Factors associated with stage of change in smoker in relation to smoking cessation based on the Korean National Health and Nutrition Examination Survey II-V

Predictors of Adolescents' Transition Through the Stages of Change for Quitting E-Cigarettes: Findings From the Population Assessment of Tobacco and Health Study

PURPOSE

To identify predictive factors associated with US adolescents' transition through the stages of change for potentially quitting e-cigarettes using the Trans-theoretical model of behavior change.

DESIGN

Prospective cohort study.

SETTING

United States.

SUBJECTS

We utilized data from adolescents (12-17 years) in Wave 3 of the Population Assessment of Tobacco and Health study who used e-cigarettes exclusively over the past 30 days (n = 177) and were followed up with in Wave 4.

MEASURES

Outcome variables were 3 transition categories: those who remained stagnant, those who progressed, and those who regressed in their stage of quitting e-cigarettes. Predictor variables were socio-demographics, e-cigarette harm perception, e-cigarette use at home or by important people, social norms, e-cigarette and anti-tobacco advertisements, and e-cigarette health warnings.

ANALYSIS

Weighted-adjusted multinomial regression analysis was performed to determine the association between predictor and outcome variables.

RESULTS

From Wave 3 to Wave 4, 19% of adolescents remained stagnant; 73.3% progressed; and 7.7% regressed. Adolescents were less likely to progress in their stage of change if they perceived nicotine in e-cigarettes to be "not at all/slightly harmful" (AOR = .26 [95% CI: .25, .27], P < .001); reported important people's use of e-cigarettes (AOR = .18 [95% CI: .05, .65, P = .009); and "rarely" noticed e-cigarette health warnings (AOR = .28 [95% CI: .08, .98, P = .054).

CONCLUSION

Intervention efforts must target specific predictive factors that may help adolescents quit e-cigarettes.

The Brazilian Longitudinal Study of Adult Health (ELSA-Brasil): Factors Related to Smoking Cessation

BACKGROUND

Smoking cessation is not an easy accomplishment. However, the benefits are several for those who do it, such as cardiovascular risk reduction 1 year after quitting smoking. This study aimed to verify the factors related to smoking cessation in civil servants of The Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

METHODS

This study had a longitudinal design using data from a prospective cohort of civil servants (ELSA-Brasil). Our variable of interest was smoking cessation. The relationship between socio-demographic characteristics, job stress, health-related variables, legislation, and smoking cessation was analyzed by Cox proportional hazard models. The analyses were stratified by gender. Second-hand smoke exposure, age, education, excessive alcohol consumption, common mental disorder, and smoking control law were the variables considered in the final model.

RESULTS

Information of 2020 women and 2429 men was analyzed. Individuals without second-hand smoke exposure, with up to 49 years of age, with higher education, without excessive alcohol consumption, without common mental disorders, and who initiated smoking in 1989 or after the smoking control law had a higher risk of stopping smoking. The risks magnitudes were higher for women.

CONCLUSIONS

Our study reinforces the necessity of alcohol consumption regulation, the relevance of Public Health Policies, and the need for more smoking cessation measures focused on men, on people with mental disorders, alcoholism, and older adults. Also, our results did not show significant risks regarding the psychosocial working environment.

Factors Associated with E-Cigarette Quit Intention Among Adolescents in the United States

Background: Given increasing use of e-cigarettes among adolescents in the United States and its potential for nicotine addiction, encouraging adolescents to quit using these products has become a public health priority. This study examined factors at various socio-ecological levels associated with e-cigarette quit intention (pre-contemplation, contemplation, or preparation) using the Stages of Change of the Trans-theoretical Model among the U.S. adolescents. Methods: We used cross-sectional data from the past 30-day adolescent exclusive e-cigarette users participating in Wave 4 of the Population Assessment of Tobacco and Health study (n = 349). Weighted adjusted multinomial logistic regression models were used to analyze the data. Results: Compared to pre-contemplators and contemplators, preparators were more likely to believe that nicotine in e-cigarettes was "very/extremely harmful" (vs. "not at all harmful") to health (p < 0.001) and people cause a "lot of harm" (vs. "no harm") to themselves when they use e-cigarettes (p < 0.001). In comparison to pre-contemplators, contemplators and preparators were more likely to report that their parents/guardians talked with them about not using e-cigarettes than those whose parents/guardians did not talk with them (p < 0.001). Additionally, contemplators and preparators were also more likely to report that they "often/very often" (vs. never) noticed health warnings on e-cigarette packages (p < 0.001). Conclusion: Our findings suggest that harm perception, influence of family, and e-cigarette health warnings are some of the important factors associated with the stages of change for intention to quit among adolescent e-cigarette users. This study will help public health practitioners and researchers design multi-level e-cigarette cessation interventions for adolescents.

Causes of smoking relapse in the 12 months after smoking cessation treatment: Affective and cigarette dependence-related factors

Despite advances in smoking cessation treatments, smoking relapse remains common. Experiencing positive or negative affect and cigarette dependence are the most common causes of relapse; however, little is known about the characteristics that increase the risk of relapse from these causes among current treatment-seeking smokers. Thus, this study aimed to identify the most frequent causes of relapse and the individual characteristics that increase the risk of relapse from these causes during a 12-month period after smoking cessation. Participants included 121 treatment-seeking smokers who quit smoking at the end of treatment and relapsed during a 12-month follow-up period (60.3% female;Mage = 42.57, SD = 11.07). Results indicated that the most frequent smoking relapse situations occurred when smokers experienced positive (e.g., being relaxed; 43.0%) or negative (e.g., being angry; 37.2%) affect or cigarette dependence-related situations (e.g., craving; 19.8%). At an individual level, males with a higher level of education and without a psychopharmaceutical prescription had a higher risk of relapsing in positive-affect situations. Smoking the first cigarette at an older age increased the risk of relapse in negative-affect situations. Finally, being younger and less motivated to quit at pretreatment increased the likelihood of relapse in cigarette dependence-related situations. These findings provide detailed information about smoking relapse situations and identify a set of characteristics that might help to improve current relapse-prevention interventions.

