE OF REVIEW

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.

RECENT FINDINGS

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'.

Examination of different definitions of snacking frequency and associations with weight status among U.S. adults

Snacks, while widely consumed in the United States (U.S.), do not have a standard definition, complicating research to understand associations, if any, with weight status. Therefore, the purpose of this study was to examine the association between snacking frequency and weight status using various snacking definitions that exist in the scientific literature among U.S. adults (NHANES 2013–2016; ≥20y n = 9,711). Four event-based snacking definitions were operationalized including participant-defined snacks, eating events outside of meals, and operationally defined snacks based on absolute thresholds of energy consumed (>50 kcal). Weight status was examined using body mass index (BMI), waist circumference, and sagittal abdominal diameter risk. Logistic regression models examined snacking frequency and associations with weight status. Outcomes varied by the definition of a snack employed, but the majority of findings were null. Mean energy from snacks was significantly higher among women with obesity compared to women with normal weight when a snack was defined as any event outside of a typical mealtime (i.e. other than breakfast, lunch, dinner, super, brunch), regardless of whether or not it contributed ≥50 kcal. Further investigation into ingestive behaviors that may influence the relationship between snacking frequency and weight status is needed.

Behavioural and psychosocial factors associated with 5-year weight trajectories within the PORTAL Overweight/Obesity Cohort

Objective

The purpose of this study was to model weight trajectories over a 5‐year time period (2012–2016) and their association with behavioural and psychosocial characteristics and health care–related experiences using data from the Patient Outcomes Research to Advance Learning (PORTAL) overweight/obesity cohort.

Methods

Weight trajectories for each eligible patient in the PORTAL overweight/obesity cohort (n = 2864) were identified first using growth modelling; trajectories were then grouped using a hierarchical cluster analysis. Weight trajectory clusters that emerged were compared on demographics, and predictors of cluster membership were examined. Clusters were also compared on responses to a survey assessing health behaviours, quality of life, and health care experience completed in 2015 by 49% of the total sample (n = 1391).

Results

Seven distinct weight trajectory clusters were identified: (a) significant weight loss then maintenance; (b) higher stable weight; (c) moderate stable weight; (d) steady weight loss then relapse; (e) weight gain then weight loss; (f) steady weight gain then maintenance; and (g) lower stable weight. Age, sex, race/ethnicity, and body mass index at baseline predicted patient's weight trajectory (P < .001). Over two thirds of patients maintained their weight over the 5‐year period. Significant weight loss then maintenance, weight gain then weight loss, and higher stable weight patients were more likely to report receiving weight counselling from their provider. Patients in the significant weight loss then maintenance and lower stable weight clusters were more likely to be physically active than the other clusters.

Conclusion

Findings suggest variability in patterns of weight change among adults with overweight or obesity who have access to health care and that these patterns differ on demographic, behavioural and psychosocial factors, and health care experience.

Iatrogenic Obesity

Obesity has been identified as a multifactorial disease with several determinants, including genetic predisposition, environmental influences, dietary patterns, and physical activity factors. Iatrogenic obesity, most commonly medication-induced weight gain, is often overlooked as a contributing factor to a patient's obesity. This article highlights medications known to cause weight gain.

Prevalence of impaired fasting glucose, type 2 diabetes and associated risk factors in undiagnosed Chinese rural population: the Henan Rural Cohort Study

OBJECTIVE

This study estimated the burden and characterised the risk factors associated with diabetes and impaired fasting glucose (IFG) in an undiagnosed rural population.

DESIGN

Data for 36 960 participants from the Henan Rural Cohort baseline with undiagnosed diabetes were analysed. X2 test and multivariate logistic regression analyses were performed to test for association between risk factors and diabetes and IFG.

