Understanding e-Cigarette Addictiveness: Triangulation of Focus Group and Netnographic Data.

BACKGROUND: Numerous studies have shown that e-cigarettes are addictive. For example, we previously showed that users of e-cigarette online forums discuss experiences of addiction in a netnographic analysis. However, it is unclear what makes e-cigarettes addictive apart from nicotine. In a focus group analysis, we recently identified 3 unique features of e-cigarettes that users linked to experiences of addiction: the pleasant taste, unobtrusiveness, and unlimited usability of e-cigarettes. OBJECTIVE: This study aimed to validate the previously identified features of e-cigarette addictive potential by triangulating data from the netnographic analysis and focus group discussions. METHODS: Drawing on a netnographic analysis of 3 popular, German-language e-cigarette forums, we studied whether experiences of addiction were linked to specific e-cigarette features. We included 451 threads in the analysis that had been coded for addictive experiences in a previous study by our team. First, we conducted a deductive analysis with preregistered codes to determine whether the features of pleasant taste, unobtrusiveness, and unlimited usability were mentioned in relation to the addictive potential of e-cigarettes in the online forums. Second, an inductive approach was chosen to identify further possible addictive features of e-cigarettes. RESULTS: Our deductive analysis confirmed that the features highlighted in our previous focus group study (pleasant taste, unobtrusiveness, and unlimited usability) were also frequently discussed in online forums in connection to addictive symptoms. In addition, our inductive analysis identified nicotine dosage as a significant feature linked to addiction. Users reported varying their nicotine doses for different reasons, leading to the identification of four distinct user types based on dosing patterns: (1) high doses for intermittent, (2) high doses for constant use, (3) low doses for constant use, and (4) switching between high and low doses depending on the situation. CONCLUSIONS: Our comprehensive analysis of online forum threads revealed that users' experiences of addiction are linked to 4 specific features unique to e-cigarettes: pleasant taste, unobtrusiveness, unlimited usability, and nicotine dosage. Recognizing these addictive features of e-cigarettes is crucial for designing cessation programs and informing public health policies to reduce the addictiveness of e-cigarettes.

The Association Between Smoking Behavior and the Risk of Hypertension: Review of the Observational and Genetic Evidence.

Background: Cigarette smoking is one of the world's largest avoidable risk factors for morbidity and mortality. Numerous studies have investigated the association between smoking and hypertension (HTN). Although observational data and cross-sectional research often exhibit a link between smoking and HTN, establishing causation remains challenging owing to potential confounding variables. Mendelian randomization (MR), a genetic epidemiological technique that employs genetic variants as instrumental variables, offers a more robust approach for evaluating causal links. This review aimed to explore both the observational and causal relationships between smoking and the risk of HTN. Methodology: A comprehensive literature search across major electronic databases was conducted to identify relevant observational and Mendelian randomization (MR) studies on smoking and HTN risk. Various characteristics were included during study selection, such as study design, exposure assessment, and age range. Standardized processes were used for data retrieval and quality evaluation. Results: Analysis of observational data revealed a paradoxical association between smoking and the risk of HTN, where a lower risk was observed among current smokers when compared to non-smokers. However, observational analysis also presented a dose-response effect with greater smoking intensity showed a modest linear increase in HTN risk, and older smoking initiation was associated with a slight increase in HTN risk (compared with younger). In contrast, MR-based causal estimates provide inconsistent evidence regarding the causal relationship between smoking behavior and HTN. Some MR analyses indicated a potential causal link between smoking and HTN; but this was not consistent. Conclusion: Observational studies suggest a paradoxical association between smoking and HTN. However, MR studies do not provide sufficient evidence to establish a causal relationship. Regardless, lifestyle variables remain crucial for overall health. Healthcare professionals should regularly assess smoking status and provide counseling for quitting. Further research is needed to clarify the underlying processes, identify mediators, and evaluate the interventions.

The association of genetic polymorphisms within the dopaminergic system with nicotine dependence: A narrative review.

