Tobacco Use Insights最新文献

Background: Waterpipe tobacco smoking (WTS) is a popular mode of nicotine delivery among young people. We examined the trends and disparities in WTS from 2013 to 2021 among US adolescents and adults.

Methods: Data were from Wave 1 (initially conducted among 32 320 adults and 13 651 adolescents) to Wave 6 (2013-2021) of the Population Assessment of Tobacco and Health Study. We assessed the weighted prevalence of ever and current (past 30-day) WTS for adults and adolescents across waves stratified by demographics.

Results: From 2013-2021 among adolescents, the prevalence of ever and current WTS decreased by 86.5% (7.4% to 1.00%; p = 0.0364) and 97.1% (1.65% to 0.05%; p = 0.0012), respectively. Despite the decreasing trends among adolescents across all waves, females had a higher prevalence of ever and current WTS compared to males (p 's < 0.001 for all trends). Hispanics had the highest prevalence of ever WTS compared to other races/ethnicities (p 's < 0.001). Adolescents aged 15-17 had a higher (except Wave 6) prevalence of ever and current WTS than 12-14 years old (p 's < 0.001). For adults, the prevalence of ever WTS increased by 27.4% (16.39% to 20.92%; p = 0.0006), and current WTS decreased by 45.5% (2.19% to 1.24%; p = 0.0012). Young adults aged 18-24 experienced increasing trends in WTS and had the highest prevalence of ever and current WTS compared to other age groups (p 's < 0.001) across all waves.

Conclusions: Our study indicates a notable decrease in adolescent WTS prevalence from 2013 to 2021 but an increase of ever WTS among adults. Demographic differences underscore disparities in WTS, calling for tailored interventions.

Introduction: The FDA oversees regulatory aspects of all U.S. tobacco products. Understanding the impact of emerging health trends and incidents associated with various tobacco and nicotine products is vital for public health. This study utilizes the FDA's Tobacco Product Problem Reports (TPPRs) to characterize and track adverse health events (AHEs) associated with tobacco and nicotine products over time, considering the impact of EVALI and the COVID-19 pandemic.

Methods: FDA TPPRs from 2017-2022 provided information on AHEs related to various tobacco products. After data cleaning, 839 reports were categorized by two independent coders based on affected health category, frequency of AHEs reports, and proportion of AHEs per each health category. Additionally, variations in AHEs over time were assessed, considering major health events like EVALI and the COVID-19 pandemic.

Results: Among the 839 reports, electronic cigarettes (e-cigarettes) were the primary product of concern, comprising 90.6% (n = 760) of all reports, surpassing traditional cigarettes (5.1%; n = 43) and other products. Notably, 45.6% of reports (n = 383) identified the neurological system as the most frequently mentioned health category, each reporting at least one AHE. This was followed by the respiratory (39.1%; n = 328) and digestive (10.7%; n = 90) systems. Among all reported AHEs, respiratory system issues were most frequent (25.9%; n = 512), closely followed by neurological (25.2%; n = 499) and digestive (6.6%; n = 131) concerns. Most reports occurred in 2019 (65.7%; n = 551), coinciding with the EVALI outbreak, with a subsequent decline post-Q3 2019, highlighting the potential impact of specific health crises on reporting trends.

Conclusion: E-cigarettes dominated adverse health reports, particularly affecting the neurological and respiratory systems, with a peak in 2019. Our findings provide insights to regulatory entities and future research, enhancing understanding of AHEs in lesser-explored bodily systems, such as the neurological and digestive systems. This study emphasizes the need for ongoing and improved surveillance of emerging tobacco products to protect public health.

Background: Electronic nicotine delivery systems ("e-cigarettes") are the nicotine product most commonly used by adolescents. Research, treatment, and policy could benefit from measures of adolescent e-cigarette beliefs about outcomes of use (ie, expectancies). In the current study, we developed and tested an adolescent electronic nicotine vaping expectancy measure.

