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INTRODUCTION E-cigarette use among youth and young adults remains of public health concern. Pod-based e-cigarettes, including JUUL, significantly changed the e-cigarette landscape in the US. Using an online survey, we explored the socio-behavioral correlates, predisposing factors, and addictive behaviors, among young adult pod-mod users within a University in Maryland, USA. METHODS In total, 112 eligible college students aged 18--24 years, recruited from a University in Maryland, who reported using pod-mods were included in this study. Participants were categorized into current/non-current users based on past- 30-day use. Descriptive statistics were used to analyze participants' responses. RESULTS The mean age of the survey participants was 20.5 ± 1.2 years, 56.3% were female, 48.2% White, and 40.2% reported past-30-day (current) use of pod-mods. The mean age of first experimentation with pod-mods was 17.8 ± 1.4 years, while the mean age of regular use was 18.5 ± 1.4 years, with the majority (67.9%) citing social influence as the reason for initiation. Of the current users, 62.2% owned their own devices, and 82.2% predominantly used JUUL and menthol flavor (37.8%). A significant proportion of current users (73.3%) reported buying pods in person, 45.5% of whom were aged <21 years. Among all participants, 67% had had a past serious quit attempt. Among them, 89.3% neither used nicotine replacement therapy nor prescription medications. Finally, current use (adjusted odds ratio, AOR=4.52; 95% CI: 1.76--11.64), JUUL use (AOR=2.56; 95% CI: 1.08-6.03), and menthol flavor (AOR=6.52; 95% CI: 1.38-30.89) were associated with reduced nicotine autonomy, a measure of addiction. CONCLUSIONS Our findings provide specific data to inform the development of public health interventions targeted at college youth, including the need for more robust cessation support for pod-mod users. [ABSTRACT FROM AUTHOR]

The e-cigarette or vaping product-use-associated lung injury outbreak in the United States has raised concerns about the potential health effects of cannabis vaping, a method of cannabis use that is becoming increasingly popular. We used 2017-2019 Behavioral Risk Factor Surveillance System data to estimate yearly prevalence and trends of past-30-day cannabis use and vaping among US adults. We used multivariable logistic regression to evaluate the associations of cannabis vaping with high-risk behaviors, asthma, and other respiratory symptoms. Our sample size was 160,209 (53,945-2017; 55,475-2018; and 50,789-2019). Past-30-day cannabis use prevalence increased from 10.0% (95% CI, 9.4%-10.7%) in 2017 to 13.4% (12.8%-12.0%) in 2019. Similarly, past-30-day cannabis vaping prevalence increased from 1.0% (0.8%-1.2%) to 2.0% (1.7%-2.2%) over the same period, with the greatest increase, 1.2% to 3.9%, observed among young adults (18-24 years). Individuals who vaped cannabis were more likely to concurrently vape nicotine. Cannabis vaping was associated with increased odds of heavy alcohol use (aOR, 1.95; 95% CI, 1.45-2.63), binge drinking (aOR, 2.82; 95% CI, 2.25-3.54), and other high-risk behaviors (aOR, 2.47; 95% CI, 1.89-3.24). In analyses adjusting for sociodemographic characteristics and body mass index, cannabis vaping was not associated with asthma (aOR, 1.03; 95% CI, 0.64-1.64) or other respiratory symptoms (aOR, 1.08; 95% CI, 0.44-2.63). Adjusting for nicotine vaping did not substantively alter these associations. The prevalence of past-30-day cannabis vaping has increased, particularly among young adults, and was associated with high-risk behaviors. Although there was no association between cannabis vaping and asthma or other respiratory symptoms, the increasing trends of cannabis vaping, particularly among young adults, raise concern and underscore the need for continued surveillance. [ABSTRACT FROM AUTHOR]

Introduction: Cannabis use and cannabis use disorder (CUD) are associated with adverse psychosocial outcomes, but their impact on workplace absenteeism remains poorly understood. Moreover, few studies have examined the role of CUD severity. This study aims to address these gaps by examining the associations between cannabis use recency, frequency, CUD severity, and workplace absenteeism., Methods: Cross-sectional data from a U.S. representative sample of full-time employed adults aged ≥18 from the 2021 to 2022 National Survey on Drug Use and Health (N=46,499) were analyzed. The associations between cannabis use recency, past-month cannabis use frequency, CUD severity, and workplace absenteeism (measured by self-reported number of missed days due to illness/injury and skipped work in the last 30 days) were evaluated using negative binomial regression, adjusting for sociodemographic characteristics and other substance use. Data were analyzed in 2023-2024., Results: An estimated 15.9% of full-time employed adults used cannabis in the past month, with 6.5% meeting CUD criteria. Past-month cannabis use (compared to no lifetime use), more frequent past-month cannabis use (compared to no use in the past month), and each level of CUD (compared to no CUD) were associated with increased incidence of both missing work due to illness/injury and skipping work, with a dose-response relationship observed between CUD severity and skipping work (mild: adjusted incident rate ratio [aIRR]=1.60 [95% confidence interval [CI]=1.24, 2.08]; moderate: aIRR=1.98 [95% CI=1.50, 2.61]); severe (aIRR=2.87 [95% CI=2.12, 3.88])., Conclusions: Individuals with recent and frequent cannabis use and CUD are disproportionately prone to workplace absenteeism. Results support the enforcement of workplace drug prevention and treatment policies., (Copyright © 2024 Elsevier Inc. All rights reserved.)