Nicotine, the main compound in cigarettes, leads to smoking addiction. Nicotine acts on the limbic dopamine reward loop in the midbrain by binding to nicotinic acetylcholine receptors, promoting the release of dopamine, and resulting in a rewarding effect or satisfaction. This satisfaction is essential for continued and compulsive tobacco use, and therefore dopamine plays a crucial role in nicotine dependence. Numerous studies have identified genetic polymorphisms of dopaminergic pathways which may influence susceptibility to nicotine addiction. Dopamine levels are greatly influenced by synthesis, storage, release, degradation, and reuptake-related genes, including genes encoding tyrosine hydroxylase, dopamine decarboxylase, dopamine transporter, dopamine receptor, dopamine 3-hydroxylase, catechol-O-methyltransferase, and monoamine oxidase. In this paper, we review research progress on the effects of polymorphisms in the above genes on downstream smoking behavior and nicotine dependence, to offer a theoretical basis for the elucidation of the genetic mechanism underlying nicotine dependence and future personalized treatment for smoking cessation.

A qualitative study on tobacco use during the COVID-19 pandemic in Lebanon: Waterpipe and cigarette smokers' views, risk perceptions, and behaviors.

INTRODUCTION: Since the beginning of the COVID-19 pandemic, a growing number of studies have documented more severe COVID-19 symptoms and worse outcomes among smokers compared to non-smokers. The aim of this research is to understand the views, risk perceptions, and behaviors of Lebanese adult smokers during the pandemic. METHODS: We conducted 18 qualitative online structured interviews with adults who smoke cigarettes and waterpipe tobacco residing in Lebanon from November 2020 through April 2021. Participants were recruited predominantly via paid social media ads. Interviews were audio-recorded using Zoom software then transcribed verbatim. Data were analyzed thematically. RESULTS: The findings showed three main themes: changes to smoking behaviors, concerns over the susceptibility and severity of COVID-19, and using coping methods to protect smokers from COVID-19. Although there was an increased risk perception of COVID-19 in relation to smoking, most participants reported an increase in smoking. Instead of being encouraged to quit, participants developed coping strategies against COVID-19 while smoking. CONCLUSIONS: Smoking behavior did not seem to decrease during the COVID-19 pandemic. To support cessation initiatives and raise awareness, effective health messaging aimed at smokers is pivotal. Smoking cessation programs need to be better equipped at supporting people who smoke in finding healthier coping mechanisms during a pandemic. Moreover, policies to regulate the propagation of misinformation are required to prevent the development of a false sense of safety and protection from COVID-19.

Genetic correlation between smoking behavior and gastroesophageal reflux disease: insights from integrative multi-omics data.

BACKGROUND: Observational studies have preliminarily revealed an association between smoking and gastroesophageal reflux disease (GERD). However, little is known about the causal relationship and shared genetic architecture between the two. This study aims to explore their common genetic correlations by leveraging genome-wide association studies (GWAS) of smoking behavior-specifically, smoking initiation (SI), never smoking (NS), ever smoking (ES), cigarettes smoked per day (CPD), age of smoking initiation(ASI) and GERD. METHODS: Firstly, we conducted global cross-trait genetic correlation analysis and heritability estimation from summary statistics (HESS) to explore the genetic correlation between smoking behavior and GERD. Then, a joint cross-trait meta-analysis was performed to identify shared "pleiotropic SNPs" between smoking behavior and GERD, followed by co-localization analysis. Additionally, multi-marker analyses using annotation (MAGMA) were employed to explore the degree of enrichment of single nucleotide polymorphism (SNP) heritability in specific tissues, and summary data-based Mendelian randomization (SMR) was further utilized to investigate potential functional genes. Finally, Mendelian randomization (MR) analysis was conducted to explore the causal relationship between the smoking behavior and GERD. RESULTS: Consistent genetic correlations were observed through global and local genetic correlation analyses, wherein SI, ES, and CPD showed significantly positive genetic correlations with GERD, while NS and ASI showed significantly negative correlations. HESS analysis also identified multiple significantly associated loci between them. Furthermore, three novel "pleiotropic SNPs" (rs4382592, rs200968, rs1510719) were identified through cross-trait meta-analysis and co-localization analysis to exist between SI, NS, ES, ASI, and GERD, mapping the genes MED27, HIST1H2BO, MAML3 as new pleiotropic genes between SI, NS, ES, ASI, and GERD. Moreover, both smoking behavior and GERD were found to be co-enriched in multiple brain tissues, with GMPPB, RNF123, and RBM6 identified as potential functional genes co-enriched in Cerebellar Hemisphere, Cerebellum, Cortex/Nucleus accumbens in SI and GERD, and SUOX identified in Caudate nucleus, Cerebellum, Cortex in NS and GERD. Lastly, consistent causal relationships were found through MR analysis, indicating that SI, ES, and CPD increase the risk of GERD, while NS and higher ASI decrease the risk. CONCLUSION: We identified genetic loci associated with smoking behavior and GERD, as well as brain tissue sites of shared enrichment, prioritizing three new pleiotropic genes and four new functional genes. Finally, the causal relationship between smoking behavior and GERD was demonstrated, providing insights for early prevention strategies for GERD.

