A Longitudinal Study of Predictors for Adolescent Electronic Cigarette Experimentation and Comparison with Conventional Smoking

International Journal of Environmental Research and Public Health Article A Longitudinal Study of Predictors for Adolescent Electronic Cigarette Experimentation and Comparison with Conventional Smoking Jaana M. Kinnunen 1,*ID , Hanna Ollila 2, Jaana Minkkinen 1, Pirjo L. Lindfors 1,3 and Arja H. Rimpelä 1,3,4 ID 1Faculty of Social Sciences, Health Sciences, University of Tampere, 33014 Tampere, Finland; [email protected] (J.M.); [email protected] (P.L.L.); [email protected] (A.H.R.) 2Alcohol, Drugs and Addictions Unit, Department of Public Health Solutions, National Institute for Health and Welfare, 00271 Helsinki, Finland; [email protected] 3PERLA—Tampere Centre for Childhood, Youth and Family Research, University of Tampere, 33014 Tampere, Finland 4Department of Adolescent Psychiatry, Pitkäniemi Hospital, Tampere University Hospital, 33380 Nokia, Finland *Correspondence: [email protected]; Tel.: +358-40-190-1667 Received: 14 December 2017; Accepted: 6 February 2018; Published: 9 February 2018 Abstract: Little is known of the predictors of electronic cigarette (e-cigarette) use among adolescents, even though the use is increasing. We studied here the predictors for e-cigarette experimentation (tried and tried more than twice) and compared them with predictors for conventional smoking. A baseline school survey was conducted in the Helsinki metropolitan area, Finland, in 2011 for seventh graders (12 to 13-year-olds). Response rate was 73%. The same students were followed up in 2014 (9th grade, 15 to 16-year-olds), N= 5742. Generalized linear mixed models controlling for school clustering were used. In the follow-up, 43.3% of boys and 25.6% of girls had tried e-cigarettes and 21.9% and 8.1% correspondingly more than twice. The strongest predictors for both genders were conventional smoking, drunkenness and energy drink use. Furthermore, poor academic achievement predicted e-cigarette experimentation for both genders, and for boys, participation in team sports was a predictor. The predictors for experimenting and for experimenting more than twice were very similar, except for boys’ participation in team sports. They were also similar compared to the predictors of conventional smoking but the associations were weaker. To conclude, smoking and other addictive behaviors predict adolescents’ experimentation with e-cigarettes. Family’s socioeconomic background had little significance. Keywords: electronic cigarette; adolescents; smoking; predictors; school survey 1. Introduction Electronic cigarettes (e-cigarettes) or electronic nicotine delivery systems (ENDS) have taken root all over the world among younger populations during the last few years [ 1 – 4 ]. Young smokers seem to be more prone to experiment with and use e-cigarettes, but also among those who have never tried smoking, e-cigarette experimentation has been reported [ 5 – 7 ]. As e-cigarette experimentation has increased rapidly among adolescents and e-cigarettes may also be a gateway to conventional smoking [ 8 ], curbing the increase in adolescents’ e-cigarette experimentation should be promoted. To identify the susceptible adolescents better, the risk factors for e-cigarette experimentation need to be studied in detail. The correlates for adolescent e-cigarette experimentation and use have been studied quite widely in cross-sectional studies. So far, adolescent e-cigarette experimentation and use have been associated Int. J. Environ. Res. Public Health 2018,15, 305; doi:10.3390/ijerph15020305 www.mdpi.com/journal/ijerph Int. J. Environ. Res. Public Health 2018,15, 305 2 of 17 with other addictive behaviors: susceptibility to conventional smoking initiation [6,9] , conventional smoking [ 4 , 5 , 10 – 21 ], ever-use of other tobacco products (combustible and non-combustible) [10,12,14,18] , and alcohol [ 4 , 11 , 14 , 22 ] and cannabis use [ 20 , 21 ]. Additionally, male gender [ 4 , 11 , 13 , 14 , 16 , 22 , 23 ], perception of low harm of e-cigarettes [ 24 – 27 ], peer smoking [ 4 , 13 , 20 , 26 ], parents’ smoking [ 10 , 18 , 23 ] and exposure to e-cigarette advertising [28,29] have been associated with e-cigarette use. There are only a handful of longitudinal studies on adolescent e-cigarette use that have been published so far, and they have concentrated on the progression to conventional cigarette smoking after e-cigarette use [ 30 – 35 ] and on the predictors of continued e-cigarette use after experimentation [ 36 ]. To our knowledge, predictors for adolescent e-cigarette experimentation have been studied only once in a longitudinal setting. In this German study [ 37 ], sensation-seeking behavior and friends’ and parental smoking predicted e-cigarette use, while conventional cigarette smoking and male gender did not [ 37 ]. The above-mentioned study [ 37 ] also compared the risk factors between e-cigarette use and conventional cigarette smoking: some of the risk factors were the same but, e.g., male gender and older age predicted only conventional cigarette smoking. In Finnish studies, male gender has been associated with e-cigarette experimentation [ 10 , 18 ]. Thus, there is a need for gender-stratified and more detailed analyses of factors that increase the risk for e-cigarette experimentation and use. This study explores predictors for e-cigarette experimentation separately for boys and girls in a longitudinal setting in Finland. As the risk factors for e-cigarette use and use of conventional cigarettes may be different [ 7 ], we compare the predictors for both. The predictors to be studied include addictive health behaviors (drunkenness, use of energy drinks), socioeconomic and family background, parents’ smoking, and student’s own academic achievement at school. These are known to be risk factors or correlates for smoking as well [ 38 ]. As smokeless tobacco (snus) use has been found to be associated with participation in team sports [ 39 ], three different kinds of leisure activities, namely participation in team sports, individual sports, and music, art or club activities were also included in the investigated predictors. At the time of the surveys, there was no age limit in Finland for purchasing non-nicotine e-cigarettes as they were classified as tobacco imitations and e-liquids as substitute tobacco. The age limit for conventional cigarettes was 18 years. Nicotine-containing e-cigarettes at that time were treated as medicinal products and no e-cigarette company had a selling permit for them. However, e-cigarettes with nicotine were acquired from visits abroad or online also by adolescents, along with friends as a main source [ 10 ]. According to the new Tobacco Act of 2016, e-cigarettes, both nicotine and non-nicotine, are considered equal to conventional cigarettes [40]. 2. Materials and Methods 2.1. Participants and Study Procedure Metropolitan Longitudinal Finland (MetLoFIN) is a longitudinal study following a cohort of 13,012 children in the Helsinki metropolitan area of Finland. The study covered all schools of 14 metropolitan municipalities (N= 136). The first school survey was conducted in autumn 2011 (baseline) in the beginning of the lower secondary school, i.e., 7th grade (12 to 13-year-olds), and 9497 people of the cohort participated in the survey, meaning a response rate of 73%. In the city of Helsinki, five schools (2.5%; N= 330) were omitted: two schools refused to participate, two schools had construction in their computer classes and one school had a delay of the individual