This study aimed to estimate the trends in the body mass index (BMI) and prevalence of obesity among United States (U.S.) adolescents (10-19 years) and to examine the associations between sociodemographic factors and both BMI and obesity prevalence. The 2007-2020 National Health and Nutrition Examination Survey (NHANES), a nationally representative repeated cross-sectional survey data (n = 9,826) were used. Outcomes included: 1) Mean BMI and 2) obesity (yes/no; defined as BMI ≥95% percentile). Sociodemographic variables included age, sex, race/ethnicity, and poverty income ratio (PIR; low-income <1.3, middle-income ≥1.3 and <3.5, high-income ≥3.5). By accounting for the complex survey design, weighted generalized linear/Poisson models were used to conduct the analyses. Girls constituted 49% of the sample. From 2007-2008 to 2017-2020, there was an increase in BMI and obesity prevalence, particularly among Black and Hispanic adolescents, and those from low- and middle-income families. Additionally, there was an increase in obesity prevalence among both boys and girls. However, there were no significant changes in BMI and obesity prevalence in the other race and ethnic adolescents. Girls had a 12% (Adjusted Prevalence Ratio [APR] = 0.88; 95% CI, 0.81-0.96) lower likelihood of being obese than boys. Compared to White adolescents, Black and Hispanic adolescents had 22% (APR = 1.22; 95% CI, 1.06-1.40) and 19% (APR = 1.19; 95% CI, 1.05-1.36) greater risk of being obese. Compared to high-income families, adolescents from low- and middle-income families had 62% (APR = 1.62; 95% CI, 1.39-1.90) and 47% (APR = 1.47; 95% CI, 1.24-1.76) greater risk of being obese, respectively. The results indicated persistent disparities in obesity prevalence among different race/ethnic and sociodemographic groups. Future obesity intervention should address key disparities by targeting specific race/ethnic adolescents from low-income families and promoting health equality., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Deng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: Both diabetes and smoking significantly increase the risk of cardiovascular disease (CVD). Understanding whether a diagnosis of diabetes can be leveraged to promote smoking cessation is a gap in the literature., Methods: We used data from the US National Health Interview Survey, 2006 to 2018, to investigate the relationship between self-report of diagnosis of diabetes and subsequent smoking abstinence among 142,884 respondents who reported regular smoking at baseline. Effect sizes were presented as hazard ratios (HRs) derived from multivariable Cox regression models adjusted for potential confounders using diabetes as a time-dependent covariate. Subgroup-specific estimates were obtained using interaction terms between diabetes and variables of interest., Results: A self-reported diagnosis of diabetes was associated with smoking abstinence (HR: 1.21; 95% CI: 1.16 to 1.27). The strength of the association varied based on race (P for interaction: 0.004), where it was strongest in African Americans (HR: 1.44; 95% CI: 1.29 to 1.60); income (P for interaction <0.001), where it was strongest in those with a yearly income less than $35,000 (HR: 1.45; 95% CI: 1.36 to 1.53); and educational attainment (P for interaction <0.001), where it was strongest in those who did not attend college (HR: 1.48; 95% CI: 1.40 to 1.57)., Conclusion: Among adults who smoke, a diagnosis of diabetes is significantly associated with subsequent smoking abstinence. The association is strongest in socially disadvantaged demographics, including African Americans, low-income individuals, and those who did not attend college., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Understanding the association between initial experimentation with a tobacco product and subsequent patterns of tobacco use among youth is important to informing prevention activities for youth in the US. We conducted an online survey from August to October 2017 among youth aged 13-18 years. The current analysis focused on respondents reporting initial experimentation with any tobacco product (n = 2,022). Using multinomial logistic regression, we examined the association between first tobacco product tried (cigarettes; cigars including cigarillos, little cigars, and bidis; electronic nicotine delivery systems (ENDS); smokeless and chewing tobacco; or hookah) with subsequent patterns of tobacco use while adjusting for covariates. Of the youth who experimented, 56.8% were non-current tobacco users. Of current tobacco users (n = 934), 13% were exclusive ENDS users, 