Janet Audrain-McGovern

Association of Electronic Cigarette Use With Initiation of Combustible Tobacco Product Smoking in Early Adolescence

IMPORTANCE Exposure to nicotine in electronic cigarettes (e-cigarettes) is becoming increasingly common among adolescents who report never having smoked combustible tobacco. OBJECTIVE To evaluate whether e-cigarette use among 14-year-old adolescents who have never tried combustible tobacco is associated with risk of initiating use of 3 combustible tobacco products (ie, cigarettes, cigars, and hookah). DESIGN, SETTING, AND PARTICIPANTS Longitudinal repeated assessment of a school-based cohort at baseline (fall 2013, 9th grade, mean age = 14.1 years) and at a 6-month follow-up (spring 2014, 9th grade) and a 12-month follow-up (fall 2014, 10th grade). Ten public high schools in Los Angeles, California, were recruited through convenience sampling. Participants were students who reported never using combustible tobacco at baseline and completed follow-up assessments at 6 or 12 months (N = 2530). At each time point, students completed self-report surveys during in-classroom data collections. EXPOSURE Student self-report of whether he or she ever used e-cigarettes (yes or no) at baseline. MAIN OUTCOMES AND MEASURES Six- and 12-month follow-up reports on use of any of the following tobacco products within the prior 6 months: (1) any combustible tobacco product (yes or no); (2) combustible cigarettes (yes or no), (3) cigars (yes or no); (4) hookah (yes or no); and (5) number of combustible tobacco products (range: 0-3). RESULTS Past 6-month use of any combustible tobacco product was more frequent in baseline e-cigarette ever users (n = 222) than never users (n = 2308) at the 6-month follow-up (30.7% vs 8.1%, respectively; difference between groups in prevalence rates, 22.7% [95% CI, 16.4%-28.9%]) and at the 12-month follow-up (25.2% vs 9.3%, respectively; difference between groups, 15.9% [95% CI, 10.0%-21.8%]). Baseline e-cigarette use was associated with greater likelihood of use of any combustible tobacco product averaged across the 2 follow-up periods in the unadjusted analyses (odds ratio [OR], 4.27 [95% CI, 3.19-5.71]) and in the analyses adjusted for sociodemographic, environmental, and intrapersonal risk factors for smoking (OR, 2.73 [95% CI, 2.00-3.73]). Product-specific analyses showed that baseline e-cigarette use was positively associated with combustible cigarette (OR, 2.65 [95% CI, 1.73-4.05]), cigar (OR, 4.85 [95% CI, 3.38-6.96]), and hookah (OR, 3.25 [95% CI, 2.29-4.62]) use and with the number of different combustible products used (OR, 4.26 [95% CI, 3.16-5.74]) averaged across the 2 follow-up periods. CONCLUSIONS AND RELEVANCE Among high school students in Los Angeles, those who had ever used e-cigarettes at baseline compared with nonusers were more likely to report initiation of combustible tobacco use over the next year. Further research is needed to understand whether this association may be causal.

Does delay discounting play an etiological role in smoking or is it a consequence of smoking

Although higher delay discounting rates have been linked to cigarette smoking, little is known about the stability of delay discounting, whether delay discounting promotes smoking acquisition, whether smoking contributes to impulsive choices, or if different relationships exist in distinct subgroups. This study sought to fill these gaps within a prospective longitudinal cohort study (N=947) spanning mid-adolescence to young adulthood (age 15-21 years old). Smoking and delay discounting were measured across time. Covariates included peer and household smoking, academic performance, depression, novelty seeking, inattention and hyperactivity/impulsivity symptoms, and alcohol and marijuana use. The associated processes latent growth curve modeling (LGCM) with paths from the delay discounting level factor (baseline measure) and the trend factor (slope) to the smoking trend factor (slope) fit the data well, chi(2)((19,n=947)) =15.37, p=.70, CFI=1.00, RMSEA=0, WRMR=.36. The results revealed that delay discounting did not change significantly across time. Baseline delay discounting had a significant positive effect on smoking trend (beta=.08, z=2.16, p=.03). A standard deviation (SD=1.41) increase in baseline delay discounting resulted in an 11% increase (OR=1.11, 95% CI=1.03, 1.23) in the odds of smoking uptake. The alternative path LCGM revealed that smoking did not significantly impact delay discounting (ps>.05). Growth mixture modeling identified three smoking trajectories: nonsmokers, early/fast smoking adopters, and slow smoking progressors. Delay discounting was higher in the smoking versus nonsmoking trajectories, but did not discriminate between the smoking trajectories, despite different acquisition patterns. Delay discounting may provide a variable by which to screen for smoking vulnerability and help identify subgroups to target for more intensive smoking prevention efforts that include novel behavioral components directed toward aspects of impulsivity.

