A Pilot Randomized Controlled Trial of Distress Tolerance Treatment for Weight Concern in Smoking Cessation Among Women

Body weight change during a smoking cessation intervention for individuals with overweight or obesity

INTRODUCTION

A more comprehensive understanding of the factors regarding weight control in individuals with overweight or obesity after quitting smoking is needed. The study aimed to analyze the changes of in-treatment variables during a smoking cessation intervention and examine their impact on weight.

METHODS

A total of 120 individuals who smoke with overweight or obesity (MBMI = 31.75 ± 4.31; 54.16 % female) participated in a cognitive-behavioral therapy for smoking cessation and weight control or the same treatment plus contingency management. Weight, smoking variables (cotinine and continuous abstinence), eating behaviors (appetite, grazing), exercise, and sleep were assessed weekly throughout the treatment.

RESULTS

More participants gained weight over time with reduced nicotine use or abstinence. There was a tendency during treatment to increase appetite and exercise time, while grazing episodes and sleeping hours remained stable. Higher baseline weight (p < .001), greater cotinine reduction (p = .021) and time (p = .009) were associated with greater weight gain, while more hours of exercise (p = .003), no appetite changes (p = .003) and diminished appetite (p < .001) were associated with less gain over the treatment. Both treatment conditions showed similar results in all in-treatment variables.

DISCUSSION

Individuals with overweight and obesity with higher baseline weight and higher baseline cotinine levels during smoking cessation interventions may require special attention to improve weight outcomes. Exercise and appetite regulation may be useful for mitigating weight gain in smoking cessation interventions for individuals with overweight or obesity.

Effectiveness of including weight management in smoking cessation treatments: A meta-analysis of behavioral interventions

INTRODUCTION

The potential of weight gain after smoking cessation reduces the incentive to quit. This meta-analysis examines the efficacy of behavioral interventions for smoking cessation that also address post-cessation weight gain.

METHODS

Medline, Web of Science, PsycINFO, and the Cochrane Central Register of Controlled Trials were searched for randomized controlled trials on behavioral treatments targeting both health outcomes. Six separate meta-analyses were undertaken to assess treatment efficacy on smoking abstinence and weight outcomes at end of treatment (EOT), short-term, and long-term follow-up. Individual and treatment moderators were examined as well as methodological quality and publication bias of studies.

RESULTS

A total of 28 studies were included in the meta-analysis. There was a statistically significant positive impact of treatments addressing both targets on smoking outcomes at EOT (RR = 1.279, 95% CI: 1.096, 1.492, p = .002), but not at follow-ups. Age impacted on EOT abstinence rates Q (1) = 4.960, p = .026) while increasing the number of sessions significantly improved EOT abstinence rates (p = .020). There was no statistically significant impact of these treatments on weight at EOT (Hedges' g = -0.015, 95% CI: -.164, 0.135, p = .849) or follow-ups (short term: Hedges' g = 0.055, 95% CI: -0.060, 0.170, p = .347; long term: Hedges' g = -0.320, 95% CI: -.965, 0.325, p = .331). There were minimal impacts of publication bias, mostly related to sample size, meaning studies including small sample sizes revealed larger effect sizes on abstinence at EOT.

DISCUSSION

Addressing post-cessation weight management in treatments for smoking cessation significantly enhances tobacco abstinence at EOT though it was not found to have a lasting impact after treatment.

Post-Cessation Weight Gain among Smokers with Depression Predicts Smoking Relapse

Objective: Weight gain (WG) is one of the most widespread consequences of smoking cessation, although there is a great variability of post-cessation weight changes among smokers. Its approach is critical because it depicts an important barrier to trying to quit smoking and because it has been considered as a long-term predictor of relapse. Notwithstanding, little is known about post-cessation WG specifically among depressed smokers. The current study sought to: (1) describe the WG at posttreatment and follow-ups in smokers with depression, (2) examine the predictors of posttreatment WG, and (3) analyze whether post-cessation WG predicts smoking relapse at 6-month follow-up. Methods: The sample was comprised of 125 smokers with depression who achieved tobacco abstinence at posttreatment following a psychological smoking cessation intervention. Smoking abstinence was biochemically verified through carbon monoxide and urine cotinine. Multiple linear and hierarchical logistic regressions were conducted to examine predictors of WG at posttreatment and tobacco relapse at 6-month follow-up, respectively. Results: Abstinent participants gained an average of 3.55 kg at 6-month follow-up compared to 1.49 kg among participants who relapsed. Greater nicotine dependence (β = .372, p = .001) and diastolic pressure at baseline (β = .252, p = .021) predicted higher WG at end of treatment. WG at posttreatment increased the likelihood of relapse 6 months later (B = .303, OR = 1.354; 95% CI [1.006, 1.822]). Limitations: Weight concerns, disordered eating, and BMI were not recorded, and they could be related to the present findings. Conclusions: These results suggest that individuals with depression during treatment for smoking cessation should be regularly screened and offered treatment to prevent WG.

