Multiple imputation (MI) and full information maximum likelihood (FIML) are the two most common approaches to missing data analysis. In theory, MI and FIML are equivalent when identical models are tested using the same variables, and when m, the number of imputations performed with MI, approaches infinity. However, it is important to know how many imputations are necessary before MI and FIML are sufficiently equivalent in ways that are important to prevention scientists. MI theory suggests that small values of m, even on the order of three to five imputations, yield excellent results. Previous guidelines for sufficient m are based on relative efficiency, which involves the fraction of missing information (γ) for the parameter being estimated, and m. In the present study, we used a Monte Carlo simulation to test MI models across several scenarios in which γ and m were varied. Standard errors and p-values for the regression coefficient of interest varied as a function of m, but not at the same rate as relative efficiency. Most importantly, statistical power for small effect sizes diminished as m became smaller, and the rate of this power falloff was much greater than predicted by changes in relative efficiency. Based our findings, we recommend that researchers using MI should perform many more imputations than previously considered sufficient. These recommendations are based on γ, and take into consideration one's tolerance for a preventable power falloff (compared to FIML) due to using too few imputations.

BACKGROUND: Use of electronic cigarettes (e-cigarettes) among adolescents has increased since their introduction into the US market in 2007. Little is known about the role of e-cigarette psychosocial factors on risk of e-cigarette or cigarette use in adolescence. METHODS:Information on e-cigarette and cigarette psychosocial factors (use and attitudes about use in the home and among friends) was collected from 11th-and 12th-grade participants in the Southern California Children's Health Study during the spring of 2014.RESULTS: Of 2084 participants, 499 (24.0%) had used an e-cigarette, including 200 (9.6%) current users (past 30 days); 390 participants (18.7%) had smoked a combustible cigarette, and 119 (5.7%) were current cigarette smokers. Cigarette and e-cigarette use were correlated. Nevertheless, 40.5% (n = 81) of current e-cigarette users had never smoked a cigarette. Psychosocial factors (home use of each product, friends' use of and positive attitudes toward e-cigarettes and cigarettes) and participant perception of the harm of e-cigarettes were strongly positively associated both with e-cigarette and cigarette use. Most youth who reported e-cigarette use had friends who used e-cigarettes, and almost half of current users reported that they did not believe there were health risks associated with e-cigarette use.CONCLUSIONS: Longitudinal studies of adolescents are needed to determine whether the strong association of e-cigarette psychosocial factors with both e-cigarette and cigarette use will lead to increased cigarette use or dual use of cigarettes and e-cigarettes, or whether e-cigarettes will serve as a gateway to cigarette use. WHAT'S KNOWN ON THIS SUBJECT:Electronic cigarette (e-cigarette) use in adolescence is increasing. E-cigarette use has been associated with cigarette use, but there has been little study of other psychosocial risk factors for e-cigarette use and their relationship with cigarette use. WHAT THIS STUDY ADDS:Approval and use of e-cigarettes and cigarettes among friends and family were strongly associated with cigarette and e-cigarette use in a cohort of adolescents in southern California.

Objective: to assess the co-occurrence of patterns of adolescent substance use and sexual behavior and test for potential moderating effects of gender. Method: the 2005 Youth Risk behavior survey sample of 13,953 high school students was used in this study. latent class analyses were conducted to examine the relation between patterns of substance use and sexual risk behavior in a nationally representative adolescent sample. the final model controlled for demographic covariates and an interaction between gender and substance-use classes. Results: Four class solutions to each behavior provided optimal fit. substance-use classes were nonusers (27%), alcohol experimenters (38%), occasional polysubstance users (23%), and frequent polysubstance users

Background The potential for increases in adolescent marijuana use is an important concern given recent changes in marijuana policy. The purpose of this study was to estimate trends in marijuana use from 1999-2013 among a national sample of US high school students. We examine changes over time by race/ethnicity and sex. Methods Data are from the National Youth Risk Behavior Survey (YRBS), which involves biennial, school-based surveys that generate nationally-representative data about 9th-12th grade students in the United States. Students self-reported sex, race/ethnicity, and marijuana use (i.e., lifetime use, current use, any use before age 13). We generated national estimates of the prevalence of marijuana use for the time period, and also tested for linear and quadratic trends (n=115,379). Results The prevalence of lifetime marijuana use decreased modestly from 1999 to 2009 (44% to 37%), and has increased slightly since 2009 (41%). Other marijuana use variables (e.g., past 30-day use) followed a similar pattern over time. The prevalence of past 30-day use from 1999-2013 for all groups and both sexes was 22.5%, and it was lowest among Asians and highest among American Indian/Alaska Natives. Although boys have historically had a higher prevalence of marijuana use, results indicate that male-female differences in marijuana use decreased over time. Conclusion Despite considerable changes in state marijuana policies over the past 15 years, marijuana use among high school students has largely declined. Continued surveillance is needed to assess the impact of policy changes on adolescent marijuana use.