RESULTS

Women constituted 60.30% of the study participants, mean age of participants was 55.32±12.18 years, risk factors for diabetes and IFG were prevalent (75% dyslipidaemia, 57% overweight/obese, 50% central obesity and 18% metabolic syndrome). The prevalence of diabetes and IFG was 4.19% and 7.22%, respectively. Having a metabolic syndrome (adjusted OR (aOR) 4.7, 95% CI 4.27 to 5.33), dyslipidaemia (aOR 2.76, 95% CI 2.31 to 3.21), centrally obese (aOR 2.38, 95% CI 2.11 to 2.70), being overweight/obese (aOR 1.66, 95% CI 1.45 to 1.79) and a family history of diabetes (aOR 1.50, 95% CI 1.15 to 1.92) were associated with diabetes. These factors were also associated with IFG. Intake of high salt diet (aOR 1.16, 95% CI 1.02 to 1.32) and smoking (aOR 1.22, 95% CI 1.02 to 1.47; significant in men) were also associated with diabetes. Engaging in moderate physical activity (aOR 0.94, 95% CI 0.89 to 0.98) was noted to be negatively associated with diabetes.

CONCLUSION

Diabetes and IFG remain prevalent in Chinese population with obesity and dyslipidaemia being some of the most significant predictors. Regular physical activity and consumption of fruits and vegetables may be beneficial in keeping blood glucose level low.

TRIAL REGISTRATION NUMBER

ChiCTR-OOC-15006699.

Tobacco Smoking, Eating Behaviors, and Body Weight: A Review

Purpose of review

This narrative review provides an overview of the relationships among tobacco smoking, eating behaviors, and body weight. The aims are to (1) examine the concurrent and longitudinal associations between tobacco smoking and body weight, (2) describe potential mechanisms underlying the relationships between smoking and body weight, with a focus on mechanisms related to eating behaviors and appetite, and (3) discuss management of concomitant tobacco smoking and obesity.

Recent findings

Adolescents who smoke tobacco tend to have body mass indexes (BMI) the same as or higher than nonsmokers. However, adult tobacco smokers tend to have lower BMIs and unhealthier diets relative to nonsmokers. Smoking cessation is associated with a mean body weight gain of 4.67 kg after 12 months of abstinence, though there is substantial variability. An emerging literature suggests that metabolic factors known to regulate food intake (e.g., ghrelin, leptin) may also play an important role in smoking-related behaviors. While the neural mechanisms underlying tobacco smoking-induced weight gain remain unclear, brain imaging studies indicate that smoking and eating cues overlap in several brain regions associated with learning, memory, motivation and reward. Behavioral and pharmacological treatments have shown short-term effects in limiting post-cessation weight gain; however, their longer-term efficacy is limited.

Summary

Further studies are needed to identify the exact mechanisms underlying smoking, eating behaviors, and body weight. Moreover, effective treatment options are needed to prevent long-term weight gain during smoking abstinence.

Predictive utility of subtyping women smokers on depression, eating, and weight-related symptoms

OBJECTIVE

Smoking and overweight or obesity are preventable causes of disease and death. Women are reluctant to quit smoking because of concerns about postcessation weight gain, underscoring the need to elucidate patterns of weight concerns and associated psychosocial factors that may affect smoking cessation outcomes. The present study aimed to subtype women smokers based on psychosocial and behavioral factors associated with smoking and weight, and examine the utility of these subtypes to predict abstinence and postcessation weight gain.

METHOD

Weight-concerned women (N = 343) were randomized to 1 of 2 smoking cessation counseling adjuncts and 1 of 2 cessation medication conditions. At baseline, women were weighed and completed measures of depression, weight or appearance concerns, and eating behaviors. At 3-, 6-, and 12-months after the target quit date, women were weighed and completed self-report and biochemical smoking assessments.

RESULTS

Latent profile (LP) analyses supported a 3-profile model. The groups had typical (53%, LP1), minimal (33%, LP2), and high (14%, LP3) levels of depressive symptoms and weight concerns. At 12-months posttarget quit date, women in LP3 were more likely to relapse than women in LP1 (odds ratio, OR = 2.93). Among abstinent women, those in LP2 and LP3 gained more postcessation weight than those in LP1.

CONCLUSIONS

Heterogeneity in symptoms of depression, weight or appearance concerns, and eating behaviors was captured by three groups of women smokers, with unique risks for relapse and postcessation weight gain. The distinct profiles identified may help personalize the delivery of care for smoking cessation and, ultimately, reduce disease risk. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Does everyone who quit smoking gain weight? A real-world prospective cohort study

Objective:

To evaluate weight changes after 12 months of biochemically confirmed smoking abstinence, comparing patients who lost weight or maintained their baseline weight with those who gained weight.