Mindfulness for smoking cessation

BACKGROUND

Mindfulness-based smoking cessation interventions may aid smoking cessation by teaching individuals to pay attention to, and work mindfully with, negative affective states, cravings, and other symptoms of nicotine withdrawal. Types of mindfulness-based interventions include mindfulness training, which involves training in meditation; acceptance and commitment therapy (ACT); distress tolerance training; and yoga.

OBJECTIVES

To assess the efficacy of mindfulness-based interventions for smoking cessation among people who smoke, and whether these interventions have an effect on mental health outcomes.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's specialised register, CENTRAL, MEDLINE, Embase, PsycINFO, and trial registries to 15 April 2021. We also employed an automated search strategy, developed as part of the Human Behaviour Change Project, using Microsoft Academic.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) and cluster-RCTs that compared a mindfulness-based intervention for smoking cessation with another smoking cessation programme or no treatment, and assessed smoking cessation at six months or longer. We excluded studies that solely recruited pregnant women.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods. We measured smoking cessation at the longest time point, using the most rigorous definition available, on an intention-to-treat basis. We calculated risk ratios (RRs) and 95% confidence intervals (CIs) for smoking cessation for each study, where possible. We grouped eligible studies according to the type of intervention and type of comparator. We carried out meta-analyses where appropriate, using Mantel-Haenszel random-effects models. We summarised mental health outcomes narratively.

MAIN RESULTS

We included 21 studies, with 8186 participants. Most recruited adults from the community, and the majority (15 studies) were conducted in the USA. We judged four of the studies to be at low risk of bias, nine at unclear risk, and eight at high risk. Mindfulness-based interventions varied considerably in design and content, as did comparators, therefore, we pooled small groups of relatively comparable studies. We did not detect a clear benefit or harm of mindfulness training interventions on quit rates compared with intensity-matched smoking cessation treatment (RR 0.99, 95% CI 0.67 to 1.46; I² = 0%; 3 studies, 542 participants; low-certainty evidence), less intensive smoking cessation treatment (RR 1.19, 95% CI 0.65 to 2.19; I² = 60%; 5 studies, 813 participants; very low-certainty evidence), or no treatment (RR 0.81, 95% CI 0.43 to 1.53; 1 study, 325 participants; low-certainty evidence). In each comparison, the 95% CI encompassed benefit (i.e. higher quit rates), harm (i.e. lower quit rates) and no difference. In one study of mindfulness-based relapse prevention, we did not detect a clear benefit or harm of the intervention over no treatment (RR 1.43, 95% CI 0.56 to 3.67; 86 participants; very low-certainty evidence). We did not detect a clear benefit or harm of ACT on quit rates compared with less intensive behavioural treatments, including nicotine replacement therapy alone (RR 1.27, 95% CI 0.53 to 3.02; 1 study, 102 participants; low-certainty evidence), brief advice (RR 1.27, 95% CI 0.59 to 2.75; 1 study, 144 participants; very low-certainty evidence), or less intensive ACT (RR 1.00, 95% CI 0.50 to 2.01; 1 study, 100 participants; low-certainty evidence). There was a high level of heterogeneity (I² = 82%) across studies comparing ACT with intensity-matched smoking cessation treatments, meaning it was not appropriate to report a pooled result. We did not detect a clear benefit or harm of distress tolerance training on quit rates compared with intensity-matched smoking cessation treatment (RR 0.87, 95% CI 0.26 to 2.98; 1 study, 69 participants; low-certainty evidence) or less intensive smoking cessation treatment (RR 1.63, 95% CI 0.33 to 8.08; 1 study, 49 participants; low-certainty evidence). We did not detect a clear benefit or harm of yoga on quit rates compared with intensity-matched smoking cessation treatment (RR 1.44, 95% CI 0.40 to 5.16; 1 study, 55 participants; very low-certainty evidence). Excluding studies at high risk of bias did not substantially alter the results, nor did using complete case data as opposed to using data from all participants randomised. Nine studies reported on changes in mental health and well-being, including depression, anxiety, perceived stress, and negative and positive affect. Variation in measures and methodological differences between studies meant we could not meta-analyse these data. One study found a greater reduction in perceived stress in participants who received a face-to-face mindfulness training programme versus an intensity-matched programme. However, the remaining eight studies found no clinically meaningful differences in mental health and well-being between participants who received mindfulness-based treatments and participants who received another treatment or no treatment (very low-certainty evidence).

