Tobacco Use Assessment

1. Longitudinal Study Examining the Association Between Impulsivity and Developmental Trajectories of Cigarette Smoking in Young Adults Dustin C. Lee1, Zachary W. Adams2, Richard Milich1, Thomas H. Kelly1, Donald R. Lynam3 1University of Kentucky, 2Medical University of South Carolina, 3Purdue University Results (Aim 2) Tobacco Use Assessment Life History Questionnaire (LHC):This questionnaire is a retrospective method for collecting data on a wide range of life events and behaviors. Participants were asked to report on their substance use in 4 month blocks from age 13 up until the time of the first interview, then report monthly substance use at two-follow up sessions scheduled at yearly intervals thereafter. Monthly tobacco use data from each follow-up session was averaged into eight 3-month blocks for trajectory analyses. Data Analysis Aim 1: Group-based trajectory modeling (i.e. Nagin, 1999) assuming a zero inflated Poisson distribution was used to empirically cluster individual participants’ smoking trajectories in order to find the most parsimonious group structure. Bayes Information Criteria (BIC) was used to determine the specific number of tobacco use groups that best fit the data. A 4 group model produced the smallest BIC while maintaining group sizes >5% and was chosen as the model that best fit the data. Probabilities of each individual participant’s membership in a tobacco use group were calculated, and group size was determined by calculating the percentage of individuals with the highest probabilities for belonging to each group (see Figure 1 and Table 1 of results for group sizes). This analysis was completed using SAS proctraj. Aim 2: To examine the influence of UPPS dimensions and behavioral inhibition on the probability of group membership, each variable was included in the trajectory model as a risk factor and a p-value was assigned for whether each risk factor significantly changed the probability of belongingto a smoking group relative to the non-smoking group (see Table 2 of results section). Note: behavioral inhibition did not significantly increase the probability of smoking group membership and was omitted from Table 2. Aim 3: A 4x3 (group x wave) mixed models approach (SAS proc mixed) was used to determine whether behavioral impulsivity changed as a function of tobacco use. Groups were determined by assigning each individual to a trajectory to which (s)he had the highest probability of belonging. Change in behavioral inhibition was measured across waves 1, 2 and 3 of the data set. • Background • Previous longitudinal studies have demonstrated that young adults are at risk for initiating tobacco use and escalation to tobacco dependence (e.g. Brook et al., 2008; Chassin et al., 2000) • Impulsivity is a multi-dimensional construct (Evenden, 1999; Whiteside and Lynam, 2001) that is assessed using both subject-rated trait assessments and performance on tasks of behavioral inhibition • Previous studies have demonstrated that several dimensions of impulsivity are associated with increased vulnerability to tobacco initiation, escalation, and dependence • Sensation seeking is closely associated with initiation and current smoking status (Flory and Manuck, 2009; Perkins et al., 2008), whereas inhibition and urgency are closely associated with the development of tobacco dependence (Flory and Manuck, 2009; Grano et al., 2004; Spillane et al., 2010) • Further research is needed in order to determine how individual differences in impulsivity contribute to patterns of tobacco use, including initiation and escalation of cigarette smoking • The aims of this study are to: • 1) identify distinct trajectories of smoking behavior in young adults entering college, • 2) determine if individual differences in impulsivity confers vulnerability to escalating tobacco use, and • 3) Evaluate if behavioral inhibition varies as a consequence of escalating tobacco use • Supported by DA-05312 Results (Aim 1) Table 2The influence of UPPS dimensions on probability of smoking trajectory membership. Positive estimates indicate an increase in probability of belonging to a particular smoking group relative to the non-smoking group. UPPS dimensions that were significant risk factors for smoking group membership are highlighted. Behavioral measures were also assessed but did not significantly increase the probability of smoking group membership. Method Subjects:Participants (N=428) were young-adult college students between the ages of 18-24 who were recruited from an introductory Psychology course during their freshman year at the University of Kentucky. Procedure: Participants completed 3-2.5 hour sessions at yearly intervals. During each session, participants