Perception and the influence of information toward e-cigarette smoking behavior.

INTRODUCTION: Perceptions, personal perspectives, and public awareness of e-cigarette information have a significant impact on e-cigarette smoking behavior, and provide comprehensive information that can help reduce interest in e-cigarette smoking and reduce the number of new smokers. This study aimed to investigate the perceptions towards e-cigarettes related to e-cigarette use and how that information related to people's use of them. METHODS: The data for this cross-sectional study were collected via an online questionnaire. Thai nationals who were aged ≥18 years provided data between June 2021 and January 2022. Multivariable logistic regression and the chi-squared test were used to analyze the data. RESULTS: There were 340 respondents, 76 e-cigarette users, and 264 non-e-cigarette users. Most of the perceptions of information that differed statistically significantly between e-cigarette users and non-e-cigarette users included information on regulations, products, health effects, and the effectiveness of smoking cessation. The association between factors and e-cigarette smoking behavior revealed that the perception of the product information and male gender were associated with e-cigarette smoking behavior (AOR=13.59; 95% CI: 2.35-78.60, and AOR=5.19; 95% CI: 2.87-9.40, respectively). CONCLUSIONS: The perception of e-cigarette product information and male gender were associated with e-cigarette smoking behavior.

The Trend of Smoking-Related Cognition and Its Association with Smoking Behaviors Among Junior High School Students - China, 2013-2021.

What is already known about this topic?: In 2013, 31.61% of students perceived quitting smoking as difficult, 61.73% considered smoking less attractive, and 73.89% believed that secondhand smoke is definitely harmful to health. What is added by this report?: The percentage of students who perceived quitting smoking as difficult increased from 31.61% in 2013 to 38.83% in 2021, while the percentage of students who found smoking less attractive rose from 61.73% to 69.40%. Conversely, there was a decrease in the percentage of students who perceived secondhand smoke as harmful, from 73.89% to 68.46%. An increased awareness of the hazards of secondhand smoke was associated with a reduction in smoking behaviors. What are the implications for public health practice?: It is imperative to enhance health education efforts that aim to raise awareness of the hazards of secondhand smoke.

The Effect of Cigarette Content Marketing on Students' Smoking Behavior and Decisions: A PLS-SEM Approach.

OBJECTIVE: This research aims to analyze the influence of cigarette content marketing on student behavior, and on cigarette purchasing decisions, as well as the influence of behavior on cigarette purchasing decisions. METHODS: This research is quantitative, using a sample of 500 smoking students from twelve universities in the city of Medan, Indonesia, who were selected using a simple random sampling technique. Data collection was carried out by distributing questionnaires that had been tested for convergent validity with an Outer Loading value > 0.7 and an AVE value > 0.5, and for discriminant validity with an HTMT value < 0.9. The data was analyzed using a multivariate analysis technique which combines factor analysis and regression analysis. RESULTS: The research results show that the t-statistical value for the behavioral variable (BHV) is 4.128 (> 1.98) and the p-value is 0.000 (< 0.05), which means that the BHV variable has a significant effect on the cigarette purchasing decision variable (PD). The t-statistical value for the content marketing (CM) variable is 27.57 (> 1.98) and the p-value is 0.000 (< 0.05), which means that the CM variable has a significant effect on the BHV variable. The t-statistical value for the CM variable is 18,542 (> 1.98) and the p-value is 0.000 (< 0.05), which means that the CM variable has a significant effect on the PD variable.  93.2% of respondents admitted that they had seen cigarette marketing content on social media, many of them (43%) believed that smoking was detrimental to their health, but the most influential factor was their perception regarding the activity of smoking. CONCLUSION: Cigarette marketing content has been proven to influence students' behavior towards cigarettes, as well as directly influencing their decision to purchase cigarettes. Students' behavior towards cigarettes also influences their decisions in purchasing cigarettes.

