Lisa Dierker

Risk and Protective Factors Associated with Trajectories of Depressed Mood from Adolescence to Early Adulthood

This study used semi-parametric group-based modeling to explore unconditional and conditional trajectories of self-reported depressed mood from ages 12 to 25 years. Drawing on data from the National Longitudinal Study of Adolescent Health (N = 11,559), 4 distinct trajectories were identified: no depressed mood, stable low depressed mood, early high declining depressed mood, and late escalating depressed mood. Baseline risk factors associated with greater likelihood of membership in depressed mood trajectory groups compared with the no depressed mood group included being female, Black or African American, Hispanic or Latino American, or Pacific Islander or Asian American; having lower socioeconomic status; using alcohol, tobacco, or other drugs on a weekly basis; and engaging in delinquent behavior. Baseline protective factors associated with greater likelihood of membership in the no depressed mood group compared with the depressed mood trajectory groups included 2-parent family structure; feeling connected to parents, peers, or school; and self-esteem. With the exception of delinquent behavior, risk and protective factors also distinguished the likelihood of membership among several of the 3 depressed mood groups. The results add to basic etiologic research regarding developmental pathways of depressed mood in adolescence and young adulthood.

Trajectories of smoking from adolescence to early adulthood and their psychosocial risk factors.

OBJECTIVEnTo explore patterns of persistence and change in smoking behavior as well as risk factors associated with the developmental course of smoking from age 13 to 25.nnnDESIGNnData from the public use sample of the National Longitudinal Study of Adolescent Health (N = 5,789) were analyzed using semiparametric group-based modeling.nnnMAIN OUTCOME MEASURESnSmoking quantity-frequency in the past 30 days.nnnRESULTSnSix distinct smoking trajectories were identified: nonsmokers, experimenters, stable light smokers, quitters, late escalators, and stable high smokers. Baseline risk factors that were associated with greater likelihood of membership in all of the smoking trajectory groups compared with nonsmokers included alcohol use, deviance, peer smoking, and (with the exception of the late escalators) drug use. Deviance, peer smoking, and alcohol and drug use also distinguished the likelihood of membership among several of the 5 smoking trajectory groups.nnnCONCLUSIONnThe results add to basic etiologic research on developmental pathways of smoking in adolescence and young adulthood by providing evidence of heterogeneity in smoking behavior and prospectively linking different patterns of risk factors with the probability of trajectory group membership.

Smoking in College Freshmen: University Project of the Tobacco Etiology Research Network (UpTERN)

UpTERN, a study conducted by the Tobacco Etiology Research Network (TERN), was designed to examine trajectories of change in smoking behavior and the emergence of dependence over the course of the freshman year from a large sample of college students. The project included extensive quantitative and qualitative assessments of participants. In the first phase, screener data were collected from 4,690 freshmen entering Purdue University in the fall of 2002. In the second phase, 912 students were enrolled from the 2,001 who reported some prior exposure to smoking cigarettes in the first phase. These students provided extensive baseline information on a web-based assessment protocol administered in the week prior to the beginning of classes in the fall semester. In the third phase, these students participated in a web-based assessment administered for 35 consecutive weeks. Approximately 88% of the sample completed the web-based assessment each week. This report describes the rationale for the project and provides an overview of the constructs targeted across the research. In addition, the research methods, procedures, and assessments are discussed. Findings are reported for day-to-day patterns of smoking as well as alcohol and marijuana use across the 35 weeks of assessment. Finally, selected results from reports using data generated from this project are summarized, including analyses of patterns of smoking over time, associations between daily cigarette smoking and alcohol use, evaluations of the nature of nicotine dependence in low-level smokers, an exploration of early cigarette-use episodes in novice smokers, and a consideration of the role of descriptive and injunctive norms from romantic partners and friends in predicting cigarette smoking over time.

