Tobacco Induced Diseases最新文献

Introduction: Electronic cigarettes are battery-operated devices that allow users to 'vape' flavored solutions including nicotine. The prevalence of users of e-cigarettes with different flavors, is not known in the Medina region in Saudi Arabia. Thus, the study aimed to assess the prevalence and characteristics of e-cigarette smokers in Medina region. Additionally, this study aimed to determine the popular flavors and the most common reasons for smoking e-cigarettes among young adults.

Methods: This cross-sectional study was conducted between 1 February and 19 March 2024 using an online questionnaire via convenience sampling. The total number of participants was 388, including males and females aged ≥18 years.

Results: The study findings showed that 78.2 % of the e-cigarette smokers were young adults, while 58.4 % of the participants aged 18-29 years preferred fruit flavors. Additionally, the majority of young adults used e-cigarettes for reducing stress and enjoyment, corresponding to 40.6 % and 31.7 % of participants, respectively.

Conclusions: Our study is useful for identifying the preferences towards e-cigarette usage within a population and monitoring emerging trends, particularly among young adults. Researching regional preferences for e-cigarette flavors might help to direct future studies into the health effects of various flavorings.

Introduction: Electronic cigarettes (e-cigarettes) have gained increasing popularity among young adults worldwide, particularly among college students who represent a key target population for e-cigarette marketing. Understanding cognitive factors that influence e-cigarette use susceptibility is critical for developing effective prevention strategies. This study aimed to develop and validate a scale based on the Protection Motivation Theory (PMT) to assess cognitive factors related to e-cigarette use susceptibility among Chinese college students for prevention purposes.

Methods: A cross-sectional survey design was employed and data were collected among 303 students aged 18-24 years from universities in China during February 2023. A 21-item PMT scale was adapted from a previous study on Chinese youth tobacco use. Construct validity was assessed using confirmatory factor analysis (CFA). Internal consistency reliability was evaluated using Cronbach's α. Structural equation modeling was used to examine associations between PMT constructs and e-cigarette use susceptibility. Statistical significance was set at p<0.05, and all tests were 2-tailed. Power calculations indicated adequate sample size for the planned analyses. Concurrent validity was examined by correlating PMT constructs with e-cigarette use susceptibility.

Results: After removing one item, the final 20-item scale demonstrated good model fit in the CFA (GFI=0.917, CFI=0.933, RMSEA=0.055). Internal reliability was acceptable to good (Cronbach's α=0.52-0.83). The overall Cronbach's α coefficient was 0.831. All PMT constructs were significantly correlated with e-cigarette use susceptibility in the expected directions (p<0.05).

Conclusions: The PMT-based scale is a valid and reliable measure to investigate e-cigarette use related cognitions among Chinese college students, and can be used as a tool to guide prevention efforts. The study supports the utility of applying PMT to e-cigarette research in different socio-cultural contexts.

Introduction: China, the world's largest tobacco market, has raised concerns due to e-cigarettes' health risks and rising youth usage. Despite a decade of regulatory policies, their effectiveness remains uncertain. This study examines trends in e-cigarette discourse on Weibo (2016-2025), analyzing discussion volume shifts and the impact of various topics on public engagement.

Methods: This study employs a hybrid computational approach integrating topic modeling, LLM-assisted annotation, and quantitative analysis to examine the evolution of e-cigarette discussions on Weibo (2015-2025) and topic dissemination effects (n=129769). LDA modeling identify 10 topics, followed by DeepSeek-V3-assisted classification. Linear regression in SPSS analyzed relationships between topic categories and social media engagement metrics (reposts/comments/likes) at 95% confidence intervals.

Results: Findings reveal 2020 as a key year of change: pro-vaping posts declined while anti-vaping content increased. Despite reduced volume, pro-vaping material maintained significant digital influence. Pre-policy, marketing content (p<0.01), health effects (p<0.01) and regulation (p<0.01) drove engagement. Post-policy, marketing lost engagement impact, while 'user experience' posts gained traction, significantly correlating with all interactions (all p<0.05). This indicates regulations were less effective against user-generated content, with pro-vaping messaging shifting towards peer-driven channels. Crucially, influencers consistently triggered strong engagement throughout the period (p<0.01) despite lower post volume, remaining key discourse drivers.

Conclusions: Although China is strengthening its control over e-cigarettes, the results of our study indicate that this control remains limited. We advocate for more robust regulation of social media content, particularly concerning the management of celebrities and influencers, as well as the sharing of e-cigarette use experiences. However, the current regulatory framework enforced by the State Tobacco Monopoly Administration has proven inadequate for widespread and effective governance. We suggest that regulatory authority be shared with public health agencies in order to better integrate e-cigarette regulation with broader public health objectives.

Introduction: Smoking has been identified as a potential risk factor for adverse COVID-19 outcomes. This study aimed to investigate the association between long-term smoking cessation and COVID-19 outcomes.