The Impact of Different Smoking Behavior on Pulmonary Function and Pulmonary Hypertension Among Chinese Male Patients with Chronic Obstructive Pulmonary Disease.

Purpose: Cigarette smoking is the most recognized risk factor of chronic obstructive pulmonary disease (COPD) in China. However, there are no studies analyzing the impact of different smoking behaviors on pulmonary function and pulmonary hypertension (PH) among Chinese male patients with COPD. Patients and Methods: Chinese male smokers with COPD performed pulmonary function tests. Clinical characteristics, smoking behavior features, spirometry and echocardiographic results were compared between the two groups stratified by initial smoking age (18 years old) or complicated PH. Results: The early-smoking group had more respiratory symptoms, more severe smoking behavior, worse pulmonary function with lower FEV1%pre (38.5% vs 70.2%) and FEV1/FVC% (47.5% vs 63.8%), and higher systolic pulmonary artery pressure (sPAP: 38.6 vs 33.9 mmHg) than the late-smoking group. Initiating smoking before adulthood was an independently contributing factor of ventilatory dysfunction and Global Initiative for Obstructive Lung Disease (GOLD) stage escalation. It also had a significant interaction with long smoking duration (≥30 years), characterized by markedly decreased lung volumes (VC%pre: 64.0% vs 84.5%), impaired diffusing capacity (DLCO%pre: 58.0% vs 76.8%) and severe emphysema (RV/TLC%pre: 145.2% vs 130.2%). COPD patients complicated with PH exhibited worse ventilatory function (FEV1%pre: 43.2% vs 56.2%), impaired diffusion capacity (DLCO%pre: 56.7% vs 77.1%) and decreased lung volume (VC%pre: 67.67% vs 75.38%). Both severe smoking behaviors and impaired pulmonary function had close correlations with sPAP. Conclusion: The early-smoking group exhibited predominantly ventilation dysfunction and had complex interactions with long smoking duration to further affect lung volume and diffusion capacity. Different smoking behaviors influenced variations of pulmonary dysfunction and comorbid PH in patients with COPD.

Do tougher drinking policies affect men's smoking behavior - Evidence from China.

In 2011, China implemented tougher driving-under-the-influence laws, which criminalized driving under the influence of alcohol for the first time and increased penalties. This paper provides the first comprehensive analysis of the effects of stricter drinking policies on men's smoking behavior by using data from the 2010 and 2012 waves of the China Family Panel Studies. The results show that stricter drinking policies reduced smoking initiation and the number of cigarettes smoked per day among men by reducing the frequency and quantity of alcohol consumption. Heterogeneity analyses show that the impact of the policy is more pronounced not only for men aged 41-55, but also for men who have higher educational qualifications, who are employed, or who are not members of the Communist Party.

Predictors of quitting smoking behavior: evidence from Pakistan.

This study attempts to identify factors that significantly encourage the cessation of smoking in the context of Pakistan. The study distributes a modified questionnaire among 421 respondents (current as well as former smokers) in the capital city of Pakistan, Islamabad. The binary regression method was employed to data for analyzing predictors of making quit attempts and successful smoking cessation. The result indicates that respondents having strong intentions to quit, high socioeconomic status, low nicotine dependency, and past quit attempts, and those having no-smoking friends, are more likely to quit cigarette smoking successfully. On the other hand, factors like social pressure to quit smoking, religious information against smoking, intention to quit smoking, and public regulation on smoking are more likely to encourage smokers to make quit attempts. The study calls for community and school-wide smoking cessation campaigns involving officials, peers and parents, religious leaders, and other influential individuals to inform people about the dangers of smoking. In addition, religious leaders should be encouraged to issue rulings against smoking especially during "Friday Prayer." Furthermore, the government should pronounce more strict and comprehensive regulations on smoking by properly monitoring its implementation to encourage cessation of cigarette smoking.

Relationship between stable smoking behavior and cognitive function in male schizophrenia patients.