Confirmatory Factor Analysis of the Nicotine Dependence Syndrome Scale in an American College Sample of Light Smokers

The five-factor structure of the Nicotine Dependence Syndrome Scale (NDSS) obtained with samples of mature, heavy smokers has not been replicated in samples of younger, less experienced smokers. Furthermore, the idea that the interrelationships among the NDSS factors are best explained by a single higher-order factor (nicotine dependence) has not been evaluated empirically. This study examined the first- and second-order factor structure of the NDSS in a first-year college sample of light smokers (N = 154). NDSS measures completed at the end of the first semester of college were analyzed using confirmatory factor analysis. The hypothesized five-factor model provided adequate fit to the data. The second-order factor model did not fit the data as well as the correlated first-order factor model, suggesting that an overarching dependence factor may not account for the interrelationships among the five first-order factors. This study provided support for the multidimensional structure of the NDSS among a first-year college sample of light smokers.

Tobacco, Alcohol, and Marijuana Use Among First-Year U.S. College Students : A Time Series Analysis

The present study sought to evaluate the day-to-day patterns of tobacco, alcohol, and marijuana use among first-year college students in the United States. Using 210 days of weekly time-line follow-back diary data collected in 2002 to 2003, the authors examined within-person patterns of use. The sample was 48% female and 90% Caucasian. Sixty-eight percent of the participants were permanent residents of Indiana. Univariate time series analysis was employed to evaluate behavioral trends for each substance across the academic year and to determine the predictive value of day-to-day substance use. Some of the most common trends included higher levels of substance use at the beginning or end of the academic year. Use on any given day could be predicted best from the amount of corresponding substance use 1 day prior. Conclusions: Although universal intervention might best be focused in the earliest weeks on campus and at the end of the year when substance use is at its highest, the diversity of substance use trajectories suggests the need for more targeted approaches to intervention. Study limitations are noted.

Alcohol problems as a signal for sensitivity to nicotine dependence and future smoking.

BACKGROUNDnAlcohol use is a well-documented risk factor for the emergence of chronic smoking behavior. Very little is known, however, about the mediating pathways through which alcohol and/or alcohol-related problems influence future smoking.nnnMETHODSnData were drawn from the longitudinal Social and Emotional Contexts of Adolescent Smoking Patterns Study (SECASPS). Adolescents who had smoked under 100 cigarettes in their lifetime (n=898; experimenters) and adolescents who had smoked over 100 cigarettes, but fewer than 5 cigarettes per day (n=152: current smokers) were examined separately (grouping variable). Path analysis was performed to investigate the association between alcohol related problems at baseline (primary predictor) and smoking regularity at the 48 month follow-up (primary outcome), both directly and through mediating variables of smoking quantity and frequency, and nicotine dependence (averaged across these measures at 6-, 15-, and 24-month assessment waves).nnnRESULTSnAmong experimenters, after controlling for smoking and alcohol use, the association between alcohol-related problems at baseline and smoking frequency 48 months later was fully mediated by nicotine dependence symptoms. Among current smokers, only past smoking behavior was associated with 48-month smoking frequency.nnnCONCLUSIONSnAlcohol-related problems are a risk factor for future smoking among novice adolescent smokers above and beyond drinking or smoking per se. By signaling sensitivity to nicotine dependence symptoms, alcohol related problems represent an easily measureable risk factor that can be used to identify and intervene with adolescents before more chronic smoking behaviors emerge.

An Integrated Data Analysis Approach to Investigating Measurement Equivalence of DSM Nicotine Dependence Symptoms