AUTHORS' CONCLUSIONS

We did not detect a clear benefit of mindfulness-based smoking cessation interventions for increasing smoking quit rates or changing mental health and well-being. This was the case when compared with intensity-matched smoking cessation treatment, less intensive smoking cessation treatment, or no treatment. However, the evidence was of low and very low certainty due to risk of bias, inconsistency, and imprecision, meaning future evidence may very likely change our interpretation of the results. Further RCTs of mindfulness-based interventions for smoking cessation compared with active comparators are needed. There is also a need for more consistent reporting of mental health and well-being outcomes in studies of mindfulness-based interventions for smoking cessation.

Longitudinal Associations Between Changes in Cigarette Smoking and Alcohol Use, Eating Behavior, Perceived Stress, and Self-Rated Health in a Cohort of Low-Income Black Adults

BACKGROUND

Black adults in the U.S. experience significant health disparities related to tobacco use and obesity. Conducting observational studies of the associations between smoking and other health behaviors and indicators among Black adults may contribute to the development of tailored interventions.

PURPOSE

We examined associations between change in cigarette smoking and alcohol use, body mass index, eating behavior, perceived stress, and self-rated health in a cohort of Black adults who resided in low-income urban neighborhoods and participated in an ongoing longitudinal study.

METHODS

Interviews were conducted in 2011, 2014, and 2018; participants (N = 904) provided at least two waves of data. We fit linear and logistic mixed-effects models to evaluate how changes in smoking status from the previous wave to the subsequent wave were related to each outcome at that subsequent wave.

RESULTS

Compared to repeated smoking (smoking at previous and subsequent wave), repeated nonsmoking (nonsmoking at previous and subsequent wave) was associated with greater likelihood of recent dieting (OR = 1.59, 95% CI [1.13, 2.23], p = .007) and future intention (OR = 2.19, 95% CI [1.61, 2.98], p < .001) and self-efficacy (OR = 1.64, 95% CI [1.21, 2.23], p = .002) to eat low calorie foods, and greater odds of excellent or very good self-rated health (OR = 2.47, 95% CI [1.53, 3.99], p < .001). Transitioning from smoking to nonsmoking was associated with greater self-efficacy to eat low calorie foods (OR = 1.89, 95% CI [1.1, 3.26], p = .021), and lower perceived stress (β = -0.69, 95% CI [-1.34, -0.05], p = .036).

CONCLUSIONS

We found significant longitudinal associations between smoking behavior and eating behavior, perceived stress, and self-rated health. These findings have implications for the development of multiple behavior change programs and community-level interventions and policies.

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.

Cessation classification likelihood increases with higher expired-air carbon monoxide cutoffs: a meta-analysis

BACKGROUND

Expired-air carbon monoxide (CO) is commonly used to biochemically verify smoking status. The CO cutoff and CO monitor brand may affect the probability of classifying smokers as abstinent, thus influencing conclusions about the efficacy of cessation trials. No systematic reviews have tested this hypothesis. Therefore, we performed a meta-analysis examining whether the likelihood of smoking cessation classification varied due to CO cutoff and monitor brand.

METHODS

Eligible studies (k = 122) longitudinally assessed CO-verified cessation in adult smokers in randomized trials. Primary meta-regressions separately assessed differences in quit classification likelihood due to continuous and categorical CO cutoffs (Low, 3-4 parts per million [ppm]; [SRNT] Recommended, 5-6 ppm; Moderate, 7-8 ppm; and High, 9-10 ppm); exploratory analyses compared likelihood outcomes between monitor brands: Bedfont and Vitalograph.

RESULTS

The likelihood of quit classification increased 18% with each 1 ppm increase above the lowest cutoff (3 ppm). Odds of classification as quit significantly increased between each cutoff category and High: 261% increase from Low; 162% increase from Recommended; and 150% increase from Moderate. There were no differences in cessation classification between monitor brands.

CONCLUSIONS

As expected, higher CO cutoffs were associated with greater likelihood of cessation classification. The lack of CO monitor brand differences may have been due to model-level variance not able to be followed up in the present dataset. Researchers are advised to report outcomes using a range of cutoffs-including the recommended range (5-6 ppm)-and the CO monitor brand/model used. Using higher CO cutoffs significantly increases likelihood of quit classification, possibly artificially elevating treatment strategies.