Objectives: Given the need to understand e-cigarette retail and its impact, we examined so- ciodemographic, tobacco and marijuana use, and e-cigarette retail experiences as correlates of (1) past 30-day e-cigarette use, (2) past 30-day advertising/media exposure, and (3) point-of-sale age verification among young adults. Methods: We analyzed baseline survey data (September- December, 2018) among 3006 young adults (ages 18-34) in 6 metropolitan areas (Atlanta, Boston, Minneapolis, Oklahoma City, San Diego, Seattle) in a 2-year longitudinal study. Results: In this sample (Mage = 24.6, 42.3% male, 71.6% white, 11.4% Hispanic), 37.7% (N = 1133) were past 30-day e-cigarette users; 68.6% (N = 2062; non-users: 66.0%, users: 72.9%) reported past 30-day e-cigarette-related advertising/media exposure. Among e-cigarette users, vape shops were the most common source of e-cigarettes (44.7%) followed by online (18.2%). Among users, 34.2% were "almost always" asked for age verification. In multilevel logistic regression, e-cigarette use and advertising/media exposure were correlated (and both correlated with being younger). E- cigarette use also correlated with other tobacco product and marijuana use (and being male and white). Infrequent age verification correlated with commonly purchasing e-cigarettes online (and being older and black). Conclusions: Increased efforts are needed to reduce young adult advertising/media exposure and increase retailer compliance among retailers, particularly online and vape shops.
Background: The 16.9 million cancer survivors in the United States are at increased risk for comorbidities and recurrence. However, this risk may be attenuated by a healthy lifestyle. This study describes health behaviors by cancer history to inform behavior change priorities.Methods: We analyzed 2013-2017 data from the National Health Interview Survey. There were 164,692 adults, of whom 12,648 reported a cancer history. We calculated prevalence of smoking, physical activity, alcohol consumption, body mass index (BMI), and sleep duration by cancer history, age, and cancer site. We conducted logistic regression to determine odds of meeting lifestyle recommendations by cancer history.Results: Overall, those with a cancer history were less likely to report current smoking (14.1% vs. 16.8%) and moderate/heavy drinking (18.8% vs. 21.9%) than those without a cancer history.However, a lower percentage of cancer survivors met physical activity guidelines (14.2% vs. 21.1%) or reported a healthy BMI (31.6% vs. 34.7%) compared with those without a cancer history. Cancer survivors were more likely to report excessive sleep (6.8% vs. 3.6%). In adjusted logistic regression, survivors were more likely to meet recommendations on smoking, physical activity, and BMI but were less likely to meet alcohol recommendations; meeting sleep recommendations did not differ by cancer history.Conclusions: While cancer survivors had lower prevalence of smoking and moderate/heavy drinking, they also had lower prevalence of physical activity and healthy BMI, and reported longer sleep duration. Regression analyses suggested survivors only showed poorer behaviors for alcohol.Impact: Targeted health promotion interventions among cancer survivors are needed.
Introduction E-cigarette cessation intervention research is limited. Young adult e-cigarette use and cessation is particularly nuanced, given various user profiles (i.e., polytobacco use, co-use with marijuana) warranting different intervention approaches. Methods The current study is an analysis of baseline survey data (collected September-December, 2018) among 1,133 young adult (ages 18-34) e-cigarette users in a 2-year longitudinal study. We examined: 1) e-cigarette user profiles (i.e., e-cigarette only; e-cigarette/other tobacco; e-cigarette/marijuana; e-cigarette/other tobacco/marijuana); and 2) correlates of readiness to quit e-cigarette use in the next 6 months and past-year e-cigarette quit attempts. Results In this sample (Mage=23.91, 47.3% male, 35.5% sexual minority, 75.2% White, 13.7% Hispanic), e-cigarette user profiles were: 16.8% e-cigarettes-only, 23.4% e-cigarette/other tobacco, 18.0% e-cigarette/marijuana, and 41.8% e-cigarette/other tobacco/marijuana. Multinomial logistic regression (referent: e-cigarette-only use) indicated that all polyuse groups were more likely to use high-nicotine e-liquids (containing ≥9 mg of nicotine). Other predictors included: e-cigarettes/other tobacco users being older and male; e-cigarettes/marijuana users using closed systems; and e-cigarettes/other tobacco/marijuana users being sexual minority (p’s<.01). Readiness to quit e-cigarettes and past-year quit attempts were reported by 20.8% and 32.3%, respectively. Per multilevel regression, readiness to quit and quit attempts correlated with using fewer days, high-nicotine e-liquids, and closed systems, but not marijuana, as well as being heterosexual and Black (vs. White); readiness to quit also correlated with being single; past-year quit attempts correlated with other tobacco use and being Hispanic. Conclusions Young adult e-cigarette users demonstrate distinct user profiles and cessation-related experiences that should be considered in developing cessation interventions. Implications The vast majority of young adult e-cigarette users use other tobacco products and marijuana. Unfortunately, few reported readiness to quit or attempting quit. Moreover, certain subgroups (e.g., sexual/racial/ethnic minorities) are more likely to be ready or attempt to quit, but may not be successful. Vaping cessation interventions must attend to these nuances.
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