passwords for the survey. Almost empty and unreliable questionnaires, i.e., profanities in open-ended questions and extreme choices, were excluded (N= 42). Additionally, some students were absent from the school on the survey day or refused to participate (separate N’s not known). The second survey was conducted in spring 2014 (follow-up) at the end of lower secondary school, i.e., 9th grade (15 to 16-year-olds). The flow diagram representing the formation of the study population is presented in Figure 1. Int. J. Environ. Res. Public Health 2018,15, 305 3 of 17 Figure 1. Flow diagram representing the formation of the study population. Invited in 2011: Schools N = 136 Students N = 13,012 Schools N = 131 Students N = 12,682 Refused: Schools N = 2 Omitted: Schools N = 2 (due to construction in computer classes) Schools N = 1 (due to delay of passwords) N = 330 students Participated in baseline survey in 2011: Schools N = 131 Students N = 9539 Missing students: Absent or refused N = 3143 Included in baseline sample: Schools N = 131 Students N = 9497 Excluded: Students N = 42 due to unreliable answers Participated in follow-up in 2014: Schools N = 123 Students N = 5742 Attrition: Schools N = 8 Students N = 3755 Figure 1. Flow diagram representing the formation of the study population. The data was gathered as part of the school routine and, therefore, no parental consent was needed according to the ethical guidelines of the Finnish Advisory Board on Research Integrity (www.tenk.fi/en). However, the local authorities required parental consents in two of the 14 municipalities and the consents were collected. In other municipalities, parents received information letters on the survey, and were able to deny their children the participation (=passive consent). The participants completed an online survey in computer classrooms using personal user names and passwords. The study protocol has been approved by the Ethics Committee of the Finnish National Institute of Health and Welfare. For the 2011 survey, the statement code is 27.5.2011 and the code for the 2014 survey is 9.4.2014. The well-being survey consisted of questions regarding well-being, health, health behavior, school, and family background. E-cigarette use was assessed at follow-up, and predictors are analyzed from the baseline. E-cigarette use was not asked at baseline but it can be well assumed that the students were never-users of e-cigarettes or that there were just very few of them in 2011. The reason for this Int. J. Environ. Res. Public Health 2018,15, 305 4 of 17 assumption is that, according to our other research, e-cigarette use was very rare among 12-year-olds in Finland after two years of the survey in 2013, and most of them had not even heard about e-cigarettes [ 10 ]. All respondents who answered both baseline and follow-up (N= 5742, Nfor schools = 123) were included in the analyses, meaning 60.5% of those who participated in the first survey and 44.1% of the original cohort. The distribution of boys and girls was equal (Boys: N= 2871; Girls: N= 2871). The descriptive statistics of the study population are presented in Table 1. Table 1. Descriptive statistics of the study population by gender, %. Predictor|Gender Boys (N= 2871), % (N) Girls (N= 2871), % (N) Not tried e-cigarettes at follow-up 56.7 (1533) 74.4 (2079) Tried e-cigarette once or twice at follow-up 21.5 (582) 17.4 (486) Tried e-cigarettes 20 times or less at follow-up 6.7 (180) 4.5 (127) Tried e-cigarettes more than 20 times at follow-up 15.2 (411) 3.6 (101) Not tried smoking at follow-up 50.0 (1351) 57.7 (1609) Tried smoking (1–50 cigarettes) at follow-up 32.0 (865) 29.4 (820) Smoked more than 50 cigarettes at follow-up 18.0 (485) 12.9 (360) Addictive behavior at baseline Smoking Never tried 78.2 (2166) 85.1 (2407) Tried