Obesity and Cardiovascular Risk After Quitting Smoking: The Latest Evidence

Weight Loss Programs: Why Do They Fail? A Multidimensional Approach for Obesity Management

PURPOSE OF REVIEW

Despite the prevalence of weight loss programs, their success rates remain discouraging, with around half of individuals regaining lost weight within two years. The primary objective of this review is to explore the factors contributing to the failure of weight loss programs and to provide insights into effective weight management strategies.

RECENT FINDINGS

Factors contributing to the failure of weight loss programs include the impracticality of restrictive diets, potential metabolic impacts, limited focus on lifestyle changes, genetic predispositions, psychological influences, socioeconomic status, and medical conditions. A holistic approach considering these factors is crucial for safe and sustainable weight loss. Key findings indicate the importance of holistic approaches to weight management, including lifestyle modifications, medical interventions, and behavioral and psychological strategies. Effective weight loss strategies emphasize low-calorie, nutrient-rich diets, regular physical activity, and interventions tailored to individual needs. Combining multiple approaches offers the best chance of successful weight management and improved health outcomes. This review provides insights into the complexities of obesity management and the factors contributing to the failure of weight loss programs. It highlights the necessity of adopting a holistic approach that addresses dietary habits, physical activity, genetic factors, psychological well-being, and socioeconomic influences. Recommendations include implementing lifestyle modifications, medical interventions when necessary, and integrating behavioral and psychological support to achieve sustainable weight loss and mitigate the global health challenge posed by obesity.

Contingency management for smoking cessation for individuals with overweight or obesity: A randomized controlled trial

BACKGROUND

Interventions for quitting smoking and weight control among individuals with excess weight are scarce. Our study evaluated the effectiveness of cognitive behavioral therapy (CBT) plus contingency management (CM) in this population, and examined whether CM for smoking cessation improved CBT treatment outcomes at end of treatment (EOT) and at 1-, 3-, 6-, and 12-month follow-ups (FU).

METHODS

In an 8-week randomized clinical trial, 120 adults who smoke with overweight or obesity (54.16% females; MBMI = 31.75 ± 4.31) were randomly assigned to CBT for both quitting smoking and weight control (n = 60) or the same treatment plus CM for smoking cessation (n = 60). Outcome variables were compared (i.e., treatment completion, smoking abstinence, weight change and secondary outcomes).

RESULTS

At EOT, the CBT + CM group achieved 78.33% 7-day point-prevalence abstinence rates compared to 61.67% in the CBT group (p = .073), and rates declined over time (12-month FU: 18% vs 12%). Participants who attained abstinence weighed more compared to baseline at EOT (Mkg = 1.07; SD = 1.88) and over time (12-month FU: Mkg = 4.19; SD = 4.31). No differences were found between the two groups in outcome variables.

CONCLUSIONS

Both interventions were effective in promoting abstinence and reducing tobacco use over time. Combining CBT with CM for smoking cessation did not improve treatment outcomes in individuals with overweight or obesity compared to CBT only. Future studies should evaluate whether implementing CM for weight maintenance helps control post-cessation weight gain in this population.

Association of combined healthy lifestyle with general and abdominal obesity

Background

Data linking joint healthy lifestyle factors to general and abdominal obesity are scarce, in particular in the Middle East. The aim of this study was to examine the association of combined healthy lifestyle factors with general and abdominal obesity in a large population of Iranian adults.

Methods

This cross-sectional study was done on 3,172 Iranian adults aged ≥18 years. We constructed healthy lifestyle score using information on dietary intakes, physical activity, smoking status, and psychological distress. To evaluate components of healthy lifestyle, we applied a validated 106-item semi-quantitative Food Frequency Questionnaire (FFQ), General Practice Physical Activity Questionnaire (GPPAQ), General Health Questionnaire (GHQ), and other pre-tested questionnaires. General obesity was defined as having a body mass index (BMI) ≥30 kg/m2 and abdominal obesity as a waist circumference (WC) of ≥102 cm in men and ≥88 cm in women.

Results

Mean age of participants was 36.54 ± 7.97 years. General and abdominal obesity were prevalent among 8.7% and 21.5% of study participants, respectively. Linear analysis showed a significant positive relationship between healthy lifestyle score and BMI among men (β: 0.30, 95% CI: 0.05, 0.54). However, no significant association was found between healthy lifestyle and abdominal obesity in men. Among women, one score increase in healthy lifestyle score was associated with a reduction of 0.65 cm in WC. In terms of individual components of healthy lifestyle, we found that low-distressed women had lower odds of abdominal obesity compared with high-distressed women.

Conclusion

We found a significant inverse association between healthy lifestyle and WC among women. However, healthy lifestyle was positively associated with BMI among men.

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.

Pilot randomized trial of cognitive-behavioral treatment plus contingency management for quitting smoking and weight gain prevention among smokers with overweight or obesity

BACKGROUND

Post-cessation weight gain is a risk factor for relapse among quitters. The primary study aim was to evaluate, among smokers with overweight or obesity, the feasibility and acceptability of a cognitive-behavioral treatment (CBT) plus contingency management (CM) for quitting smoking and weight control. The secondary aim was to examine preliminary tobacco abstinence and weight change outcomes.

METHODS

In an 8-week pilot randomized clinical trial, 41 participants (M_age = 52.73, SD = 10.91, 56.1% females) with overweight or obesity (M_BMI = 31.86, SD = 4.7) received a CBT for both quitting smoking and weight gain prevention (n = 24) or the same treatment plus CM (n = 17), consisting of providing incentives contingent upon smoking abstinence biochemically verified.