Methods: A focus group with adolescents evaluated potential e-cigarette expectancy items. A panel of national experts assisted in revision of these items. Finally, items were administered to a sample of adolescents 14-17 years old (N = 267, Mean age 15.6, SD = 1.1, 50.9% Female, 50.2% Non-Hispanic White, 22.5% Non-Hispanic Black, 14.2% Hispanic) in a large Southeastern metropolitan area in the United States.

Results: Exploratory Factor Analysis revealed a four factor solution: Negative Consequences (Cronbach's α = .92); Positive Reinforcement (α = .83); Negative Affect Reduction (α = .95); and Weight Control (α = .89). Subscales were significantly correlated with vaping susceptibility and lifetime vaping. Subscales successfully differentiated susceptible adolescents from confirmed non-susceptible adolescents, with susceptible adolescents reporting more positive expectancies, eg, Positive Reinforcement, M = 5.0, SD = 2.0 vs M = 3.0, SD = 2.1, P < .001, η² = 0.19, and less negative expectancies, M = 5.5, SD = 2.3 vs M = 6.5, SD = 2.6, P = .001, η² = 0.04. Similar results were found comparing adolescents who have never vaped nicotine with those who have vaped nicotine. Hierarchical linear regression demonstrated subscales were significant predictors of lifetime vaping after controlling for demographics, vaping ad exposure, and peer/family vaping.

Conclusions: A preliminary version of an adolescent expectancy measure appears reliable and valid based on expert input and pilot testing with adolescents. Promising results were found in the domains of concurrent validity, discriminant validity, and incremental validity. Future research and evaluation efforts will be able to use this tool to further prevention and treatment goals.

Introduction: Tobacco companies conduct and fund research. They are not always interested in open-ended research. They promote their interests through public relations campaigns. It's a proven fact that they influence the scientific community by impairing scientific reputation, especially in the case of health-related research.

Methods: To obtain a comprehensive picture of research and funding activities of the tobacco industry as well as studies about the tobacco industry, respective scientific articles were analyzed in terms of temporal aspects, research areas, networking, and funding sources using established and advanced bibliometric methods.

Results: We found the foci of publications with tobacco industry involvement or funding were mainly in chemistry, toxicology, pharmacology, and agricultural sciences. Health-related scopes occurred much less frequently. In contrast, health and medical sciences were the main focus of publications on the tobacco industry. The Chinese state-owned CNTC was the most research-involved tobacco company and often networked with Chinese academic institutions. Whereas, Western universities, on the other hand, collaborated with tobacco companies to a much lesser extent.

Conclusion: Conflicts of interest of researchers or academic institutions with the tobacco industry occur repeatedly. That is highly problematic and should not be ignored by the scientific community. The science and the public should be skeptical about tobacco industry-supported research.

Objective: To estimate the economic costs of selected tobacco-related illnesses (TRI) in Kenya in 2022.

Research design and methods: This study was conducted in 2 phases. Phase 1, conducted between 2021 and 2022, entailed conducting a cross-sectional study conducted in 4 national public referral hospitals in Kenya. Patients with cardiovascular disease, cancer, chronic obstructive pulmonary disease, or tuberculosis were interviewed to compute the indirect and direct medical costs related to the illness. Activity-Based Costing approach was used to capture costs for services along the continuum of care pathway. In the second phase, the Tobacco Attributable Factor was used to estimate the direct, indirect, and ultimately economic cost due to tobacco smoking.

Results: The estimated health care cost attributed to tobacco use in Kenya is US$396,107,364. Among TRIs included in the study, myocardial infarction had the highest health care cost at US$158,687,627, followed by peripheral arterial disease and stroke with health care cost of US$64,723,181 and US$44,746,700 respectively. The main cost driver across all the illnesses is the cost for medication accounting for over 90% of the total health care cost. The productivity losses from the diseases ranged between US$148 to US$360 and accounted for 27% to 48% of the economic costs. The total cost attributable to tobacco use to Kenya's economy for the selected TRIs was between US$544.74 million and US$756.22 million.