Methods:

This was a real-world prospective cohort study conducted at the Outpatient Smoking Cessation Clinic of São Lucas Hospital, in the city of Porto Alegre, Brazil, between 2010 and 2016. The patients evaluated received intensive smoking cessation counseling, focused especially on weight issues, together with pharmacotherapy, and were followed for 12 months. The baseline and final weights were measured. Continuous abstinence was confirmed by determining the concentration of exhaled carbon monoxide (eCO).

Results:

Of a total of 348 patients evaluated, 161 (46.2%) achieved continuous abstinence (eCO < 10 ppm) over the 12-month follow-up period. Of those 161 patients, 104 (64.6%) maintained their initial weight or had a weight change of no more than 5% in relation to their baseline weight, whereas the remaining 57 (35.4%) had a weight gain of more than 5%, 18 of those patients showing a > 10% increase over their baseline weight. The number needed to harm (i.e., the number of patients required in order to detect one patient with a weight increase) was calculated to be 3.6 (95% CI: 2.8-5.4).

Conclusions:

Weight gain is not necessarily associated with smoking cessation, and smokers who are motivated to quit should be informed of that fact. This information could also be useful for addressing smokers who are still undecided because of possibility of weight gain.

Current Smoking: An Independent Predictor of Elevated A1C in Persons With Type 2 Diabetes

Purpose

The purpose of this study is to examine the association of current smoking as one of several potential predictors of elevated A1C in adults with type 2 diabetes (T2D).

Methods

Using a cross-sectional design, baseline data (N = 282) were analyzed from a randomized clinical trial examining treatment of obstructive sleep apnea in persons with T2D. Sociodemographic, clinical, and behavioral data were collected using questionnaires and physical examinations. Physical activity (mean daily steps walked) was measured with the BodyMedia Armband. Participants were asked if they never smoked, had previously smoked, or currently smoke. The sample distributions of demographic and clinical characteristics were examined using descriptive statistics. Continuous variables were described using means and standard deviations; categorical variables were described as numbers and percentages. Multiple linear regression analysis with backward selection was conducted to develop a parsimonious predictive model for the dependent variable A1C.

Results

Participants were generally middle-aged and, on average, obese with suboptimal blood glucose control; almost 1 of every 5 participants currently smoked. After controlling for age, race, education, financial difficulty, diabetes education, physical activity, and diabetes knowledge, 4 variables were found in the final model to be independently associated with higher A1C: (1) current smoking status, (2) younger age, (3) longer diabetes duration, and (4) higher diabetes-related distress.

Conclusions

The study found that not only is smoking prevalent among persons with T2D with self-reported sleep problems but smoking is also an independent predictor of elevated A1C. The results highlight the vital role diabetes educators have in promoting risk reduction through education and support for smoking cessation.

Smoking and weight loss among smokers with overweight and obesity in Look AHEAD

Smoking cessation is associated with increases in body weight, but little is known about the relationship between participation in a weight loss intervention and smoking.

OBJECTIVE

To determine whether (a) weight losses at 1 year differ as a function of baseline smoking status (never smoker, current smoker, ex-smoker) and (b) participation in a weight loss intervention affects smoking behavior.

METHOD

This analysis addressed these questions using the publicly available database from Look AHEAD, a randomized trial comparing intensive lifestyle intervention (ILI) and diabetes support and education (DSE; control condition) among individuals with overweight/obesity and Type 2 diabetes, and included 4,387 participants who had self-reported smoking and objective weight measures available at baseline and at 1 year.

RESULTS

Although participants in ILI lost a significantly greater percentage of weight than those in DSE at 1 year (ILI, M = -8.8%, SD = 6.8; DSE, M = -0.7%, SD = 4.7), there were no differences in weight loss outcomes between never smokers (n = 2,297), ex-smokers (n = 2,115), and current smokers (n = 188) within either condition. Participation in ILI was not associated with compensatory smoking or likelihood of quitting smoking or relapsing.

