Objectives We examined psychographic characteristics associated with tobacco use among Project DECOY participants. Methods Project DECOY is a 2-year longitudinal mixed-methods study examining risk for tobacco use among 3418 young adults across 7 Georgia colleges/universities. Baseline measures included sociodemographics, tobacco use, and psychographics using the Values, Attitudes, and Lifestyle Scale. Bivariate and multivariable analyses were conducted to identify correlates of tobacco use. Results Past 30-day use prevalence was: 13.3% cigarettes; 11.3% little cigars/cigarillos (LCCs); 3.6% smokeless tobacco; 10.9% e-cigarettes; and 12.2% hookah. Controlling for sociodemographics, correlates of cigarette use included greater novelty seeking (p < .001) and intellectual curiosity (p = .010) and less interest in tangible creation (p = .002) and social conservatism (p < .001). Correlates of LCC use included greater novelty seeking (p < .001) and greater fashion orientation (p = .007). Correlates of smokeless tobacco use included greater novelty seeking (p = .006) and less intellectual curiosity (p < .001). Correlates of e-cigarette use included greater novelty seeking (p < .001) and less social conservatism (p = .002). Correlates of hookah use included greater novelty seeking (p < .001), fashion orientation (p = .044), and self-focused thinking (p = .002), and less social conservatism (p < .001). Conclusions Psychographic characteristics distinguish users of different tobacco products.

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.

Common TAS2R38 taste receptor gene variants specify the ability to taste phenylthiocarbamide (PTC), 6-n-propylthiouracil (PROP) and structurally related compounds. Tobacco smoke contains a complex mixture of chemical substances of varying structure and functionality, some of which activate different taste receptors. Accordingly, it has been suggested that non-taster individuals may be more likely to smoke because of their inability to taste bitter compounds present in tobacco smoke, but results to date have been conflicting. We studied three cohorts: 237 European-Americans from the state of Georgia, 1,353 European-Americans and 2,363 African-Americans from the Dallas Heart Study (DHS), and 4,973 African-Americans from the Dallas Biobank. Tobacco use data was collected and TAS2R38 polymorphisms were genotyped for all participants, and PTC taste sensitivity was assessed in the Georgia population. In the Georgia group, PTC tasters were less common among those who smoke: 71.5% of smokers were PTC tasters while 82.5% of non-smokers were PTC tasters (P = 0.03). The frequency of the TAS2R38 PAV taster haplotype showed a trend toward being lower in smokers (38.4%) than in non-smokers (43.1%), although this was not statistically significant (P = 0.31). In the DHS European-Americans, the taster haplotype was less common in smokers (37.0% vs. 44.0% in non-smokers, P = 0.003), and conversely the frequency of the non-taster haplotype was more common in smokers (58.7% vs. 51.5% in non-smokers, P = 0.002). No difference in the frequency of these haplotypes was observed in African Americans in either the Dallas Heart Study or the Dallas Biobank. We conclude that TAS2R38 haplotypes are associated with smoking status in European-Americans but not in African-American populations. PTC taster status may play a role in protecting individuals from cigarette smoking in specific populations.

Background Marijuana-tobacco co-use has increased recently, particularly in young adults. Objectives We conducted a mixed-methods study to: (1) examine reasons for co-use; and (2) develop a scale assessing reasons for co-use among participants in a longitudinal cohort study of 3,418 students aged 18-25 from 7 Georgia colleges and universities. Methods Phone-based semi-structured interviews were conducted in Summer 2015 among 46 current (past 30-day, n = 26) or lifetime (n = 20) marijuana users. Subsequently, scale items were developed and included at Wave 3. Participants reporting past 4-month tobacco and marijuana use (n = 328) completed the Reasons for Marijuana-Tobacco Co-use section. Results Per qualitative data, reasons for marijuana-tobacco co-use included synergistic effects, one triggering or preceding the other’s use, using one to reduce the other’s use, co-administration, social context, and experimentation. The survey subsample included 37.1% who used cigarettes, 30.4% LCCs, 9.4% smokeless, 23.7% e-cigarettes, and 30.4% hookah. Four subscale factors emerged: (1) Instrumentality, indicating synergistic effects; (2) Displacement, indicating using one product to reduce/quit the other; (3) Social context, indicating use in different settings/social situations; and (4) Experimentation, indicating experimentation with both but no specific reasons for co-use. These subscales demonstrated distinct associations with tobacco type used; nicotine dependence; marijuana and alcohol use frequency; tobacco and marijuana use motives, respectively; perceptions of tobacco and marijuana; and parental and friend use. Including these subscales in regressions predicting nicotine dependence and days of marijuana use significantly contributed to each model. Conclusions These findings might inform theoretical frameworks upon which marijuana-tobacco co-use occurs and direct future intervention studies.