Conclusions/interpretation: Tobacco related illnesses impose a significant economic burden as reported for direct and indirect costs. These findings underscore the need for strengthened implementation of the provision of the Framework Convention on Tobacco Control and the Tobacco Control Act (2007) to facilitate a reduction in tobacco consumption in the population.

Background: Supporting smoking cessation at pharmacies can be challenging owing to difficulties in recruiting smokers to participate in cessation programs, insufficient communication skills among pharmacists, and lack of knowledge and self-efficacy in successfully quitting smoking in Japan.

Objective: This study evaluates the effectiveness of a smoking cessation training program on community pharmacists' knowledge, attitude, and self-efficacy in supporting smoking cessation.

Methods: The study, conducted in Japanese pharmacies with 100 community pharmacists, employed a quasi-experimental design. Two online training programs were implemented. Participants completed a web-based survey assessing their knowledge, attitude, and self-efficacy in supporting smoking cessation before, immediately after, and 1 year after the training program. A two-way analysis of variance with a mixed model was used to examine score changes at each time point.

Results: Total knowledge scores significantly increased between baseline and immediately after training and baseline and 1 year after training. The total attitude scores between baseline and immediately after training differed significantly. However, no differences were noted between baseline and 1 year after training. Total self-efficacy scores significantly increased at baseline, immediately after training, and between baseline and 1 year after training. Despite no significant interactions between the programs, there was a partial interaction effect on knowledge, with only the customized program having items whose knowledge levels improved after 1 year.

Conclusion and relevance: The training program improved community pharmacists' knowledge, attitude, and self-efficacy regarding smoking cessation support. The customized program must be reinforced to improve support performance and maintain attitude.

Background: Tobacco usage and obesity remain critical public health issues in the United States. This study examined the relationship between smoking behaviors, specifically-cigarettes per day (CPD) and motivations to smoke-and body mass index (BMI). We hypothesized that motivations related to food or stress, as well as a higher CPD, will be positively associated with BMI.

Methodology: We analyzed the electronic medical records of 204 patients from the Johns Hopkins' Tobacco Treatment and Cancer Screening Clinic (TTCSC) between January and April 2022. Demographic information, smoking behavior, CPD, and motivations to smoke were recorded. Multiple linear regression analysis was performed.

Results: We found no statistical significance between motivations to smoke, CPD, and BMI. However, the age at a patient's first visit to the TTCSC was negatively associated with BMI (B = -0.152, P < 0.001).

Conclusions: Smoking behaviors were not significantly related to BMI in our sample. It is advisable for clinicians working in tobacco cessation clinics to consider the BMI of individuals who present for cessation services, especially for younger individuals who smoke. They may be more likely to have an elevated BMI at presentation.

Background: This study described the marketing strategies tobacco companies use to advertise tobacco products to the Queer community. Methods: In this secondary qualitative analysis, 15 Queer participants were interviewed to explore their life experiences with tobacco product advertisements during the early days of the COVID-19 pandemic. Results: Participants self-reported as male (n = 5), followed by female (n = 4), gender non-binary (n = 4) and, transgender (n = 2). In addition, most participants identified as Black/African American (n = 7) or White (n = 7). Many participants identified as Bisexual (n = 5) or Queer (n = 4). Using narrative analysis, the themes for this study were: (1) tobacco and vaping companies target minoritized and Queer people; (2) tobacco and vape companies maintain their presence by sponsoring local Lesbian, gay, bisexual, transgender, questioning, intersex, asexual, and other community (LGBTQIA+) bars and Pride events, often through giveaways and coupons; and (3) the use of social media influencers represents a new social marketing technique. As a result, Queer participants were more likely to encounter many different types of advertisements from tobacco companies and, most recently, social media influencers. Conclusion: Social media influencers are a new factor that needs further study to understand the new tobacco advertising landscape.