5.3% exclusive combustible mono-users, 13.4% ENDS plus combustible poly-users, 3.3% combustible product only poly-users, and 8.2% other tobacco poly-users. The most common type of first tobacco product tried was ENDS (44.7%), followed by cigarettes (35.0%) and cigars (8.6%). Those who experimented with combustible tobacco products were less likely to be exclusive ENDS users [Relative Risk Ratio (RRR) = 0.46; 95% CI = 0.28, 0.73 for cigarettes; RRR = 0.32; 95% CI = 0.13, 0.81 for cigars; and RRR = 0.33; 95% CI = 0.14, 0.79 for hookah] when compared to non-current tobacco users (reference group). Tobacco product choices for initial experimentation appear to play a role in subsequent tobacco use patterns among youth. Understanding the reasons behind initial product choice may inform our understanding regarding the reasons for subsequent current tobacco product use, thus informing youth prevention efforts., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 El-Shahawy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: This study explores the association between psychosocial stressors and current e-cigarette use among adolescents in the United States., Methods: We used data from 12,767 participants in the 2019 National Youth Risk Behavioral Survey to examine the association between psychosocial stressors (bullying, sexual assault, safety-related absence from school, depressive symptoms, suicidal ideation, physical altercation, and weapon threats) and past-30-day e-cigarette use using multivariable-adjusted logistic regression models. We examined the association for each stressor and then as a burden score (0-7). To compare the strength of the association between stressors and current e-cigarette use to current combustible cigarette use, we additionally examined the association between each stressor and current combustible cigarette use., Results: Approximately 32.7% reported current e-cigarette use. The weighted prevalence of current e-cigarette use was higher among individuals who experienced stressors than those who did not. For example, bullying (43.9% vs. 29.0%). Similar prevalence patterns were seen among other stressors. Individuals who experienced stressors had significantly higher adjusted odds of current e-cigarette use than those who did not (OR [Odds Ratio] range: 1.47-1.75). Similarly, individuals with higher burden scores had a higher prevalence (zero [20.5%], one [32.8%], two [41.4%], three [49.6%], four to seven [60.9%]) and higher odds of current e-cigarette use (OR range: 1.43-2.73) than those with a score of zero. The strength of the association between the stressors and e-cigarette use was similar to that between the stressors and combustible cigarette use., Conclusion: The study demonstrates a significant association between psychosocial stressors and adolescent e-cigarette use, highlighting the potential importance of interventions, such as targeted school-based programs that address stressors and promote stress management, as possible means of reducing adolescent e-cigarette use. Future research directions include exploring underlying mechanisms linking stressors to e-cigarette use and evaluating the effectiveness of interventions addressing stressors in reducing adolescent e-cigarette use., (© 2023. The Author(s).)

Purpose: Healthcare providers play a critical role in curbing youth tobacco use through screening and counseling. Current rates of tobacco use screening by healthcare providers among US youth are unknown., Methods: We used 2020 National Youth Tobacco Survey data to examine the prevalence of healthcare provider screening for tobacco and e-cigarette use among US youth. Using multivariable logistic regression, we examined the factors associated with being screened for tobacco use., Results: Of 13,434 individuals who reported past 12-month visits to any healthcare professional, 47.5% (44.8%-50.1%) reported being screened for any tobacco use, while 31.5% (29.2%-40.0%) reported e-cigarette-specific screening. The odds of tobacco use screening were lower among males (odds ratio [OR]: 0.81 [0.73-0.89]) and middle schoolers (OR: 0.39 [0.33-0.44]) compared to females and high schoolers, respectively. In addition, non-Hispanic Black (OR: 0.71 [0.56-0.89]), Hispanic (OR: 0.76 [0.63-0.92]), and Asian youth (OR: 0.48 [0.37-0.63]) had lower odds of being screened than non-Hispanic White youth., Discussion: There are missed opportunities in tobacco screening by healthcare providers, particularly among males, middle schoolers, and racial/ethnic minority youth., (Copyright © 2022 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.)