but does not smoke 17.1 (474) 10.9 (309) Occasionally 2.3 (65) 1.9 (53) Weekly 1.2 (34) 0.8 (24) Daily 1.1 (31) 1.2 (34) Has been drunk at least once 8.1 (223) 6.3 (179) Energy drink use Never 45.3 (1258) 69.7 (1974) Occasionally 48.1 (1336) 28.4 (805) Daily 6.5 (181) 1.9 (54) Leisure activities at baseline Team sports 44.2 (1268) 26.9 (771) Individual sports 21.7 (622) 18.4 (529) Music, art or club activities 20.0 (575) 31.8 (914) Academic achievement at baseline Excellent 21.1 (595) 28.1 (797) Good 43.0 (1210) 45.3 (1286) Satisfactory 29.1 (818) 21.7 (615) Poor 6.8 (192) 5.0 (141) Socioeconomic and family background at baseline Family structure not intact 29.2 (834) 28.4 (810) Parents’ education University degree (>15 years of education) 34.8 (849) 34.0 (849) Matriculations examination/A-levels (12 years) 28.7 (700) 29.4 (735) Vocational education and training (12 years) 21.1 (515) 20.6 (514) Comprehensive school (9 years) 15.4 (376) 16.0 (401) Parents’ smoking Neither of them smokes 50.0 (1378) 49.6 (1402) Mother/father has smoked 21.7 (597) 21.4 (604) Mother/father smokes 21.2 (584) 21.3 (601) Both of them smoke 7.2 (198) 7.7 (217) 2.2. Measures In 2014 (follow-up), e-cigarette use was asked with a question “Have you sometimes used the following products?” E-cigarettes with nicotine liquid and e-cigarettes with other liquid were asked Int. J. Environ. Res. Public Health 2018,15, 305 5 of 17 separately. The options were ‘No’, ‘I have tried once or twice’, ‘I have used 20 times or less’ and ‘I have used more than 20 times’. For the analyses of experimentation, the questions were combined into a variable ‘Has tried an e-cigarette’ and it was dichotomized as ‘Not tried’ and ‘Tried’. For the analyses of use for more than twice, the questions were combined into a variable ‘Has tried an e-cigarette more than twice’ and it was dichotomized as ‘Not tried’ and ‘Tried’. The reason for combining the groups of different types of liquids was that most of the students who had tried e-cigarettes had tried both types of liquids (overlap in girls 441 and in boys 830 students). Additionally, whether the e-cigarette contains nicotine or not does not seem to be meaningful for the adolescents when they experiment with the product, and many of the adolescents do not even know about the contents of the e-liquid [18]. At baseline and follow-up, smoking experimentation was asked with a question: ”Have you ever smoked? If you have, how many cigarettes have you smoked altogether until now?” The options were ‘I have never tried smoking’, ‘One’, ‘About 2 to 50’ and ‘More than 50’. The variable ‘Tried smoking’ was dichotomized as ‘Not tried’ and ‘Tried’, and the variable ‘Smoked over 50 cigarettes’ was dichotomized as ‘Not smoked’ and ‘Smoked’. The inconsistent answers (N= 89) in smoking, i.e., reporting tried smoking at baseline but not tried at follow-up, were corrected so that the follow-up answer coincided with the baseline answer. List of the questions, answering options and created categories on baseline predictors can be found from Table A1. The proportion of missing answers was small for all variables (0.1–4.2%), except for parents’ education (proportion of missing answers 14%). 2.3. Attrition Analysis To assess attrition, the students who answered both surveys (=sample in the analyses, N= 5742) were compared to those students who completed only the baseline survey but not the follow-up (=attrition, N= 3755) using some answers of the baseline survey. In the attrition, there were statistically significantly (p< 0.001) more students with poorer academic achievement (e.g., poor 9.3% and excellent 20.2%) compared to the sample (poor 5.9% and excellent 24.6%). The students in the attrition also had tried more smoking (p= 0.002; 23.4%) compared to the students in