Smoking relapse and weight gain prevention program for postmenopausal weight-concerned women: A pilot study

Impact of Weight Concern on Post-Cessation Weight Management, Smoking Cessation, and Program Engagement

PURPOSE

Weight concern is a barrier to smoking cessation. We examined the impact of weight concern on post-cessation weight gain, abstinence and program engagement.

DESIGN

Randomized-controlled trial.

SETTING

Telephone-based and group-based intervention sessions.

SUBJECTS

305 participants were randomized and analyzed.

INTERVENTION

Participants were randomized to receive a self-guided intervention, a weight loss intervention, or a weight stability intervention prior to all receiving the same smoking cessation intervention.

MEASURES

Level of weight concern on three measures, point-prevalence abstinence, weight change, and session attendance at 12 months.

ANALYSIS

Continuous and discrete outcomes were compared between weight-concerned and non-weight-concerned participants using two-sample t-tests and chi-square tests respectively.

RESULTS

There were no significant differences in weight change (range: +1.77, -1.91 kg) when comparing weight-concerned and non-weight-concerned participants. Point-prevalence abstinence ranged from 36% to 64%, with no differences by condition based on level of weight concern. There were no significant differences in session attendance by weight concern (Weight sessions: 50-70%, Smoking cessation sessions: 41-56%, Booster sessions: 28-45%). Weight concern, on all measures, significantly decreased between screening and 2 months (after the weight management intervention), for most of the comparisons made overall and by condition.

CONCLUSION

It may not be necessary to screen for weight concerns in smoking cessation and/or post-cessation weight management programs, as the trial interventions were beneficial regardless of weight concern.

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.

Patterns of smoking and menopause-specific quality of life: smoking duration matters more

Evidence about the association of quantity of cigarettes smoked and duration of smoking with quality of life in menopause is sparse. The purpose of this study was to examine the association between smoking patterns and menopause-specific quality of life. This cross-sectional study included 513 consecutive midlife women at two primary health care centers in Belgrade, Serbia. Collection of data was carried out from February 2014 to January 2015, using three questionnaires: socio-epidemiologic questionnaire, Menopause-specific Quality of Life questionnaire (MENQOL) and Beck's Depression Inventory (BDI). Women reported their smoking status (smoker, former smoker, non-smoker), the length of time spent smoking and quantity of cigarettes smoked per day. There was no difference in proportions of ever smokers compared to never smokers. However, there were more women who were current nonsmokers than current smokers. A linear regression model, adjusted for residency district, relationship status, educational level, employment, drinking alcohol, having exercise, age and BDI, showed that longer duration of smoking, but not number of cigarettes smoked per day, was associated with worse Physical domain and total MENQOL score. Receiver Operating Characteristic analysis showed that menopausal symptoms as measured by total MENQOL score were significantly less bothersome for women who smoked less than 10 years and significantly more intense in women who smoked 21 to 30 years. Midlife women should be encouraged to quit smoking as soon as possible, preferably before menopause. Strategies to prevent and quit smoking should be prioritized at all levels of health care delivery for women.Supplemental data for this article is available online at.

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.

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.

An empirical investigation of the impact of smoking on body weight using an endogenous treatment effects model approach: the role of food consumption patterns

BACKGROUND

This study explored the influence of cigarette smoking and food consumption patterns on BMI after adjusting for various socio-demographic characteristics. Since weight-based stereotypes may have an impact on smoking behaviour and both obesity and smoking have been associated with detrimental health effects, an interdependency between them is quite possible.

METHODS

Cross-sectional data were collected via a formal standardized questionnaire administered in personal interviews and two additional self-completion questionnaires from a random sample of 3471 German adults. The empirical framework considered potential endogeneity between smoking and body weight by employing an endogenous treatment effects model with an ordered outcome. The estimations derived from the endogenous treatment effects approach were also compared to the univariate ordered probit model results.

RESULTS

Our findings showed that ignoring potential endogeneity may affect both the statistical significance of the smoking estimate and the direction of the influence of smoking on BMI. Smoking was positively associated with BMI in both male (β = 1.236, p < 0.01) and female (β = 0.634, p < 0.10) participants. Smokers presented a 23.1% higher risk of obesity and a 24.3% lower likelihood of being within a healthy weight range. Male smokers also appeared to have a considerably augmented probability of being obese compared to their female counterparts (23.6% vs 15.1%). The relationship between smoking and BMI may be attributed to dietary practices, since smoking was correlated with poor dietary habits characterized by the frequent intake of more energy-dense foods (meat products and white-toasted bread) and less frequent consumption of healthy food items, such as whole-grain bread, vegetables and fruits. Concerning the impact of eating habits on body weight, frequent consumption of meat products and confectionery was found to have a direct association with BMI in both genders. Furthermore, white-toasted bread consumption was negatively linked with body weight in males (β = - 0.337, p < 0.01).