Methods: In this nationwide, cross-sectional online survey conducted in China (January-February 2023), 22709 adults with COVID-19, confirmed by nucleic acid amplification test (NAAT) or SARS-CoV-2 antigen testing, were included. Smoking status was self-reported and classified as never smokers, long-term ex-smokers (≥10 years), ex-smokers (<10 years), and current smokers. COVID-19 outcomes, including pneumonia, hospitalization, and severe COVID-19, were compared across these groups. Logistic regression models were used to adjust for potential confounders. Sensitivity analyses included all self-reported cases irrespective of test confirmation.

Results: Among 22709 COVID-19-positive participants, current smokers and ex-smokers <10 years exhibited significantly higher proportion of pneumonia, hospitalization, and severe COVID-19 than never smokers. Current smokers (AOR=3.18; 95% CI: 2.90-3.48) and ex-smokers quit <10 years (AOR=3.48; 95% CI: 2.96-4.09) had increased odds of pneumonia, whereas long-term ex-smokers showed no elevated risk (AOR=1.12; 95% CI: 0.45-2.41). These associations were consistent in sensitivity analyses. Other factors significantly associated with pneumonia included sex, education level, residence, obesity, income, and chronic conditions.

Conclusions: Long-term smoking cessation was not associated with an elevated risk of COVID-19-related pneumonia compared to never smokers, whereas ex-smokers (<10 years) and current smokers remained high-risk groups. These findings support the potential benefits of sustained cessation, although further longitudinal studies are needed to confirm and extend these findings.

Introduction: Limited data exist on how home smoking and e-cigarette use restrictions influence patterns of cigarette and e-cigarette use among individuals who use both products. This study examined the association between home restrictions and the use of cigarettes and e-cigarettes among dual users of these two products.

Methods: We conducted a secondary analysis of data from the Adult Consumers of Tobacco Study (ACTS), an online, nationwide survey administered during 2020-2021. A sub-sample of 250 dual users of cigarettes and e-cigarettes was included in this analysis. Outcome variables were concurrent use behaviors, categorized as predominant smokers (daily smoking, e-cigarette use some days), equivalent users (either daily or some days use of both products), and predominant e-cigarette users (daily e-cigarette use, smoking some days), as well as e-cigarette use frequency (daily vs some days). Primary explanatory variables were home smoking and e-cigarette use restrictions (both categorized as complete, partial, or no restrictions). Multivariable logistic regression was used to examine associations between restrictions and concurrent use behaviors.

Results: Nearly half (46.8%) of dual users reported having complete smoking restrictions in their homes, complete e-cigarette use restrictions (12.8%), and complete restrictions on both (11.2%). Dual users reported having complete home smoking restrictions (vs no restrictions) were more than two times more likely to be predominant e-cigarette users versus equivalent users or predominant smokers (AOR=2.60; 95% CI: 1.30-5.30), after controlling for home e-cigarette use restrictions and other covariates. Neither partial smoking restrictions nor partial e-cigarette use restrictions were associated with concurrent use behaviors.

Conclusions: Small proportions of dual users reported having complete smoking and e-cigarette use restrictions adopted in their homes, suggesting a need for promoting the adoption of such restrictions. Moreover, how and why home smoking and e-cigarette use restrictions differentially impact use behaviors warrant additional investigation.

Introduction: The high prevalence of tobacco use in China has led to a heavy social burden. There have been many studies on smoking behavior in China, but few have explored it from the perspective of behavioral economics. This study investigated the association between time-inconsistent preferences and smoking behavior.

Methods: We conducted a household-based cross-sectional survey in Sichuan Province, southwestern China, in 2022. Participants were selected using multistage stratified sampling. Data were collected through face-to-face, questionnaire-based household surveys, yielding 5446 valid responses. The smoking status of all participants was confirmed by cotinine test. Descriptive statistical analysis was performed on variables such as sociodemographic variables and time-inconsistent preference, and a binary logistic regression model was used to explore the relationship between time-inconsistent preference and smoking behavior.

Results: The smoking rate of the survey participants was 23.87%, among which that of drinkers was 45.90%, which was significantly higher than that of non-drinkers (15.10%); 712 participants (13.07%) both smoked and drank, and the average time-inconsistent preference (time-inconsistent preferences measured over 1-month and 12-month delay periods) of smokers (mean ± standard deviation: 0.91 ± 0.14) was significantly lower than that of non-smokers (0.95 ± 0.11, p<0.001). Thus, those with weaker time-inconsistent preferences were less likely to smoke (p<0.001, adjusted odds ratio, AOR=0.276; 95% CI: 0.140-0.544). This trend was significant in both drinkers and non-drinkers, with AOR of 0.253 (95% CI: 0.093-0.693) and 0.26 (95% CI: 0.102-0.661), respectively.

Conclusions: Weaker time-inconsistent preferences show a significant negative association with smoking behavior in this Chinese sample, independent of alcohol consumption. Commitment mechanisms targeting time-inconsistent preferences may hold promise for smoking cessation interventions, although efficacy requires validation through randomized trials.

Introduction: Smoking cessation is a significant challenge, and various factors influence the success rates. Understanding the factors affecting cessation outcomes can guide more effective intervention strategies. This study compares the efficacy of a general outpatient cessation program versus a free cessation program, with subgroup analyses based on medication type (bupropion vs varenicline), aiming to identify factors associated with successful smoking cessation in outpatient settings.