Objective: Individuals with posttraumatic stress disorder (PTSD) smoke at higher rates compared to the general population and experience significant barriers to initiating cessation treatment. Proactive outreach addresses these barriers by directly engaging with smokers and facilitating access to treatment. The objective of the present study was to evaluate a proactive outreach intervention for increasing rates of treatment utilization and abstinence among veteran smokers with and without PTSD., Method: This is a secondary analysis of a randomized controlled trial conducted from 2013 to 2017 that demonstrated the effectiveness of proactive outreach among veterans using Veterans Affairs mental health care services. Electronic medical record data were used to identify participants with ( n = 355) and without ( n = 1,583) a diagnosis of PTSD. Logistic regressions modeled cessation treatment utilization (counseling, nicotine replacement therapy [NRT], and combination treatment) and abstinence (7-day point prevalence and 6-month prolonged at 6- and 12-month follow-ups) among participants randomized to proactive outreach versus usual care in the PTSD and non-PTSD subgroups, respectively., Results: Compared to usual care, proactive outreach increased combined counseling and NRT utilization among participants with PTSD (odds ratio [ OR ] = 26.25, 95% confidence interval [3.43, 201.17]) and without PTSD ( OR = 10.20, [5.21, 19.98]). Proactive outreach also increased 7-day point prevalence abstinence at 12 months among participants with PTSD ( OR = 2.62, [1.16, 5.91]) and without PTSD ( OR = 1.61, [1.11, 2.34])., Conclusions: Proactive outreach increased treatment utilization and abstinence among smokers with and without PTSD. Smokers with PTSD may need additional facilitation to initiate cessation treatment but are receptive when it is offered proactively. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Introduction: People with serious mental illness (SMI) have a high smoking prevalence and low quit rates. Few cessation treatments are tested in smokers with SMI. Mental health (MH) providers are reluctant to address smoking. Proactive tobacco cessation treatment strategies reach out directly to smokers to offer counseling and medication and improve treatment utilization and quit rates. The current study is a secondary analysis of a randomized controlled trial of proactive outreach for tobacco cessation treatment in VA MH patients., Aims and Methods: Participants (N = 1938, 83% male, mean age 55.7) across four recruitment sites, who were current smokers and had a MH visit in the past 12 months, were identified using the electronic medical record. Participants were randomized to Intervention (telephone outreach call plus invitation to engage in MH tailored telephone counseling and assistance obtaining nicotine replacement therapy) or Control (usual care). The current study assessed outcomes in participants with SMI (N = 982)., Results: Compared to the Control group, participants assigned to the Intervention group were more likely to engage in telephone counseling (22% vs. 3%) and use nicotine replacement therapy (51% vs. 41%). Participants in the Intervention group were more likely to be abstinent (7-day point prevalence; 18%) at 12 months than participants in the Control group (11%) but equally likely to make quit attempts., Conclusions: Proactive tobacco cessation treatment is an effective strategy for tobacco users with SMI. Proactive outreach had a particularly strong effect on counseling utilization. Future randomized clinical trials examining proactive tobacco treatment approaches in SMI treatment settings are needed., Implications: Few effective treatment models exist for smokers with SMI. Proactive tobacco cessation outreach with connections to MH tailored telephone counseling and medication promotes tobacco abstinence among smokers with SMI and is an effective treatment strategy for this underserved population., (Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco 2020.)