CONCLUSIONS

Our findings raised questions about the general belief that smoking is an effective weight control tool. Health interventions should be oriented toward a simultaneous decrease in smoking and obesity, since both behaviours seem to be interdependent. Nutrition programmes should also be designed according to the characteristics of different target groups in order to promote a healthy lifestyle.

Weight Concerns Associated With Delay in Quit Date But Not Treatment Outcomes: A Czech Republic Experience

Background

Weight concerns are prevalent in smokers and may reduce the success rate of quitting. This concept has been primarily studied on US populations and it is unknown how weight concerns may differ cross-culturally. This study examined the role of weight concern in European smokers wishing to stop smoking.

Methods

A sample of 593 smokers (299 men and 294 women, mean age 38 years) utilizing the Centre for Tobacco-Dependent in Prague, Czech Republic, between 2010 and 2013 were studied. Weight concerns were assessed at baseline prior to treatment by evidence-based stop smoking methods. Abstinence was evaluated at 12 months post baseline.

Results

Approximately 34% of all patients (204/593) were classified as weight concerned (by indicating on the Weight Concern Scale that they would return to smoking after any weight gain) at the time they sought treatment. Among all men, 19.4% (58/299) were weight concerned and among all women, 49.7% (146/294) were weight concerned. Among females, weight-concerned smokers were of similar weight, but younger (p < .001), and had been smoking cigarettes for fewer years (p = .002) compared with those without weight concerns, whereas the male weight-concerned smokers were significantly (p = .030) heavier than those without weight concerns. Although the presence of weight concern was associated with a delay in setting a quit date (log-rank test p = .019), it was not associated with abstinence at one year.

Conclusion

The quit success rate of weight-concerned smokers in Czech Republic did not differ from those without weight concern when utilizing an individualized smoking cessation treatment program. Individually tailored tobacco dependence treatment could help to prevent weight concern from affecting successful quitting.

Implications

This study adds the new cross-cultural aspect of post-cessation weight concern. Weight concern has been studied primarily on US populations and our sample consists of European sample of smokers. Additionally, we have found that the presence of weight concern lead to delay in setting a quit date, but the success rate of those weight concerned did not differ from those without weight concern. Thus, it is possible, that this individualized evidence-based tobacco treatment program was able to prevent weight concern impact towards successful quitting.

Development and evaluation of the See Me Smoke-Free multi-behavioral mHealth app for women smokers

Women face particular challenges when quitting smoking, especially those with weight concerns. A multi-behavioral smoking cessation intervention addressing these concerns and incorporating guided imagery may assist women to engage in healthy lifestyle behaviors. An mHealth app can easily disseminate such an intervention. The goals of this pilot study were to develop and test the feasibility and potential of the See Me Smoke-Free™ mHealth app to address smoking, diet, and physical activity among women smokers. We used pragmatic, direct-to-consumer methods to develop and test program content, functionality, and the user interface and conduct a pre-/post-test, 90-day pilot study. We enrolled 151 participants. Attrition was 52%, leaving 73 participants. At 90 days, 47% of participants reported 7-day abstinence and significant increases in physical activity and fruit consumption. Recruitment methods worked well, but similar to other mHealth studies, we experienced high attrition. This study suggests that a guided imagery mHealth app has the potential to address multiple behaviors. Future research should consider different methods to improve retention and assess efficacy.

Group behaviour therapy programmes for smoking cessation

BACKGROUND

Group therapy offers individuals the opportunity to learn behavioural techniques for smoking cessation, and to provide each other with mutual support.

OBJECTIVES

To determine the effect of group-delivered behavioural interventions in achieving long-term smoking cessation.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialized Register, using the terms 'behavior therapy', 'cognitive therapy', 'psychotherapy' or 'group therapy', in May 2016.