OBJECTIVE: To explore the relationship between stable smoking behavior and cognitive function in male schizophrenia patients. METHODS: A simple random sampling method is applied to select 120 patients with schizophrenia admitted to a hospital from August 2020 to December 2022 as the subjects. They are divided into two groups based on whether they smoked or not. Their cognitive function is evaluated using the Stroop test (SWCT), continuous task test (CPT), and Chinese version of the Schizophrenic Cognitive Function Battery Test (MCCB). The Spearman correlation analysis is applied to verify the correlation between smoking behavior and SWCT, CPT, and MCCB in patients. Additionally, the Fagerstrom Nicotine Dependence Scale (FTND) is used to evaluate the nicotine dependence degree in smoking group patients. Pearson correlation analysis verifies the correlation between nicotine dependence and SWCT, CPT, MCCB in smoking group patients. RESULTS: Among 120 patients include in this study, 3 have symptoms during the trial period, and 1 patient has an error in filling out the questionnaire, all of which are excluded. Finally, 116 valid documents are collected, with an effective recovery rate of 96.67%. According to the SWCT test results, the number of single word errors, single word time, double word errors, and double word time in the smoking group exceed the non-smoking group (P < 0.05). According to the CPT test results, the number of correct reactions in the smoking group is below the non-smoking group. The correct average reaction time, error rate of interference items, and error rate of ineffective items exceed the non-smoking group (P < 0.05). According to the MCCB test results, the scores of connectivity, visual spatial memory, and continuous operation test in the smoking group are below the non-smoking group (P < 0.05). The Spearman correlation analysis results show that stable smoking behavior in male schizophrenia patients is positively correlated with the number of single word errors, double word errors, double word time, correct mean reaction time, interference item error rate, and invalid item error rate (r = 0.216-0.524, P < 0.05). It is also positively correlated with the number of correct reactions, immediate memory, language function, delayed memory, MCCB connectivity, visual spatial memory, and continuous operation (r = -0.212-0.356, P < 0.05). The Pearson correlation analysis results show that the nicotine dependence degree in stable male schizophrenia patients is negatively correlated with monochromatic error count, immediate memory, visual span, attention, and MCCB scores (r = -0.321-0.930, P < 0.05). CONCLUSION: Smoking in male schizophrenic patients may have impacts on their cognitive function. This impact worsens as the patient's nicotine dependence increases, especially on their memory function. Effective measures should be taken in clinical practice to correct patients' smoking behavior, reduce their nicotine dependence, and improve their cognitive function.

Effects of common lifestyle factors on obstructive sleep apnea: precautions in daily life based on causal inferences.

Background: This study aimed to evaluate the causal impact of common modifiable lifestyles on obstructive sleep apnea (OSA), which is beneficial for recommendations to prevent and manage OSA. Method: Published genome-wide association study (GWAS) summary statistics were used to perform two-sample Mendelian randomization (MR). Variants associated with each exposure of smoking, drinking, and leisure sedentary behaviors at the genetic level were used as instrumental variables (IVs). Then, inverse-variance weighting (IVW) was considered the primary result for causality. Moreover, several complimented approaches were also included to verify the observed associations. MR-PRESSO and MR-Egger intercept were applied to test the horizontal pleiotropy. To assess heterogeneity, Cochran's Q test by IVW and MR-Egger were applied. Results: Regular smoking history increased OSA risk in all applied approaches [OR (95% CI)IVW = 1.28 (1.12, 1.45), p = 1.853 × 10-4], while the causality of lifetime smoking index [OR (95% CI)IVW = 1.39 (1.00, 1.91), p = 0.048], alcohol intake frequency [outliers removed OR (95% CI)IVW = 1.26 (1.08, 1.45), p = 0.002], and coffee intake behavior [OR (95% CI)IVW = 1.66 (1.03, 2.68), p = 0.039] on OSA risk were not always consistent in other approaches. In addition, no robust causal associations were observed for the effect of sedentary leisure behaviors on OSA risk. In sensitivity analysis, we observed no sign of horizontal pleiotropy or heterogeneity. Conclusion: Ever regularly smoking has a robust causal role in increasing OSA risk, which should be discouraged as precautions from developing OSA.