the sample (18.5%). There was no statistically significant difference in the gender distribution (p= 0.795), nor in the distribution of parental education (p= 0.099). The distributions of these variables were also compared between the students in the final sample used in the analyses (N= 5742) and all the students who completed the questionnaire at baseline (N= 9497). The distributions of gender and parents’ education were very close to each other. However, students in the final sample in the analyses had better academic achievement (e.g., poor 5.9% and excellent 24.6%) compared to the original baseline sample (poor 7.2% and excellent 22.9%). Additionally, the final sample included more of those who had not tried smoking (81.5%) compared to the students who completed the questionnaire at baseline (79.5%). 2.4. Data Analysis First, any e-cigarette experimentation and experimentation more than twice, and conventional cigarette experimentation and smoking at follow-up were cross-tabulated with all independent baseline variables separately for boys and girls (not shown in tables). Second, gender stratified multilevel binary logistic regression analyses were conducted to analyze predictors for any e-cigarette experimentation and experimentation more than twice, and for experimentation with cigarettes and smoking more than 50 cigarettes at follow-up for all independent baseline variables. Then, all statistically significant independent baseline variables were included in a multivariate logistic regression model. The multilevel logistic regression analyses were conducted with generalized linear mixed models (GLMM) with school as the random effect. The variances at school-level in follow-up e-cigarette and smoking questions were of small magnitude (1.2% to 1.7%) but statistically significant. The Test of independence in Complex Samples command, which takes the clustering into account, was used to test statistical differences. IBM SPSS Statistics V.23 (IBM, Armonk, NY, USA) was used for all data analyses. Int. J. Environ. Res. Public Health 2018,15, 305 6 of 17 3. Results At follow-up in 2014, of all 15 to 16-year-old students, 34.3% had tried e-cigarettes, 43.3% of boys and 25.6% of girls (Table 1,p< 0.001 between genders). Conventional cigarette smoking had been tried at baseline by 21.8% of 12 to 13-year-old boys and 14.9% of girls in 2011 (p< 0.001), and by follow-up in 2014, 50.0% of boys and 42.3% of girls (p< 0.001) had tried conventional cigarette smoking (Table 1). 3.1. Predictors among Boys In bivariate logistic regressions (Table 2), the strongest predictors for boys’ e-cigarette experimentation at follow-up were baseline addictive behavior factors: daily (OR 61.12; 95% CI 8.30–450.0), occasional (OR 15.58; 95% CI 7.05–34.45) and weekly conventional smoking (OR 9.60; 95% CI 3.64–25.30), drunkenness at least once (OR 7.08; 95% CI 4.92–10.21) and energy drink daily use (OR 6.70; 95% CI 4.63–9.69). Family background factors and academic achievement also predicted e-cigarette experimentation, with poor academic achievement as the strongest predictor (OR 3.63; 95% CI 2.54–5.19). Participation in leisure activities was mainly negatively associated with e-cigarette experimentation, with the exception of involvement in team sports (OR 1.43; 95% CI 1.23–1.67). The predictors for boys’ conventional smoking experimentation were rather similar but stronger, e.g., drunkenness at least once (OR 15.49; 95% CI 9.09–26.40), compared to the predictors for e-cigarette experimentation, except for leisure activities, of which only participation in music, art or club activities was negatively associated with smoking experimentation (Table 2). Table 2. Odds ratios (OR) and the 95% confidence interval of multilevel binary logistic regression for follow-up e-cigarette