SELECTION CRITERIA

Randomized trials that compared group therapy with self-help, individual counselling, another intervention or no intervention (including usual care or a waiting-list control). We also considered trials that compared more than one group programme. We included those trials with a minimum of two group meetings, and follow-up of smoking status at least six months after the start of the programme. We excluded trials in which group therapy was provided to both active therapy and placebo arms of trials of pharmacotherapies, unless they had a factorial design.

DATA COLLECTION AND ANALYSIS

Two review authors extracted data in duplicate on the participants, the interventions provided to the groups and the controls, including programme length, intensity and main components, the outcome measures, method of randomization, and completeness of follow-up. The main outcome measure was abstinence from smoking after at least six months follow-up in participants smoking at baseline. We used the most rigorous definition of abstinence in each trial, and biochemically-validated rates where available. We analysed participants lost to follow-up as continuing smokers. We expressed effects as a risk ratio for cessation. Where possible, we performed meta-analysis using a fixed-effect (Mantel-Haenszel) model. We assessed the quality of evidence within each study and comparison, using the Cochrane 'Risk of bias' tool and GRADE criteria.

MAIN RESULTS

Sixty-six trials met our inclusion criteria for one or more of the comparisons in the review. Thirteen trials compared a group programme with a self-help programme; there was an increase in cessation with the use of a group programme (N = 4395, risk ratio (RR) 1.88, 95% confidence interval (CI) 1.52 to 2.33, I² = 0%). We judged the GRADE quality of evidence to be moderate, downgraded due to there being few studies at low risk of bias. Fourteen trials compared a group programme with brief support from a health care provider. There was a small increase in cessation (N = 7286, RR 1.22, 95% CI 1.03 to 1.43, I² = 59%). We judged the GRADE quality of evidence to be low, downgraded due to inconsistency in addition to risk of bias. There was also low quality evidence of benefit of a group programme compared to no-intervention controls, (9 trials, N = 1098, RR 2.60, 95% CI 1.80 to 3.76 I² = 55%). We did not detect evidence that group therapy was more effective than a similar intensity of individual counselling (6 trials, N = 980, RR 0.99, 95% CI 0.76 to 1.28, I² = 9%). Programmes which included components for increasing cognitive and behavioural skills were not shown to be more effective than same-length or shorter programmes without these components.

AUTHORS' CONCLUSIONS

Group therapy is better for helping people stop smoking than self-help, and other less intensive interventions. There is not enough evidence to evaluate whether groups are more effective, or cost-effective, than intensive individual counselling. There is not enough evidence to support the use of particular psychological components in a programme beyond the support and skills training normally included.

Severity of Menopausal Symptoms and Nicotine Dependence amongst Postmenopausal Women Smokers

Rationale: Cigarette smoking has antiestrogenic properties, which may worsen the symptoms and health risks associated with menopause.

Objectives: In the present study, it was hypothesised that menopausal symptoms would improve with smoking abstinence.

Methods: Postmenopausal smokers (n = 76) were assessed with the Kupperman Index (KI) of menopausal symptoms and smoking-related indices of nicotine dependence, cotinine level, cigarettes per day (CPD), and number of years smoking.

Results: Participants were 67% Caucasian, 33% African-American, 52.3(SD = 7.8) mean years of age, follicle stimulating hormone (FSH) level, m = 42.6(SD = 25.7) mlU/ml, mean number of months since last menses was 145.1(SD = 118.9), and mean body mass index (BMI) was 27.4(SD = 6.2). Mean cigarettes smoked per day (CPD) was 20.3(SD = 11.5), for m = 29.4(SD = 10.7) years; m = 6.4(SD = 2.1) Fagerström Test for Nicotine Dependence (FTND), m = 23.8(SD = 13.0) ppm carbon monoxide, and m = 19.7(SD = 12.5) KI total score. Most participants (78.9%) were currently taking hormone therapy (HT). Hierarchical linear regression analyses revealed that FTND (β = 0.48, p = 0.001) and cotinine level (β = −0.27, p = 0.02) predicted KI scores at baseline. Amongst participants (n = 65) who achieved abstinence for 2 weeks, number of years smoking predicted KI scores (β = 0.38, p = 0.01). At 8 weeks postcessation, CPD significantly predicted of KI scores (β = −0.74), p = 0.04).

Conclusions: With abstinence from smoking, the overall severity of menopausal symptoms decreased and shared variance with different smoking-related variables. The temporal and cessation-related symptom course identified in this study will be important in informing cessation interventions with this population of smokers.