CONCLUSIONS

Smokers in a weight loss intervention had reductions in weight that were comparable to individuals who did not smoke without any evidence of compensatory smoking to manage eating and appetite. Smokers with obesity should be encouraged to pursue weight loss without concerns regarding the impact on smoking behavior. (PsycINFO Database Record

Factors associated with gestational weight gain: a cross-sectional survey

BACKGROUND

The aim of this study was to describe the dietary patterns in pregnant women and determine the association between diet factors, pre-pregnancy body mass index, socio-demographic characteristics and gestational weight gain.

METHODS

The analysis was conducted on a group of 458 women. Cut-off values of gestational weight gain adequacy were based on recommendations published by the US Institute of Medicine and were body mass index-specific. Logistic regression analysis was used to assess the risk of the occurrence of inadequate or excessive gestational weight gain. Dietary patterns were identified by factor analysis.

RESULTS

Three dietary patterns characteristic of pregnant women in Poland were identified: 'unhealthy', 'varied' and 'prudent'. The factor associated with increased risk of inadequate gestational weight gain was being underweight pre-pregnancy (OR = 2.61; p = 0.018). The factor associated with increased risk of excessive weight gain were being overweight or obese pre-pregnancy (OR = 7.00; p = 0.031) and quitting smoking (OR = 7.32; p = 0.019). The risk of excessive weight gain was decreased by being underweight pre-pregnancy (OR = 0.20; p = 0.041), being in the third or subsequent pregnancy compared to being in the first (OR = 0.37; p = 0.018), and having a high adherence to a prudent dietary pattern (OR = 0.47; p = 0.033).

CONCLUSIONS

Women who were overweight or obese pre-pregnancy and those who quit smoking at the beginning of pregnancy should be provided with dietary guidance to prevent excessive gestational weight gain.

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.

Ten-year weight gain is associated with elevated fasting insulin levels and precedes glucose elevation

BACKGROUND

Numerous studies have examined the relationship between endogenous insulin and weight change with mixed results. This study examined the relationship between fasting insulin levels, insulin resistance (IR), and 10-year weight change by glycaemic stage.

METHODS

Using data from the US National Health and Nutrition Examination Survey 2011-2014, 3840 participants were divided into 6 groups based on fasting glucose and fasting insulin levels. Fasting insulin concentrations were dichotomized into <25th percentile (normal) and ≥25th percentile (elevated). Ten-year weight change associated with fasting insulin was assessed by glycaemic stage.

RESULTS

Average weight change over a 10-year period was higher in individuals with elevated insulin levels compared to the first quartile (1.40 lbs. vs 11.12 lbs, P < .0001). Across all groups, a 1 μU increase in fasting insulin levels resulted in a 0.52-pound increase in weight (P < .0001). Similarly, an increase in HOMA-IR was associated with increase in weight (1.32 lbs per IR unit, P < .0001). Marginal increases in weight were most pronounced in the normal insulin groups compared to elevated insulin groups and diminished as glycaemic stage progressed.

CONCLUSIONS

Elevated fasting insulin level was positively associated with weight gain. The impact of fasting insulin and IR on weight gain preceded hyperglycaemia and diminished as glycaemic stage progressed.

More to gain: dietary energy density is related to smoking status in US adults

Background

Given the current prevalence of both cigarette use and obesity in the United States, identification of dietary patterns that reduce mortality risk are important public health priorities. The objective of the present study was to evaluate the correlation between cigarette use and dietary energy density, a marker for diet quality, in a population of current smokers, former smokers, and never smokers.

Methods

Data from a nationally representative sample of 5293 adults who participated in the 2013–2014 National Health and Nutrition Examination Surveys (NHANES) were analyzed. Specific survey procedures were used in the analysis to account for sample weights, unequal selection probability, and clustered design when evaluating the association between dietary energy density (ED, energy per weight of food, kcal/g) and current smoking status. Never smokers reported < 100 lifetime cigarettes. Smokers were identified as individuals reporting > 100 lifetime cigarettes and current smoking status was recorded as daily, some days (nondaily), or not at all (former).