and smoking experimentation by baseline predictors among boys. Tried E-Cigarette Tried E-Cigarette Tried Smoking Tried Smoking Bivariate Multivariate Bivariate Multivariate Model * Model ¥Model * Model ¥ Baseline Predictor OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) Addictive behavior Smoking (ref = Never tried) Tried but does not smoke 4.74 (3.78–5.94) 3.33 (2.54–4.36) n.a. n.a. Occasionally 15.58 (7.05–34.45) 7.02 (2.85–17.31) n.a. n.a. Weekly 9.60 (3.64–25.30) 5.04 (1.64–15.50) n.a. n.a. Daily 61.12 (8.30–450.0) 19.26 (2.51–147.7) n.a. n.a. Has been drunk (ref = Never) At least once 7.08 (4.92–10.21) 2.33 (1.49–3.65) 15.49 (9.09–26.40) 9.41 (5.23–16.95) Energy drink use (ref = Never) Occasionally 3.27 (2.76–3.88) 2.23 (1.82–2.73) 3.82 (3.23–4.52) 2.95 (2.43–3.58) Daily 6.70 (4.63–9.69) 3.16 (1.92–5.19) 10.67 (6.91–16.46) 6.27 (3.65–10.77) Leisure activities Team sports (ref = No) Yes 1.43 (1.23–1.67) 1.90 (1.55–2.32) 0.93 (0.80–1.09) n.s. Individual sports (ref = No) Yes 0.80 (0.66–0.96) 1.20 (0.95–1.52) 0.86 (0.72–1.03) n.s. Music, art or club activities (ref = No) Yes 0.63 (0.52–0.77) 0.82 (0.64–1.04) 0.74 (0.62–0.90) 1.02 (0.80–1.28) Academic achievement (ref = Excellent) Good 1.67 (1.35–2.07) 1.32 (1.02–1.71) 1.94 (1.57–2.40) 1.76 (1.37–2.27) Satisfactory 2.39 (1.89–3.00) 1.38 (1.03–1.86) 3.25 (2.58–4.10) 2.14 (1.60–2.87) Poor 3.63 (2.54–5.19) 2.13 (1.31–3.46) 4.27 (2.96–6.17) 2.39 (1.48–3.86) Int. J. Environ. Res. Public Health 2018,15, 305 7 of 17 Table 2. Cont. Tried E-Cigarette Tried E-Cigarette Tried Smoking Tried Smoking Bivariate Multivariate Bivariate Multivariate Model * Model ¥Model * Model ¥ Baseline Predictor OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) Socioeconomic and family background Family structure (ref = Intact family) Other family type 1.37 (1.16–1.62) 0.95 (0.76–1.18) 1.80 (1.52–2.13) 1.18 (0.95–1.47) Parents’ education (ref = University) Matriculations 1.19 (0.96–1.46) 1.12 (0.87–1.42) 0.99 (0.81–1.22) 0.81 (0.64–1.03) examination/A-levels Vocational education 1.45 (1.15–1.82) 1.14 (0.86–1.50) 1.26 (1.00–1.58) 0.76 (0.58–1.00) and training Comprehensive school 1.40 (1.09–1.81) 1.11 (0.81–1.50) 1.49 (1.15–1.92) 0.94 (0.69–1.27) Parents’ smoking (ref = Neither of them smokes) Mother/father has smoked 1.62 (1.33–1.98) 1.38 (1.08–1.77) 1.71 (1.40–2.10) 1.48 (1.16–1.89) Mother/father smokes 1.78 (1.46–2.18) 1.60 (1.23–2.07) 2.06 (1.68–2.52) 1.72 (1.33–2.22) Both of them smoke 1.93 (1.41–2.63) 1.08 (0.71–1.63) 2.99 (2.15–4.16) 1.83 (1.21–2.77) * Bivariate model: Bivariate logistic regression, 2-level analyses, school as the random effect; ¥ Multivariate model: Multivariate logistic regression, includes all statistically significant variables from Bivariate model, 2-level analyses, school as the random effect; Note. Odds ratio (OR) is given in boldface when it indicates a statistically significant (p< 0.05) difference from the odds of the reference category; n.s. = not significant in Bivariate model; n.a. = not applicable. In multivariate logistic regressions (Table 2), the most significant predictors for boys’ e-cigarette experimentation at follow-up were baseline daily (OR 19.26; 95% CI 2.51–147.7), occasional (OR 7.02; 95% CI 2.85–17.31) and weekly conventional smoking (OR 5.04; 95% CI 1.64–15.50). Participating in team sports was also a predictor for boys’ e-cigarette experimentation (OR 1.90; 95% CI 1.55–2.32). The strongest predictors for boys’ smoking experimentation in the multivariate model were drunkenness at least once (OR 9.41; 95% CI 5.23–16.95) and daily energy drink use (OR 6.27; 95% CI 3.65–10.77). In analyses for e-cigarette experimentation more than twice (Table 3), the strongest risk factors from baseline were the same as for experimenting, with weekly smoking as the strongest