Cigarette Smoking Practices Among American College Students: Review and Future Directions

Cigarette smoking among college students is a critical public health problem. In this article, the authors review available research on cigarette smoking practices among college students and suggest directions for future research. Studies show that smoking by college students is associated with being White, living in housing where smoking is permitted, using alcohol and other substances, and having a lower psychological sense of well-being. Depression, life satisfaction, and coping style are also related to college smoking, but the causal relationship remains unclear. Although a large proportion of college students have made an attempt to quit smoking, only a minority actually succeed. Most study designs examining college smoking have been cross-sectional, descriptive, or both. Thus, conclusions regarding predictors of smoking onset, maintenance, and cessation cannot be made. Future studies should use longitudinal designs that can identify psychological and socioenvironmental determinants of smoking among college students. Such information could inform the development of smoking prevention and cessation interventions targeted to the college student population.

The functional mu opioid receptor (OPRM1) Asn40Asp variant predicts short-term response to nicotine replacement therapy in a clinical trial

ABSTRACTTo determine whether the functional mu-opioid receptor (OPRM1) Asn40Asp variant predicts the comparative efficacy of different forms of NRT, we conducted a clinical trial of transdermal nicotine (TN) vs nicotine nasal spray (NS) in 320 smokers of European ancestry. Smokers carrying the OPRM1 Asp40 variant (n=82) were significantly more likely than those homozygous for the Asn40 variant (n=238) to be abstinent at the end of treatment, and reported less mood disturbance and weight gain. The genotype effect on treatment outcome was most pronounced among smokers receiving TN, particularly during the 21 mg dose phase. Smokers who carry the OPRM1 Asp40 variant are likely to have a favorable response to TN and may benefit from extended therapy with the 21 mg dose.

A Randomized Controlled Trial of Financial Incentives for Smoking Cessation

Background: Although 435,000 Americans die each year of tobacco-related illness, only ∼3% of smokers quit each year. Financial incentives have been shown to be effective in modifying behavior within highly structured settings, such as drug treatment programs, but this has not been shown in treating chronic disease in less structured settings. The objective of this study was to determine whether modest financial incentives increase the rate of smoking cessation program enrollment, completion, and quit rates in a outpatient clinical setting. Methods: 179 smokers at the Philadelphia Veterans Affairs Medical Center who reported smoking at least 10 cigarettes per day were randomized into incentive and nonincentive groups. Both groups were offered a free five-class smoking cessation program at the Philadelphia Veterans Affairs Medical Center. The incentive group was also offered

Randomized Trial of Four Financial-Incentive Programs for Smoking Cessation

20 for each class attended and

Adolescent smoking and depression: evidence for self‐medication and peer smoking mediation

100 if they quit smoking 30 days post program completion. Self-reported smoking cessation was confirmed with urine cotinine tests. Results: The incentive group had higher rates of program enrollment (43.3% versus 20.2%; P < 0.001) and completion (25.8% versus 12.2%; P = 0.02). Quit rates at 75 days were 16.3% in the incentive group versus 4.6% in the control group (P = 0.01). At 6 months, quit rates in the incentive group were not significantly higher (6.5%) than in the control group (4.6%; P > 0.20). Conclusion: Modest financial incentives are associated with significantly higher rates of smoking cessation program enrollment and completion and short-term quit rates. Future studies should consider including an incentive for longer-term cessation. (Cancer Epidemiol Biomarkers Prev 2006;15(1):12–8)

The impact of poor health on academic performance: New evidence using genetic markers

BACKGROUND Financial incentives promote many health behaviors, but effective ways to deliver health incentives remain uncertain. METHODS We randomly assigned CVS Caremark employees and their relatives and friends to one of four incentive programs or to usual care for smoking cessation. Two of the incentive programs targeted individuals, and two targeted groups of six participants. One of the individual-oriented programs and one of the group-oriented programs entailed rewards of approximately

Sleep Duration and Adolescent Obesity

800 for smoking cessation; the others entailed refundable deposits of

Effecting Behavior Change Awareness of Family History

150 plus