Methods: We analyzed data from 356 patients visiting our smoking cessation clinic between January 2018 and June 2022, with random allocation into two groups via computerized random number table upon enrollment: Group A (general outpatient intervention, n=188) and Group B (free cessation program, n=168). Both groups were further subdivided based on the use of bupropion (A1, B1) or varenicline (A2, B2). Factors such as demographic data, nicotine dependence, smoking cessation confidence, exhaled carbon monoxide, and smoking cessation success (7-day point prevalence abstinence rate [PPAR] and 3-month continuous quitting rate [CQR]) were analyzed. To ensure comprehensive results, we performed an intention-to-treat (ITT) analysis, including participants who dropped out or did not complete the study as failures in the smoking cessation outcome.

Results: There were no significant differences between groups A and B in demographics, smoking behavior, or medication, except for occupation and duration of cigarette smoking. Group B had lower nicotine dependence but comparable smoking cessation outcomes to Group A. Factors associated with successful cessation included being older, married, employed full-time, smoking ≤20 cigarettes/day, and using varenicline. The CQR of Group A2 was 9.36% higher than that of Group A1. The PPAR and CQR of Group B2 were 16.66% and 17.93% higher than those of Group B1, respectively. However, there were no significant differences in PPAR and CQR between Group A2 and Group B2.

Conclusions: Varenicline use, specific sociodemographic characteristics (aged >50 years, married, full-time employment), and less severe smoking behavior (≤20 cigarettes/day, ≤25 years duration, ≤600 pack-year) are key determinants of successful smoking cessation in outpatient settings. Varenicline use was associated with significantly higher cessation rates compared to bupropion within both intervention models. The free program incorporating varenicline (B2) demonstrated particularly high success rates.

Introduction: Smoking and secondhand smoke are major global health threats, significantly contributing to the burden of ischemic heart disease (IHD). Despite the implementation of tobacco control policies worldwide, limited evidence exists on the health impacts in Shanghai. This study evaluates the effects of Shanghai's 2017 smoke-free legislation on IHD hospitalization and mortality rates.

Methods: We conducted Interrupted Time Series (ITS) method to analyze monthly data on IHD hospitalizations and mortality among registered residents of Shanghai from July 2013 to December 2021. Age-standardized rate, Poisson and negative binomial regression models were performed to control for covariates.

Results: We included 898535 hospitalizations and 180658 deaths caused by IHD from July 2013 to December 2021 in Shanghai. Following policy implementation, there was a significant immediate increase (β=8.29; 95% CI: 2.45-14.13) and post-trend decline (β= -0.73; 95% CI: -0.93 - -0.54) in IHD hospitalization, which is estimated to have prevented approximately 890 hospitalizations per year. Subgroup analysis revealed that the long-term decrease was more pronounced in individuals aged ≥65 years (β= -1.72; 95% CI: -2.21 - -1.24), compared to those aged 35-64 years (β= -0.33; 95% CI: -0.42 - -0.25). However, mortality rates showed no statistically significant immediate (β= -0.90, 95% CI: -4.76-2.95) or long-term changes (β= -0.0075; 95% CI: -0.14-0.12).

Conclusions: Shanghai's comprehensive smoke-free legislation appears to be associated with a significant long-term reduction in hospitalization rates and a modest decrease in mortality rates from ischemic heart disease, particularly among older adults. These findings support the potential cardiovascular health benefits of smoke-free policies, which provide useful evidence for other cities considering the adoption or reinforcement of comprehensive public smoking bans to help reduce the burden of cardiovascular disease and improve population health.

Introduction: Gender-specific variations in hormonal profiles, adipose tissue distribution, and metabolic pathways may differentially modulate the health impacts of smoking and alcohol use. Current population-based studies on the impact of smoking and alcohol consumption on cardiometabolic diseases (CMD) and multimorbidity (CMM) often lack gender-stratified analyses, thereby limiting the evidence base for gender-tailored preventive strategies.

Methods: This population-based cross-sectional study used data from the 2020 China Health and Retirement Longitudinal Study (CHARLS), and a total of 11447 participants were included in the analysis. Multinomial logistic regression was conducted to assess behavioral risk factors, with interaction terms evaluating effect modification by gender.

Results: The prevalence was 16.67% for CMD and 5.66% for CMM. Participants who smoked were more likely to report CMM than those who did not smoke (OR=2.70, p<0.05). Smoking was significantly associated with the prevalence of CMD in females (AOR=1.34, p<0.05), but not in males (p=0.556). Moreover, female smokers were more likely to report CMM compared to male smokers (AOR_females=3.53, AOR_males=2.02, p<0.05). No significant associations were found between alcohol consumption and the prevalence of CMD or CMM, nor were any gender-specific differences observed.

Conclusions: Smoking may have a potential gender-specific effect on the risk of CMD and CMM, with female smokers exhibiting a higher prevalence of CMM than males. This highlights the need to integrate gender considerations into chronic disease prevention frameworks.