Patterns of substance use are examined in a sample of over 1200 youth in a non-metropolitan region of New England. Self-reported history and frequency of alcohol, tobacco, marijuana, inhalants, pain medications, and other hard drug use was assessed for 9th and 10th grade students. Latent class analyses identified four patterns of substance use: non-users (22%), alcohol experimenters (38%), occasional polysubstance users (29%), and frequent polysubstance users (10%). Contextual risk and protective factors in the individual, family, peer, and community domains predicted substance use patterns. Youth report of peer substance use had the largest effects on substance use class membership. Other individual characteristics (e.g., gender, antisocial behavior, academic performance, perceived harm from use), family characteristics (e.g., parental drinking, parental disapproval of youth use), and community characteristics (e.g., availability of substances) demonstrated consistent effects on substance use classes. Implications for prevention are discussed from a social-ecological perspective.

Purpose There is a growing public health concern related to the rapid increase in the use of multiple tobacco products among adolescents. This study examined patterns of adolescent use of cigarettes, e-cigarettes, cigars/cigarillo, hookah/waterpipe, and smokeless/dip/chewing tobacco in a population of southern California adolescents. Methods Data from 2,097 11th- and 12th-grade participants in the Southern California Children’s Health Study were collected via self-report in 2014. Study participants were asked about lifetime and current (past 30 days) use of cigarettes, cigars/cigarillos/little cigars, e-cigarettes, hookah/waterpipe, and smokeless/dip/chewing tobacco. Latent class analysis (LCA) was used to identify patterns of tobacco use. Results Hookah/waterpipe tobacco use had the highest current prevalence (10.7%) followed by e-cigarettes (9.6%). The prevalence of use of smokeless/dip/chewing tobacco was lowest, with 2.2% of adolescents reporting current use. The LCA suggested four distinct classes, comprising nonusers (72.3% of the sample), polytobacco experimenters (13.9%), e-cigarette/hookah users (8.2%), and polytobacco users (5.6%). Multinomial logistic regression based on these four classes found that males had double the odds to be polytobacco users relative to nonusers compared to females (odds ratio, 2.3; 95% confidence interval, 1.26–4.25). Conclusions By identifying naturally occurring configurations of tobacco product use in teens, these findings may be useful to practitioners and policymakers to identify the need for tobacco control interventions that address specific tobacco products and particular combinations of polytobacco use. LCA can be used to identify segments of the population overrepresented among certain tobacco use classes (e.g., boys) that may benefit most from targeted polyproduct intervention approaches.

Purpose One concern regarding the recent increase in adolescent e-cigarette use is the possibility that e-cigarettes may be used by those who might not otherwise have used cigarettes, and that dual use, or transition to cigarette use alone, may follow. Methods Questionnaire data were obtained in 2014 from 11th/12th grade students attending schools in 12 communities included in the Southern California Children’s Health Study (CHS). We evaluated the cross-sectional association between e-cigarette use, the psychosocial environment (family and friends’ use and approval of e-cigarettes and cigarettes) and susceptibility to future cigarette use among never cigarette smokers (N=1694), using previously validated measures based on reported absence of a definitive commitment not to smoke. Results Among adolescents who had never used cigarettes, 31.8% of past e-cigarette users and 34.6% of current (past 30 day) e-cigarette users indicated susceptibility to cigarette use, compared to 21.0% of never e-cigarette users. The odds of indicating susceptibility to cigarette use were two times higher for current e-cigarette users compared to never users (OR=1.97; 95%CI: 1.21, 3.22). A social environment favorable to e-cigarettes (friends’ use of and positive attitudes toward use of e-cigarettes) was also associated with greater likelihood of susceptibility to cigarette use, independent of an individual’s e-cigarette use. Conclusions E-cigarette use in adolescence, and a pro-e-cigarette social environment, may put adolescents at risk for future use of cigarettes. E-cigarettes may contribute to subsequent cigarette use via nicotine addiction or social normalization of smoking behaviors.

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