predictor (OR 8.41; 95% CI 4.00–17.68). However, participating in team sports was not statistically significantly associated with e-cigarette experimentation more than twice at follow-up. The strongest predictors for follow-up smoking of more than 50 cigarettes (Table 3) were baseline daily, weekly and occasional smoking, drunkenness at least once, and daily energy drink use. Table 3. Odds ratios (OR) and the 95% confidence interval of multilevel binary logistic regression for follow-up e-cigarette experimentation more than twice and smoking more than 50 cigarettes by baseline predictors among boys. Tried E-Cigarette Tried E-Cigarette Smoked > 50 Smoked > 50 >Twice >Twice Cigarettes Cigarettes Bivariate Multivariate Bivariate Multivariate Model * Model ¥Model * Model ¥ Baseline Predictor OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) Addictive behavior Smoking (ref = Never tried) Tried but does not smoke 3.72 (2.97–4.66) 2.36 (1.83–3.04) 6.04 (4.75–7.70) 4.11 (3.07–5.50) Occasionally 7.92 (4.72–13.29) 3.23 (1.77–5.93) 14.69 (8.59–25.10) 6.41 (3.34–12.31) Weekly 8.41 (4.00–17.68) 3.89 (1.72–8.83) 37.10 (14.91–92.34) 18.45 (6.51–52.29) Daily 8.08 (3.94–16.57) 2.38 (1.05–5.38) 49.54 (18.75–130.9) 22.91 (7.39–71.08) Int. J. Environ. Res. Public Health 2018,15, 305 8 of 17 Table 3. Cont. Tried E-Cigarette Tried E-Cigarette Smoked > 50 Smoked > 50 >Twice >Twice Cigarettes Cigarettes Bivariate Multivariate Bivariate Multivariate Model * Model ¥Model * Model ¥ Baseline Predictor OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) Addictive behavior Has been drunk (ref = Never) At least once 4.96 (3.71–6.63) 2.16 (1.51–3.10) 7.45 (5.52–10.05) 2.11 (1.41–3.14) Energy drink use (ref = Never) Occasionally 3.69 (2.96–4.61) 2.61 (2.05–3.33) 3.32 (2.61–4.24) 1.68 (1.25–2.25) Daily 5.60 (3.86–8.12) 2.36 (1.50–3.70) 7.10 (4.84–10.40) 1.80 (1.06–3.05) Leisure activities Team sports (ref = No) Yes 1.12 (0.93–1.35) n.s. 0.78 (0.64–0.96) 0.95 (0.73–1.24) Individual sports (ref = No) Yes 0.73 (0.58–0.92) 0.88 (0.68–1.15) 0.73 (0.56–0.94) 1.06 (0.77–1.46) Music, art or club activities (ref = No) Yes 0.61 (0.47–0.78) 0.74 (0.56–0.99) 0.80 (0.62–1.04) n.s. Academic achievement (ref = Excellent) Good 1.45 (1.10–1.92) 1.12 (0.82–1.53) 2.09 (1.48–2.94) 2.07 (1.35–3.16) Satisfactory 2.40 (1.80–3.20) 1.37 (0.99–1.90) 3.89 (2.76–5.50) 2.58 (1.65–4.04) Poor 4.37 (2.96–6.43) 2.09 (1.33–3.26) 5.52 (3.54–8.60) 2.75 (1.51–4.99) Socioeconomic and family background Family structure (ref = Intact family) Other family type 1.55 (1.27–1.88) 1.23 (0.98–1.56) 2.00 (1.63–2.46) 1.22 (0.92–1.62) Parents’ education (ref = University) Matriculations 1.16 (0.90–1.50) n.s. 0.97 (0.73–1.29) 0.79 (0.56–1.11) examination/A-levels Vocational education 1.28 (0.98–1.69) n.s. 1.21 (0.90–1.64) 0.81 (0.56–1.16) and training Comprehensive school 1.36 (1.00–1.84) n.s. 1.57 (1.15–2.15) 1.07 (0.73–1.58) Parents’ smoking (ref = Neither of them smokes) Mother/father has smoked 1.71 (1.35–2.16) 1.22 (0.94–1.60) 1.89 (1.45–2.46) 1.17 (0.84–1.64) Mother/father smokes 1.54 (1.21–1.96) 1.06 (0.80–1.40) 2.10 (1.62–2.72) 1.42 (1.01–2.00) Both of them smoke 1.79 (1.25–2.54) 0.87 (0.57–1.33) 3.26 (2.29–4.64) 1.43 (0.86–2.35) * Bivariate model: Bivariate logistic regression, 2-level analyses, school as the random effect; ¥ Multivariate model: Multivariate logistic regression, includes all statistically significant variables from Bivariate model, 2-level analyses, school as the random effect; Note. Odds ratio (OR) is given in boldface when it indicates a statistically significant (p< 0.05) difference from the odds of the reference category; n.s. = not significant in Bivariate model; n.a. = not applicable. 