completed several measures of impulsivity including self-report trait and behavioral task assessments on a computer, along with an assessment of substance use for the prior year. • Results (Aim 3) • A main effect of group was found on BART explosions F(3,424) = 2.63, p<.05 and Cued Go/No Go inhibitory errors F(3,425) = 2.94, p<.05. Pairwise comparisons indicated that the late-escalating group had significantly more balloon explosions on the BART and inhibitory errors on the Cued RT task relative to non-smokers and decreasing smokers. • However, no group by wave interactions were found on either the BART, Cued Go/No Go, or MCQ tasks. Trait Impulsivity Assessment UPPS-P:The UPPS-P is a 59-item inventory designed to measure distinct personality pathways to impulsive behavior. Items were rated on a 4-point scale from Strongly Agree to Strongly Disagree. UPPS dimensions of interest in this study were Negative Urgency,(lack of) Premeditation, (lack of) Perseverance, and Sensation Seeking Behavioral Assessments Balloon Analog Risk Task:This task provided an index of risk-taking behavior. Simulated balloons were inflated on a computer by clicking a mouse button. A successful inflation resulted in an addition of money to a temporary bank and increased the probability of the balloon popping on the next inflation. Subjects could stop inflating a balloon at any time and collect the money earned. If a subject chose to inflate the balloon and it popped, money in the temporary bank was lost. The dependent measure of of interest was the number of balloons exploded. Cued Go/No-Go Task: This task provided a measure of inhibitory control. Each trial began with a black rectangle cue presented in horizontal or vertical orientation. Go and No Go cues were then presented as solid colors (blue or green) within the rectangles. Subjects were required to respond as quickly as possible whenever a green hue was presented. The green hue was presented on 80% of the horizontal rectangle trials (Go cue), and the blue hue was presented on 80% of the vertical rectangle trials (No Go cue). The primary measure of interest was failures to inhibit a response to a No Go target when a Go cue was presented. Monetary Choice Questionnaire (MCQ):This task consisted of 27 questions assessing equivalence value of immediate versus delayed monetary rewards. Each choice on the MCQ was used to assign an overall approximation of the k value, or discounting rate for each participant, with larger k values signifying more impulsivity. • Conclusions • Similar to previous research (e.g. Caldiera et al., 2012) young adult college students tobacco use yielded distinct trajectories of smoking behavior. • Non-smokers were the most populous group, followed by early-escalating smokers, decreasing smokers, and finally those who were late-escalators. • Relative to non-smokers: • UPPS negative urgency, (lack of) premeditation, and sensation seeking increased the probability of belonging to the early-escalator smoking trajectory, and • sensation seeking alone increased the probability of belonging to the late-escalator trajectory. • Behavioral impulsivity was increased in early- and late-escalating smokers, but performance did not changeacross time within each group, and behavioral tasks did not significantly influence the probability of smoking group membership relative to non-smokers. • Overall, these results indicate that: • Young adults demonstrate heterogeneous patterns of tobacco use that are influenced by dimensions of impulsivity. • Negative urgency was the strongest predictor of group membership in the early-escalator groupand might be a target for clinical interventions aimed at reducing smoking in heavy smokers, whereas sensation seeking was the strongest predictor of group membership in the late-escalating smoking group and might be a target for prevention strategies aimed at reducing smoking uptake in young adults. • In this study, UPPS dimensions were more sensitive than behavioral inhibition as risk factors for increasing the probability of belonging to a smoking trajectory. Furthermore, behavior on tasks was largely stable across assessments within each group, suggesting that behavioral inhibition does not change as a function of escalating tobacco use in young adult smokers. Figure 1Trajectories of cigarette smoking frequency assessed across 3 waves following enrollment at the University of Kentucky.Timepoints 1-3 from the first wave are comprised of 4 month blocks, and data from waves 2 and 3 (timepoints 4-11) are comprised of 3 month blocks.Cigarette smoking frequency was assessed on a 0-5 scale using the LHC, with 0 = none, 1 = once a month, 2 = once a week, 3 = 2-3 times per week, 4 = 4-5 times per week, and 5 = daily.