Importance: The prevalence of the use of electronic cigarettes (e-cigarettes) in the United States has grown rapidly since their introduction to the market more than a decade ago. While several studies have demonstrated an association between combustible cigarette smoking and depression, the association between e-cigarette use and depression has not been thoroughly studied., Objective: To examine the association between e-cigarette use and depression in a nationally representative sample of the adult population in the United States., Design, Setting, and Participants: Cross-sectional study of the Behavioral Risk Factor Surveillance System database, 2016 to 2017. The Behavioral Risk Factor Surveillance System is the largest national telephone-based survey of randomly sampled adults in the United States. A total of 892 394 participants with information on e-cigarette use and depression were included. Data analysis was conducted in May 2019., Exposures: Electronic cigarette use status defined by self-report as never, former, or current use., Main Outcomes and Measures: Self-reported history of a clinical diagnosis of depression., Results: Of the 892 394 participants (414 326 [29.0%] aged ≥60 years; 502 448 [51.3%] women), there were 28 736 (4.4%) current e-cigarette users, of whom 13 071 (62.1%) were aged between 18 and 39 years. Compared with never e-cigarette users, current e-cigarette users were more likely to be single, male, younger than 40 years, and current combustible cigarette smokers (single, 120 797 [24.3%] vs 10 517 [48.4%]; men, 318 970 [46.6%] vs 14 962 [60.1%]; aged 18-39 years, 129 085 [32.2%] vs 13 071 [62.1%]; current combustible cigarette use, 217 895 [7.9%] vs 8823 [51.8%]). In multivariable adjusted models, former e-cigarette users had 1.60-fold (95% CI, 1.54-1.67) higher odds of reporting a history of clinical diagnosis of depression than never users, whereas current e-cigarette users had 2.10 (95% CI, 1.98-2.23) times higher odds. Additionally, higher odds of reporting depression were observed with increased frequency of use among current e-cigarette users compared with never users (daily use: odds ratio, 2.39; 95% CI, 2.19-2.61; occasional use: odds ratio, 1.96; 95% CI, 1.82-2.10). Similar results were seen in subgroup analyses by sex, race/ethnicity, smoking status, and student status., Conclusions and Relevance: This study found a significant cross-sectional association between e-cigarette use and depression, which highlights the need for prospective studies analyzing the longitudinal risk of depression with e-cigarette use. If confirmed by other study designs, the potential mental health consequences may have regulatory implications for novel tobacco products.

Objective: To examine the association between state-level tobacco control measures and current use estimates of both e-cigarettes and cigarettes, while accounting for socio-demographic correlates., Methods: Using the 2012-2013 and 2013-2014 National Adult Tobacco Survey (NATS), we assessed prevalence estimates of US adults' e-cigarette and cigarette current use. Four state groups were created based on the combined state-specific prevalence of both products: low cigarette/e-cigarette (n = 15), high cigarette/e-cigarette (n = 16), high cigarette/low e-cigarette (n = 11), and low cigarette/high e-cigarette) (n = 9). To evaluate the implementation of state-level tobacco control measures, Tobacco Control Index (TCI) was calculated using the State of Tobacco Control annual reports for 2012 and 2013. Multinomial logistic regression models were used to examine differences among the four groups on socio-demographic factors and TCI. Low cigarette/e-cigarette group was used as the referent group., Results: Current use estimates of each product varied substantially by state; current e-cigarette use was highest in Oklahoma (10.3%) and lowest in Delaware (2.7%), and current cigarette use was highest in West Virginia (26.1%), and lowest in Vermont (12.6%). Compared to low cigarette/e-cigarette, all other US-state categories had significantly lower TCI scores (high cigarette/e-cigarette: adjusted Relative Risk Ratio [aRRR] = 0.61; 95% confidence interval [CI]: 0.60-0.61, high cigarette/low e-cigarette: aRRR = 0.74; 95% CI: 0.73-0.74, and low cigarette/high e-cigarette: aRRR = 0.72; 95% CI: 0.71-073)., Conclusions: Enforcing existing tobacco control measures likely interacts with e-cigarette use despite being cigarette-focused. Continuing to monitor e-cigarette use is critical to establish baseline use and evaluate future e-cigarette specific federal and state-level tobacco regulatory actions while accounting for the existing tobacco control environment., Implications: This study investigates state-level current use estimates of e-cigarettes and cigarettes among US adults; and their association with four existing tobacco control measures. The overall score of these measures was negatively associated with state-level current use estimates such that states with low current e-cigarette and cigarette use had the highest mean overall score. This study assesses the potential relationship between existing state-level tobacco control measures and e-cigarette use and calls for improving the enforcement of the known-to-work tobacco control measures across all US states, while developing evidence-based regulations and interventions specific to e-cigarettes within the existing US tobacco use environment.