Smoking Behavior Change and the Risk of Heart Failure in Patients With Type 2 Diabetes: Nationwide Retrospective Cohort Study.

BACKGROUND: Heart failure (HF) is one of the most common initial manifestations of cardiovascular disease in patients with type 2 diabetes. Although smoking is an independent risk factor for HF, there is a lack of data for the incidence of HF according to changes in smoking behaviors in patients with type 2 diabetes. OBJECTIVE: We aimed to examine the association between interval changes in smoking behavior and the risk of HF among patients with type 2 diabetes. METHODS: We conducted a retrospective cohort study using the National Health Insurance Service database. We identified 365,352 current smokers with type 2 diabetes who had 2 consecutive health screenings (2009-2012) and followed them until December 31, 2018, for the incident HF. Based on smoking behavior changes between 2 consecutive health screenings, participants were categorized into quitter, reducer I (≥50% reduction) and II (<50% reduction), sustainer (reference group), and increaser groups. RESULTS: During a median follow-up of 5.1 (IQR 4.0-6.1) years, there were 13,879 HF cases (7.8 per 1000 person-years). Compared to sustainers, smoking cessation was associated with lower risks of HF (adjusted hazard ratio [aHR] 0.90, 95% CI0.86-0.95), whereas increasers showed higher risks of HF than sustainers; heavy smokers who increased their level of smoking had a higher risk of HF (aHR 1.13, 95% CI 1.04-1.24). In the case of reducers, the risk of HF was not reduced but rather increased slightly (reducer I: aHR 1.14, 95% CI 1.08-1.21; reducer II: aHR 1.03, 95% CI 0.98-1.09). Consistent results were noted for subgroup analyses including type 2 diabetes severity, age, and sex. CONCLUSIONS: Smoking cessation was associated with a lower risk of HF among patients with type 2 diabetes, while increasing smoking amount was associated with a higher risk for HF than in those sustaining their smoking amount. There was no benefit from reduction in smoking amount.

Trial Participants' Perceptions of the Impact of Ecological Momentary Assessment on Smoking Behaviors: Qualitative Analysis.

Background: Ecological momentary assessment (EMA) is an increasingly used tool for data collection in behavioral research, including smoking cessation studies. As previous addiction research suggests, EMA has the potential to elicit cue reactivity by triggering craving and increasing behavioral awareness. However, there has been limited evaluation of its potential influence on behavior. Objective: By examining the perspectives of research participants enrolled in a tobacco treatment intervention trial, this qualitative analysis aims to understand the potential impact that EMA use may have had on smoking behaviors that may not have otherwise been captured through other study measures. Methods: We performed a qualitative analysis of in-depth interviews with participants enrolled in a pilot randomized controlled trial of a tobacco treatment intervention that used SMS text messaging to collect EMA data on smoking behaviors. In the pilot randomized controlled trial, combustible cigarette and e-cigarette use and smoking-related cravings were measured as part of an EMA protocol, in which SMS text messaging served as a smoking diary. SMS text messaging was intended for data collection only and not designed to serve as part of the intervention. After a baseline assessment, participants were asked to record daily nicotine use for 12 weeks by responding to text message prompts that they received 4 times per day. Participants were prompted to share their experiences with the EMA text messaging component of the trial but were not directly asked about the influence of EMA on their behaviors. Transcripts were coded according to the principles of the framework for applied research. The codes were then examined, summarized, and grouped into themes based on the principles of grounded theory. Results: Interviews were analyzed for 26 participants. The themes developed from the analysis suggested the potential for EMA, in the form of an SMS text messaging smoking diary, to influence participants' smoking behaviors. The perceived impacts of EMA text messaging on smoking behaviors were polarized; some participants emphasized the positive impacts of text messages on their efforts to reduce smoking, while others stressed the ways that text messaging negatively impacted their smoking reduction efforts. These contrasting experiences were captured by themes reflecting the positive impacts on smoking behaviors, including increased awareness of smoking behaviors and a sense of accountability, and the negative impacts on emotions and smoking behaviors, including provoking a sense of guilt and triggering smoking behaviors. Conclusions: The collection of EMA smoking behavior data via SMS text messaging may influence the behaviors and perceptions of participants in tobacco treatment interventions. More research is needed to determine the magnitude of impact and mechanisms, to account for the potential effects of EMA. A broader discussion of the unintended effects introduced by EMA use is warranted among the research community.