Results

A strong linear relationship was observed between smoking pattern and dietary ED in current smokers. Compared to never smokers, daily smokers and nondaily smokers have significantly higher dietary ED (1.79 vs. 2.02 and 1.88, respectively; both p < 0.05); demonstrating that any amount of current cigarette consumption is associated with poor diet. Though former smokers had a higher dietary ED than never smokers, this difference still significantly lower than that of current smokers (p = 0.002).

Conclusion

These findings suggest that smoking status is associated with poor diet quality. Former smokers had a slightly lower ED value (1.84) than current non-daily smokers (1.89) but a higher value than never smokers (1.79).

The Impact of Weight and Weight-Related Perceptions on Smoking Status Among Young Adults in a Text-Messaging Cessation Program

Introduction

Weight gain and concerns about weight can influence a smoker's ability to successfully quit, and young adults are a subgroup of smokers who are particularly concerned about the impact of quitting on their body weight. This study explored the associations between body mass index, weight perceptions, and smoking status among young adults.

Methods

The sample consisted of 4027 young adults between the ages of 18 and 29 who participated in a randomized control trial of the National Cancer Institute's SmokefreeTXT program. Multivariable logistic regression models were used to examine the associations between weight related variables and smoking status.

Results

Obese participants had a 0.72 lower odds (95% CI: 0.62, 0.85) of reporting smoking at the end of the program than participants of normal weight, and this difference persisted over time. Weight perceptions were also associated with smoking status. Those who perceived themselves to be slightly underweight/underweight were more likely to report smoking than those who reported being just about the right weight (OR: 1.53, 95% CI: 1.20, 1.95), and those who strongly disagreed that smoking cigarettes helps people keep their weight down were less likely to report smoking at the end of treatment than those who neither agreed nor disagreed with this statement (OR: 0.69, 95% CI: 0.54, 0.87).

Conclusions

Weight related factors assessed at baseline predicted smoking status at the end of treatment and through long term follow-up. Smoking cessation programs that tailor content to addresses the specific needs of weight concerned smokers may enhance effectiveness.

Implications

This study explores the association between weight related factors and smoking status among young adults, a priority population for smoking cessation efforts. This study demonstrates that both actual weight and weight perceptions (eg, perception of body weight, perception of associations between smoking and weight) are associated with smoking outcomes, and thus need to be a considered in the development of smoking cessation programs.

Could Vaping be a New Weapon in the Battle of the Bulge?

IMPLICATIONS

Obesity is set to overtake tobacco smoking in many countries as the primary cause of several high-cost diseases. Tobacco smoking mitigates weight gain through nicotine's effect on the brain and metabolism. Smoking, however, is associated with many illnesses and premature death and appropriately has been discouraged leading to declining prevalence rates. This article explores the emerging perception that vaping electronic cigarettes with nicotine and flavors could deliver similar appetite and weight control effects as smoking. The potential to reduce risks associated with excess weight deserves exploration. An initial research agenda is suggested.

Targeting Mediators of Smoking Persistence with Intranasal Insulin

Rapid-acting, non-irritating nasal treatment options for smoking cessation pharmacotherapy are lacking. The halt in development is due, in part, to difficulty in delivering compounds across the blood brain barrier. Recently, in both human and animal models, insulin was shown to be capable of being transported to the cerebrospinal fluid and various brain regions via the “nose-to-brain” pathway, which bypasses the blood brain barrier, but is not free of its own unique, though different from blood brain barrier, challenges. This review will first evaluate and critique pharmacokinetic and pharmacodynamic evidence of intranasal insulin (i.e., nose-to-brain) delivery. As intranasal insulin has been shown in clinical trials to be effective in reducing nicotine cravings, in the remainder of the review, hypothesis-generating literature for additional mediators (i.e., other than the already shown nicotine craving) of smoking persistence will be reviewed. In particular, weight gain, impulsive behavior, and anhedonia have been shown to contribute to the inability to quit smoking. For each of these, after reviewing how the mediator promotes smoking, intranasal insulin literature from animal and clinical models will be critiqued in assessing whether a hypothesis may be generated that intranasal insulin may alleviate it, thereby potentially contributing to a successful smoking cessation outcome.