The Impact of Psychiatric Disorder Diagnosis on Motivation to Quit and Stage of Change Among Patients at a Hospital-Based Outpatient Smoking Cessation Clinic

Smoking is among the greatest international public health concerns, causing excessive levels of preventable premature death, disability, and economic costs. The prevalence of tobacco use among people with psychiatric disorders (PDs) remains persistently high relative to the general population, highlighting the need to improve smoking cessation (SC) strategies in this group. We aimed to assess the associations between having a PD and baseline motivation to quit (MtQ) smoking and Prochaska's stage of change (SoC), two clinically important metrics linked to SC outcomes. Methods: This retrospective chart review included patients who completed a baseline visit at a hospital-based outpatient SC clinic (N = 896). Multivariate hierarchical logistic and linear regression models were developed to assess variables associated with MtQ (importance and confidence in quitting) and SoC, primarily PD category (externalizing, internalizing, externalizing/internalizing, psychotic or no PD) and secondarily, demographics, physical health history, and tobacco use/dependence metrics. Results: The variables negatively associated with MtQ were female sex (p = .011), older age (p = .038), deriving income from social assistance (p < .001), and age at smoking initiation (p = .005), whereas ≥ 1 quit attempt in the past year predicted higher MtQ (p < .0001). Being in the preparative/action SoC (versus the pre-contemplative/contemplative) was associated with income from social assistance (OR 0.39, p = .001), more daily cigarettes smoked (OR 0.98, p = .005) and ≥ 1 past-year quit attempt (OR 1.69, p = .013). Conclusions: Having a PD was not associated with either MtQ or SoC. Deriving income from social assistance predicted lower MtQ and SoC. Having made ≥ 1 quit attempt in the past year was associated with higher MtQ and SoC. Our study suggests that people with PDs are as motivated to quit smoking and ready for change as people without PDs, and smoking cessation efforts should be amplified in this group to address the disproportionately high level of tobacco use, especially because having at least one quit attempt may enhance MtQ and SoC.

Identifying High-Risk Factors of Depression in Middle-Aged Persons with a Novel Sons and Spouses Bayesian Network Model

It has been reported repeatedly that depression in middle-aged people may cause serious ramifications in public health. However, previous studies on this important research topic have focused on utilizing either traditional statistical methods (i.e., logistic regressions) or black-or-gray artificial intelligence (AI) methods (i.e., neural network, Support Vector Machine (SVM), ensemble). Previous studies lack suggesting more decision-maker-friendly methods, which need to produce clear interpretable results with information on cause and effect. For the sake of improving the quality of decisions of healthcare decision-makers, public health issues require identification of cause and effect information for any type of strategic healthcare initiative. In this sense, this paper proposes a novel approach to identify the main causes of depression in middle-aged people in Korea. The proposed method is the Sons and Spouses Bayesian network model, which is an extended version of conventional TAN (Tree-Augmented Naive Bayesian Network). The target dataset is a longitudinal dataset employed from the Korea National Health and Nutrition Examination Survey (KNHANES) database with a sample size of 8580. After developing the proposed Sons and Spouses Bayesian network model, we found thirteen main causes leading to depression. Then, genetic optimization was executed to reveal the most probable cause of depression in middle-aged people that would provide practical implications to field practitioners. Therefore, our proposed method can help healthcare decision-makers comprehend changes in depression status by employing what-if queries towards a target individual.

Effect of Increasing Tobacco Prices on Stages of Smoking Cessation: A Korean Nationwide Data Analysis

BACKGROUND

In 2015, tobacco prices significantly increased in Korea as part of the government's smoking cessation policy. This study examined the changes in the stages of smoking cessation among Korean male smokers before and after the implementation of the tobacco price policy, and identified the predictors of such changes.

METHODS

The study population comprised 3,533 male current smokers (age ≥19 years) who participated in the Korea National Health and Nutrition Survey in 2012, 2013, 2015, and 2016. Current smokers were defined as persons who had smoked ≥100 cigarettes during their lifetime and are continuing to smoke. In accordance with the transtheoretical model, smokers were classified into the precontemplation stage (no plan to quit), contemplation stage, and preparation stage (planning to quit within 6 months). We examined the changes in the smoking cessation stages before and after the implementation of the policy. Multivariate logistic regression analysis was conducted to identify factors related to the likelihood of continuing smoking, after adjustments for potential confounders.

RESULTS

Immediately after the policy implementation, the percentage of smokers in the precontemplation stage decreased from 65.6% to 60.8% (P=0.014). However, this effect was temporary. Significant risk factors for remaining in the precontemplation stage were older age (odds ratio [OR], 1.010; 95% confidence interval [CI], 1.002-1.018; P=0.004), being in the lowest income quartile (OR, 1.226; 95% CI, 1.001-1.502; P=0.049), and manual worker or unemployed status (OR, 1.256; 95% CI, 1.036-1523; P=0.020).

CONCLUSION

Increasing tobacco prices only temporarily change the stage of smoking cessation among Korean male smokers.