Tobacco advertising, promotion, sponsorship and youth smoking behavior: The Indonesian 2019 Global Youth Tobacco Survey (GYTS).

INTRODUCTION: Tobacco advertisement, promotion, and sponsorship (TAPS) in all forms influences youth smoking behaviors. TAPS exposure enhances their smoking frequency and vulnerability. A 2018 Indonesia Ministry of Health (MoH) Survey showed increased smoking prevalence among youth aged 10-18 years. Thus, our objective was to analyze the relationship between TAPS and the increased Indonesian youth smoking behavior. METHODS: We conducted a secondary analysis of the Indonesian 2019 Global Youth Tobacco Survey. The sample size differed in each variable: current smokers n=3386, ever smoker n=3666, and cigarette consumption per day n=1355. We adjusted for socioeconomic and demographic variables and used logistic regression with youth smoking prevalence as the outcome and TAPS variables as the primary exposures. RESULTS: The current male youth smoker prevalence was 38.3%, ever smoker was 67%, and high consumption per day smoker (≥2 cigarettes per day) was 39.1%. Youth respondents exposed to the promotion or sponsorship of cigarette products showed an increase in three smoking behaviors. In particular, when youth respondents were exposed to more than one type of cigarette promotion (AOR=1.67, 95% CI: 1.33-2.09) or noticed one type of cigarette sponsorship (AOR=2.06, 95% CI: 1.44-2.93), their odds of all three smoking behaviors (current smoker, ever smoker, and high consumption smoker) increased. CONCLUSIONS: TAPS increase smoking behaviors among Indonesian youth. Therefore, to protect Indonesian youth health in the future, strategic action is needed to reduce youth smoking by banning all forms of TAPS in Indonesia.

Smokeless and combustible tobacco use among 148,944 South Asian adults: a cross-sectional study of South Asia Biobank.

INTRODUCTION: Tobacco use, in both smoking and smokeless forms, is highly prevalent among South Asian adults. The aims of the study were twofold: (1) describe patterns of SLT and combustible tobacco product use in four South Asian countries stratified by country and sex, and (2) assess the relationships between SLT and smoking intensity, smoking quit attempts, and smoking cessation among South Asian men. METHODS: Data were obtained from South Asia Biobank Study, collected between 2018 and 2022 from 148,944 men and women aged 18 years and above, living in Bangladesh, India, Pakistan, or Sri Lanka. Mixed effects multivariable logistic and linear regression were used to quantify the associations of SLT use with quit attempt, cessation, and intensity. RESULTS: Among the four South Asian countries, Bangladesh has the highest rates of current smoking (39.9% for male, 0.4% for female) and current SLT use (24.7% for male and 23.4% for female). Among male adults, ever SLT use was associated with a higher odds of smoking cessation in Bangladesh (OR, 2.88; 95% CI, 2.65, 3.13), India (OR, 2.02; 95% CI, 1.63, 2.50), and Sri Lanka (OR, 1.36; 95% CI, 1.14, 1.62). Ever SLT use and current SLT use was associated with lower smoking intensity in all countries. CONCLUSIONS: In this large population-based study of South Asian adults, rates of smoking and SLT use vary widely by country and gender. Men who use SLT products are more likely to abstain from smoking compared with those who do not.

The association between different types of physical activity and smoking behavior.