3.2. Predictors among Girls For girls, the predictors of e-cigarette experimentation were rather the same as for boys, with daily (OR 19.88; 95% CI 8.05–49.13), weekly (OR 15.52; 95% CI 5.66–42.60) and occasional conventional smoking (OR 15.18; 95% CI 7.78–29.62) having the strongest associations (Table 4). Drunkenness at least once and energy drink use were also significant predictors for e-cigarette experimentation. Of leisure activities, only music, art or club activities were statistically significantly and negatively associated with e-cigarette experimentation. In multivariate analyses, conventional daily (OR 11.19; 95% CI 3.41–36.66), weekly (OR 6.57; 95% CI 1.99–21.70) and occasional smoking (OR 6.00; 95% CI 2.82–12.77) remained as the strongest predictors. Academic achievement and parents’ conventional smoking were statistically significantly associated with e-cigarette experimentation in both models. The predictors for smoking experimentation were fairly similar but mainly stronger compared to e-cigarette experimentation, Int. J. Environ. Res. Public Health 2018,15, 305 9 of 17 with drunkenness at least once as the strongest predictor in both models (OR in Multivariate model: 7.15; 95% CI: 3.84–13.33). Table 4. Odds ratios (OR) and the 95% confidence interval of multilevel binary logistic regression for follow-up e-cigarette and smoking experimentation by baseline predictors among girls. Tried E-Cigarette Tried E-Cigarette Tried Smoking Tried Smoking Bivariate Multivariate Bivariate Multivariate Model * Model ¥Model * Model ¥ Baseline Predictor OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) Addictive behavior Smoking (ref = Never tried) Tried but does not smoke 6.82 (5.26–8.85) 3.66 (2.66–5.02) n.a. n.a. Occasionally 15.18 (7.78–29.62) 6.00 (2.82–12.77) n.a. n.a. Weekly 15.52 (5.66–42.60) 6.57 (1.99–21.70) n.a. n.a. Daily 19.88 (8.05–49.13) 11.19 (3.41–36.66) n.a. n.a. Has been drunk (ref = Never) At least once 6.95 (4.96–9.73) 1.49 (0.93–2.39) 17.51 (10.06–30.48) 7.15 (3.84–13.33) Energy drink use (ref = Never) Occasionally 4.31 (3.56–5.21) 2.42 (1.91–3.06) 6.16 (5.11–7.43) 4.34 (3.50–5.40) Daily 6.45 (3.62–11.51) 1.70 (0.78–3.71) 9.62 (4.76–19.45) 4.57 (1.86–11.21) Leisure activities Team sports (ref = No) Yes 0.98 (0.81–1.19) n.s. 1.01 (0.85–1.20) n.s. Individual sports (ref = No) Yes 0.83 (0.66–1.04) n.s. 0.80 (0.65–0.97) 1.05 (0.82–1.34) Music, art or club activities (ref = No) Yes 0.72 (0.59–0.87) 0.89 (0.70–1.12) 0.66 (0.56–0.79) 0.92 (0.75–1.13) Academic achievement (ref = Excellent) Good 2.22 (1.75–2.82) 1.71 (1.29–2.25) 2.17 (1.78–2.64) 1.74 (1.38–2.20) Satisfactory 3.06 (2.34–4.01) 1.53 (1.09–2.16) 3.93 (3.12–4.96) 2.54 (1.89–3.40) Poor 3.99 (2.64–6.03) 1.69 (0.96–2.98) 5.64 (3.78–8.42) 3.89 (2.22–6.82) Socioeconomic and family background Family structure (ref = Intact family) Other family type 1.47 (1.22–1.78) 1.00 (0.79–1.27) 1.80 (1.52–2.13) 1.21 (0.98–1.50) Parents’ education (ref = University) Matriculations 1.18 (0.93–1.50) 1.16 (0.88–1.53) 1.16 (0.94–1.43) 1.03 (0.81–1.30) examination/A-levels Vocational education 1.52 (1.18–1.98) 1.00 (0.73–1.37) 1.57 (1.24–1.97) 0.92 (0.69–1.21) and training Comprehensive school 1.31 (0.99–1.74) 0.80 (0.57–1.13) 1.60 (1.25–2.05) 0.75 (0.55–1.02) Parents’ smoking (ref = Neither of them smokes) Mother/father has smoked 1.86 (1.48–2.34) 1.32 (1.00–1.74) 1.94 (1.59–2.37) 1.42 (1.11–1.80) Mother/father smokes 2.24 (1.79–2.81) 1.54 (1.16–2.05) 2.52 (2.06–3.08) 1.75 (1.36–2.27) Both of them smoke 3.30 (2.41–4.51) 1.80 (1.20–2.69) 4.06 (2.99–5.52) 2.05 (1.39–3.02) * Bivariate model: Bivariate logistic regression, 2-level analyses, school as the random effect; ¥ Multivariate model: Multivariate logistic regression, includes all statistically significant variables from Bivariate model, 2-level analyses, school as the random effect; Note. 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