Background: Tobacco cannabis co-use is common and becoming more prevalent. Frequent and heavy users of cannabis may struggle to quit smoking. Quitlines offer free cessation treatment in the United States and 25% of quitline callers may also be cannabis users. The present paper describes a randomized pilot study of a tailored intervention for cannabis and cigarette co-users. The intervention combines the quitline smoking cessation treatment with a motivational enhancement therapy-based cannabis intervention. Methods: The randomized pilot study was conducted within four state-funded quitlines with quitline coaches as interventionists. 102 quitline callers who were cannabis and cigarette co-users were randomized to receive treatment as usual (TAU) or the new Quitline Check-Up (QLCU) intervention. Outcomes were collected 90 days post-randomization. Primary outcomes included feasibility and acceptability of delivering the QLCU in the quitline setting. Secondary outcomes included 7-day point prevalence tobacco abstinence, past 30-day cannabis use, and Cannabis Use Disorder Identification Test scores. Results: Study participants were heavy cannabis users, averaging 25 days of use in the past 30; nearly 70% used at a level considered hazardous. Fidelity ratings indicated coaches were successful at delivering the intervention. Treatment engagement was high for both groups (TAU m = 3.4 calls; QLCU m = 3.6 calls) as was treatment satisfaction. Intent-to-treat quit rates (with survey non-responders classified as smokers) were 28.6% for the TAU control group and 24.5% for the QLCU group (P = .45). Discussion: Hazardous cannabis use rates were high in this sample of tobacco cannabis co-users calling quitlines to quit smoking. The intervention for co-users was acceptable and feasible to deliver. No improvements in tobacco cessation outcomes were observed. Pragmatic intervention development within a real-world clinical setting can streamline the intervention development process. More research is needed on tobacco cannabis co-users and who can benefit from a tailored intervention. Registered: ClinicalTrials.gov NCT04737772, February 4, 2021.

Objective: Cannabis is frequently co-used with tobacco/nicotine products, especially among young adults. Little is known about the effects of this co-use on cannabis cessation outcomes. Within a sample of young adults using cannabis frequently (current use of ≥5 days/week in the past 3 months), this study aimed to (a) document sources of exposure to tobacco/nicotine products, whether used simultaneously with cannabis or on different occasions, (b) examine if the level of cumulated exposure to tobacco/nicotine (self-reported or from biochemical testing) could predict time to cannabis lapse during a cannabis abstinence period, and (c) explore the relationship between nicotine/tobacco exposure and time to cannabis lapse according to tobacco cigarette smoking status. Method: Urine cotinine measures and self-reported data on use of different tobacco/nicotine products, collected from 32 participants (aged 19 to 23), were analyzed to predict time to lapse during a 2-week period of attempted abstinence from cannabis, controlling for cannabis dependence and sex. Results: Half of participants (56.3%) used at least one tobacco/nicotine product. Higher urine cotinine, representing higher cumulated tobacco/nicotine exposure, was related to a higher risk of lapsing (Hazard Ratio [HR] = 1.64; 95%CI [1.04, 2.58]). The risk of lapsing was even higher ([HR] = 3.46; 95%CI [1.17, 10.25]) among heavily tobacco/nicotine exposed (>600 ng/mL, urine cotinine) participants than among unexposed (<50 ng/mL) or lightly/moderately exposed (50-600 ng/mL) participants. Among those smoking cigarettes (solely or in combination with other products), there was no relation between cotinine level and time to lapse, likely due to a reduced variability in abstinence probability and a high likelihood of lapse observed for higher cotinine levels, mainly achieved by cigarette use. Conclusions: With a rapidly changing landscape of tobacco/nicotine use, our results underscore the need to consider all sources of tobacco/nicotine exposure to fully understand the specific and cumulative contributions of tobacco/nicotine to cannabis cessation outcomes.