INTRODUCTIONnResearch identifying nicotine dependence (ND) symptoms most appropriate for measurement of adolescent ND and invariant across the range of smoking exposure is hampered by limited sample size and variability of smoking behavior within independent studies. Integrative data analysis, the process of pooling and analyzing data from multiple studies, produces larger and more heterogeneous samples with which to evaluate measurement equivalence across the full continuum of smoking quantity and frequency.nnnMETHODSnData from two studies were pooled to obtain a large sample of adolescent and young adult smokers with considerable variability in smoking. We used moderated nonlinear factor analysis, which produces study equivalent ND scores, to simultaneously evaluate whether 14 DSM ND symptoms had equivalent psychometric properties (1) at different levels of smoking frequency and (2) across a continuous range of smoking quantity, after accounting for study differences.nnnRESULTSnNine of 14 symptoms were equivalent across levels of smoking frequency and quantity in probability of endorsement at different levels of ND and in ability to discriminate between levels of ND severity. A more precise ND factor score accounted for study and smoking related differences in symptom psychometric properties.nnnCONCLUSIONSnDSM-IV symptoms may be used to reliably assess ND in young populations across a wide range of smoking quantity and frequency and within both nationally representative and geographically restricted samples with different study designs. Symptoms shared across studies produced an equivalently scaled ND factor score, demonstrating that integrating data for the purpose of studying ND in young smokers is viable.

Exploring alternate processes contributing to the association between maternal smoking and the smoking behavior among young adult offspring

INTRODUCTIONnMaternal smoking during pregnancy (MSP) is a known risk factor for regular smoking in young adulthood and may pose a risk independently of mothers lifetime smoking. The processes through which MSP exerts this influence are unknown but may occur through greater smoking quantity and frequency following initiation early in adolescence or increased sensitivity to nicotine dependence (ND) at low levels of smoking.nnnMETHODSnThis study used path analysis to investigate adolescent smoking quantity, smoking frequency, and ND as potential simultaneous mediating pathways through which MSP and mothers lifetime smoking (whether she has ever smoked) increase the risk of smoking in young adulthood among experimenters (at baseline, <100 cigarettes/lifetime) and current smokers (>100 cigarettes/lifetime).nnnRESULTSnFor experimenters, MSP was directly associated with more frequent young adult smoking and was not mediated by adolescent smoking behavior or ND. Independently of MSP, the effect of mothers lifetime smoking was fully mediated through frequent smoking and was heightened ND during adolescence. Controlling for MSP eliminated a previously observed direct association between mothers lifetime smoking and future smoking among experimenters. For current smokers, only prior smoking behavior was associated with future smoking frequency.nnnCONCLUSIONSnThese results seem to rule out sensitivity to ND and increased smoking behavior as contributing pathways of MSP. Further, the impact of MSP on young adult smoking extends beyond that of having an ever-smoking mother. Future work should test other possible mediators; for example, MSP-related epigenetic changes or gene variants influencing the brains nicotine response.

Nicotine-dependence-varying effects of smoking events on momentary mood changes among adolescents

INTRODUCTIONnTheories of nicotine addiction emphasize the initial role of positive reinforcement in the development of regular smoking behavior, and the role of negative reinforcement at later stages. These theories are tested here by examining the effects of amount smoked per smoking event on smoking-related mood changes, and how nicotine dependence (ND) moderates this effect. The current study examines these questions within a sample of light adolescent smokers drawn from the metropolitan Chicago area (N=151, 55.6% female, mean 17.7years).nnnINSTRUMENTSnEcological momentary assessment data were collected via handheld computers, and additional variables were drawn from a traditional questionnaire.nnnMETHODSnEffects of the amount smoked per event on changes in positive affect (PA) and negative affect (NA) after vs. before smoking were examined, while controlling for subject-averaged amount smoked, age, gender, and day of week. ND-varying effects were examined using varying effect models to elucidate their change across levels of ND.nnnRESULTSnThe effect of the amount smoked per event was significantly associated with an increase in PA among adolescents with low-to-moderate levels of ND, and was not significant at high ND. Conversely, the effect of the amount smoked was significantly associated with a decrease in NA only for adolescents with low levels of ND.nnnCONCLUSIONSnThese findings support the role of positive reinforcement in early stages of dependent smoking, but do not support the role of negative reinforcement beyond early stages of smoking. Other potential contributing factors to the relationship between smoking behavior and PA/NA change are discussed.