BACKGROUND: Smoking is harmful, which has become a major public health burden. Physical activity may be related to smoking. Physical activity is one of the current methods for smoking control and smoking cessation. Different types of physical activity may have different effect on smoking behavior. OBJECTIVE: The purpose of this study was to identify the direction and extent of the impact of different types of physical activity above moderate intensity (including work physical activity, recreational physical activity, commuter physical activity and sedentary behavior) on smoking behavior. MATERIALS AND METHODS: In this study, a total of 2,015 individuals (1,233 males and 782 females, mean age 54.02±17.31 years) was selected from the representative population aged 20 and above in the National Health and Nutrition Survey of the United States from 2017 to 2018. Physical activity was assessed using the Global Physical Activity Questionnaire (GPAQ) ; the tobacco use questionnaire (SMQ) was used to determine whether the sample had smoking behavior at this stage. Binary Logistic regression analysis was performed with various physical activities as independent variables and smoking behavior as dependent variables. All data were analyzed through Statistical Product and Service Solutions (SPSS) 26.0. RESULTS: After adjusted for all confounding variables, physical activity at work was close to significantly associated with smoking behavior (P=0.053), odds ratio (OR) =1.135 (95%Cl: 0.999-1.289). Recreational physical activity was significantly associated with smoking behavior (P < 0.001), OR=0.729 (95%Cl: 0.639-0.832). Commuting physical activity was significantly associated with smoking behavior (P < 0.001), OR=1.214 (95%Cl:1.048-1.405). Sedentary behavior was significantly associated with smoking behavior (P < 0.001), OR=1.363 (95%Cl: 1.154-1.611). CONCLUSIONS: Given that different types of physical activity have different associations with smoking behavior. Therefore, when physical activity is used as a tobacco control measurement, it is necessary to pay attention to the type and environment of physical activity. Recreational physical activities should be appropriately increased, sedentary behavior should be reduced, and smoking prohibit environment should be expanded as far as possible to achieve better clinical intervention effects.

Risk profiles for smoke behavior in COVID-19: a classification and regression tree analysis approach.

BACKGROUND: COVID-19 pandemic emerged worldwide at the end of 2019, causing a severe global public health threat, and smoking is closely related to COVID-19. Previous studies have reported changes in smoking behavior and influencing factors during the COVID-19 period, but none of them explored the main influencing factor and high-risk populations for smoking behavior during this period. METHODS: We conducted a nationwide survey and obtained 21,916 valid data. Logistic regression was used to examine the relationships between each potential influencing factor (sociodemographic characteristics, perceived social support, depression, anxiety, and self-efficacy) and smoking outcomes. Then, variables related to smoking behavior were included based on the results of the multiple logistic regression, and the classification and regression tree (CART) method was used to determine the high-risk population for increased smoking behavior during COVID-19 and the most profound influencing factors on smoking increase. Finally, we used accuracy to evaluated the performance of the tree. RESULTS: The strongest predictor of smoking behavior during the COVID-19 period is acceptance degree of passive smoking. The subgroup with a high acceptation degree of passive smoking, have no smokers smoked around, and a length of smoking of ≥ 30 years is identified as the highest smoking risk (34%). The accuracy of classification and regression tree is 87%. CONCLUSION: The main influencing factor is acceptance degree of passive smoking. More knowledge about the harm of secondhand smoke should be promoted. For high-risk population who smoke, the "mask protection" effect during the COVID-19 pandemic should be fully utilized to encourage smoking cessation.

Smoking behavior detection algorithm based on YOLOv8-MNC.

Introduction: The detection of smoking behavior is an emerging field faced with challenges in identifying small, frequently occluded objects like cigarette butts using existing deep learning technologies. Such challenges have led to unsatisfactory detection accuracy and poor model robustness. Methods: To overcome these issues, this paper introduces a novel smoking detection algorithm, YOLOv8-MNC, which builds on the YOLOv8 network and includes a specialized layer for small target detection. The YOLOv8-MNC algorithm employs three key strategies: (1) It utilizes NWD Loss to mitigate the effects of minor deviations in object positions on IoU, thereby enhancing training accuracy; (2) It incorporates the Multi-head Self-Attention Mechanism (MHSA) to bolster the network's global feature learning capacity; and (3) It implements the lightweight general up-sampling operator CARAFE, in place of conventional nearest-neighbor interpolation up-sampling modules, minimizing feature information loss during the up-sampling process. Results: Experimental results from a customized smoking behavior dataset demonstrate significant improvement in detection accuracy. The YOLOv8-MNC model achieved a detection accuracy of 85.887%, signifying a remarkable increase of 5.7% in the mean Average Precision (mAP@0.5) when compared to the previous algorithm. Discussion: The YOLOv8-MNC algorithm represents a valuable step forward in resolving existing problems in smoking behavior detection. Its enhanced performance in both detection accuracy and robustness indicates potential applicability in related fields, thus illustrating a meaningful advancement in the sphere of smoking behavior detection. Future efforts will focus on refining this technique and exploring its application in broader contexts.