Weight change in older adults and mortality: the Multiethnic Cohort Study

Objective

To investigate the association between weight change in older adults and mortality in a multiethnic population.

Methods

We performed a prospective analysis using data on weight change between the baseline (1993-1996) and the 10-year follow-up (2003-2007) surveys in relation to subsequent mortality among 63,040 participants in the Multiethnic Cohort Study in Hawaii and California. The participants were African American, Native Hawaiian, Japanese American, Latino, and white, aged 45-75 years at baseline, and did not report heart disease or cancer at either survey.

Results

During an average of 7.3 years of follow-up after the 10-year survey, 6,623 deaths were identified. Compared with individuals whose weight remained stable (±2.5 kg), those who lost weight and those with the highest weight gain (>10 kg) were at increased risk of all-cause mortality, with the risks greater for the weight-loss (hazard ratios [HR], 2.86; 95% confidence interval [95% CI], 2.62-3.11 for >10 kg) than the weight-gain group (HR, 1.25; 95% CI, 1.11-1.41 for >10 kg), thus resulting in a reverse J-shaped curve. Japanese Americans and Latinos had stronger associations of weight loss >10 kg with mortality than did African Americans, Native Hawaiians, and whites. The increase in risk with weight gain >10 kg was greater for older (≥55 years at baseline) than younger individuals while the increase in mortality associated with weight loss was greater for the normal weight (<25 kg/m² at baseline) participants and never smokers, compared with overweight/obese persons and current smokers, respectively.

Conclusions

Our findings confirm the association between weight change and a higher mortality in a healthy, multiethnic population, with higher risks for weight loss than weight gain. Based on these observations, public health recommendation should focus on the prevention of weight loss, as well as weight stability within the non-obese range, for middle aged and older adults.

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.

Self-administered nicotine differentially impacts body weight gain in obesity-prone and obesity-resistant rats

Obesity and tobacco smoking represent the largest challenges to public health, but the causal relationship between nicotine and obesity is poorly understood. Nicotine suppresses body weight gain, a factor impacting smoking initiation and the failure to quit, particularly among obese smokers. The impact of nicotine on body weight regulation in obesity-prone and obesity-resistant populations consuming densely caloric diets is unknown. In the current experiment, body weight gain of adult male rats maintained on a high energy diet (31.8% kcal from fat) distributed into obesity-prone (OP), obesity-resistant (OR) and an intermediate group, which was placed on standard rodent chow (Chow). These rats were surgically implanted with intravenous catheters and allowed to self-administer nicotine (0 or 60μg/kg/infusion, a standard self-administration dose) in 1-h sessions for 20 consecutive days. Self-administered nicotine significantly suppressed body weight gain but not food intake in OP and Chow rats. Self-administered nicotine had no effect on body weight gain in OR rats. These data suggest that: 1) OR rats are also resistant to nicotine-induced suppression of body weight gain; and 2) nicotine may reduce levels of obesity in a subset of smokers prone to obesity.

Obesity Might Be a Predictor of Weight Reduction after Smoking Cessation

BACKGROUND AND OBJECTIVES

Approximately one in five ex-smokers reduces or maintains weight after smoking cessation but little is known about who succeeds to avoid weight gain. The purpose of this study was to identify predictors of weight reduction after long-term smoking cessation in a general population.

METHODS

Data was obtained from two Danish population-based cohorts (the Inter99 and the Helbred2006 study). Anthropometric measurements were performed by trained research staff. Out of 3.577 daily smokers at baseline 317 participants had quit smoking at the five-year follow-up for at least one year. Multiple logistic regression analysis was performed to determine predictors of weight reduction.

RESULTS

Thirteen percent reduced weight by at least 1 kg and 4% maintained their weight. Quitters with obesity had more than seven times higher odds than normal weight quitters to lose weight (OR 7.13 (95% CI 2.76-19.71)), and they had the largest median weight loss of 4.45 kg. The only other significant predictor of weight reduction was low tobacco consumption at baseline.

CONCLUSIONS

Predictors of weight reduction after smoking cessation were high body mass index and low tobacco consumption at baseline. This study might motivate smokers with obesity to quit smoking and health professionals to give them support.