RESULTS

Recruitment success rate was 80.39% (41/51), completion rate was 90.24% (37/41), and mean number of sessions attended (out of 15 possible) was 13.20 (SD = 3.1). Mean satisfaction rating for the treatment (1-10 likert-type scale with 10 being most satisfactory) was 9.73 (SD =.61). Preliminary efficacy data indicated that the CM group achieved higher abstinence rates compared with the CBT condition (100% vs. 58.33%, p = .007). Abstinent participants increased 1.25 kg (SD = 1.79) their baseline body weight at the end of treatment (p = .001).

CONCLUSIONS

Providing weight gain prevention strategies and CM within a smoking cessation treatment seems feasible and acceptable. Preliminary data indicated that including CM facilitates tobacco abstinence rates, nevertheless no advantage for CM was found for weight control.

No Paradoxical Effect of Smoking Status on Recurrent Cardiovascular Events in Patients Following Percutaneous Coronary Intervention: Thai PCI Registry

Background

"Smoker's paradox" is a controversial phenomenon that describes an unexpectedly favorable short-term outcome of smokers post-percutaneous coronary intervention (PCI). This study aimed to evaluate the effect of smoking status on recurrent major adverse cardiovascular events (MACEs) in patients who recently underwent PCI and to determine whether it was paradoxical.

Methods

This study utilized data from the nationwide Thai PCI registry, enrolling patients during 2018-2019. Our study factor was smoking status, classified as current smokers, ex-smokers, and nonsmokers. The outcome of interest was the time to occurrence of a composite of MACEs (i.e., all-cause death, myocardial infarction (MI), stroke, and unplanned revascularization) evaluated at about 1-year post-PCI. A propensity score (PS) model using inverse probability weighting with regression adjustment was used to estimate the effect of smoking on the occurrence of MACE.

Results

Current smokers, ex-smokers, and non-smokers accounted for 23, 32, and 45% of the 22,741 subjects, respectively. Smokers were younger, more frequently male, and had fewer traditional atherosclerotic risk factors. Current smokers presented more frequently with ST-elevation MIs (STEMIs) and cardiogenic shock (54 and 14.6%, respectively) than non-smokers. MACE rates were 1.9, 1.2, and 1.6 per 100 patients per month in the current smokers, ex-smokers, and non-smokers, respectively. After applying a PS, patients with a history of current smoking and ex-smoking developed the onset of recurrent MACEs significantly sooner than non-smokers, with a median time of 4.4 vs. 4.9 vs. 13.5 months (p < 0.001), respectively.

Conclusions

"Smoker's paradox" was not observed in our patient population. Current smokers and ex-smokers were prone to develop an earlier onset of a post-PCI MACEs than nonsmokers and need a smoke cessation program for further prevention.

Obesity Risk-Factor Variation Based on Island Clusters: A Secondary Analysis of Indonesian Basic Health Research 2018

Obesity has become a rising global health problem affecting quality of life for adults. The objective of this study is to describe the prevalence of obesity in Indonesian adults based on the cluster of islands. The study also aims to identify the risk factors of obesity in each island cluster. This study analyzes the secondary data of Indonesian Basic Health Research 2018. Data for this analysis comprised 618,910 adults (≥18 years) randomly selected, proportionate to the population size throughout Indonesia. We included 20 variables for the socio-demographic and obesity-related risk factors for analysis. The obesity status was defined using Body Mass Index (BMI) ≥ 25 kg/m². Our current study defines 7 major island clusters as the unit analysis consisting of 34 provinces in Indonesia. Descriptive analysis was conducted to determine the characteristics of the population and to calculate the prevalence of obesity within the provinces in each of the island clusters. Multivariate logistic regression analyses to calculate the odds ratios (ORs) was performed using SPSS version 27. The study results show that all the island clusters have at least one province with an obesity prevalence above the national prevalence (35.4%). Six out of twenty variables, comprising four dietary factors (the consumption of sweet food, high-salt food, meat, and carbonated drinks) and one psychological factor (mental health disorders), varied across the island clusters. In conclusion, there was a variation of obesity prevalence of the provinces within and between island clusters. The variation of risk factors found in each island cluster suggests that a government rethink of the current intervention strategies to address obesity is recommended.

Trends in cardiovascular disease risk factors by BMI category among adults in England, 2003-2018

OBJECTIVE

This study aimed to estimate trends in cardiovascular disease risk factors by BMI category among adults in England (n = 115,860).

METHODS

Risk factors included cigarette smoking, hypertension, total diabetes, and raised total cholesterol. Risk factor prevalence was computed in the following four 4-year time periods: 2003-2006; 2007-2010; 2011-2014; and 2015-2018. Change was computed as the difference between the first and last time periods, expressed in percentage points (PP).

RESULTS

Hypertension remained at a stable level among men with normal weight but decreased among men with obesity (-4.1 PP; 95% CI: -7.1 to -1.0). Total diabetes remained at a stable level among adults with normal weight but increased among adults with obesity (men: 3.5 PP, 95% CI: 1.2 to 5.7; women: 3.6 PP, 95% CI: 1.8 to 5.4). Raised total cholesterol decreased in all BMI groups but fell more sharply among women with obesity (-21 PP; 95% CI: -25 to -17) versus their counterparts with normal weight (-16 PP; 95% CI: -18 to -14).

CONCLUSIONS

Greater reductions in hypertension and raised total cholesterol among adults with overweight and obesity partially reflect improvements in screening, treatment, and control among those at highest cardiovascular risk. Higher levels of risk factor prevalence among adults with overweight and obesity, in parallel with rising diabetes, highlight the importance of national prevention efforts to combat the public health impact of excess adiposity.