The European Journal of Public Health Advance Access published online on June 18, 2008
The European Journal of Public Health, doi:10.1093/eurpub/ckn050
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Longitudinal effects of the European smoking prevention framework approach (ESFA) project in Spanish adolescents
Carles Ariza1,2, Manel Nebot1,2, Zoa Tomás1, Emmanuel Giménez1, Sara Valmayor1, Visitación Tarilonte3 and Hein De Vries4
1 Evaluation and Intervention Methods Service, Agència de Salut Pública de Barcelona (Public Health Agency, Barcelona)
2 CIBER in Epidemiology and Public Health (CIBERESP), Spain
3 Personal Services Division, Barcelona Council, Barcelona, Spain
4 Health Education Department, Maastricht University, Maastricht, The Netherlands
Correspondence: Carles Ariza, Evaluation and Intervention Methods Service, Agència de Salut Pública de Barcelona (Public Health Agency, Barcelona), Pl. Lesseps 1, 08023 Barcelona, Spain, tel: +34 932 027743, fax: +34 932 921443, e-mail: cariza{at}aspb.es
Received October 25, 2007, accepted May 2, 2008
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
Background: To describe the effects of a Spanish smoking prevention programme in the context of an European project on regular smoking, in a sample of Barcelona adolescents. Method: A quasi-experimental design was conducted. An experimental group (EG) (1080 pupils) was exposed to programme and compared with a control group (CG) (872 students). The intervention included a school-based programme (16 sessions in 3 years), reinforcement of a smoke-free school policy, smoking cessation for teachers, brochures for parents and other community-based activities involving youth clubs and tobacco sales. Results: At 12 months, 4.5% of boys and 5.6% of girls were new smokers in the EG versus 6.7% and 11.7% in the CG (P < 0.001). At 36 months, 18.6% of boys and 31.2% of girls in the EG were regular smokers versus 21.6% of boys and 38.3% of girls in the CG (P < 0.001). The main factors associated with progression to regular smoking at 36 months were to be girl, to attend to a public school and to belong to the CG. Conclusion: These results endorse the effectiveness of multi-modal smoking prevention programmes, which include strategies with adults who influence adolescents.
Keywords: adolescence, effect evaluation, multi-modal programme, smoking prevention
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
Over the past 20 years several school-based programmes used social influences or Life Skills Training approaches.1 Social influences programmes aim to increase awareness of external factors that lead to smoking onset by modifying smoking acceptability and building smoking resistance skills.2 Life Skills Training enhances personal and social competence such as self-management and refusal skills training.3
Several studies have concluded that social influences programmes alone are ineffective in long-term prevention of smoking onset.4–6 Pentz7 demonstrated that a comprehensive community intervention, combining school-based programmes with the participation of parents and community leaders and smoke-free school policies are more effective than advertising and parent and community organisation alone.
Between 1998 and 2001, Barcelona and five European countries participated in the European Smoking Prevention Framework Approach (ESFA) project. This included a ‘global prevention’ approach: a school-based programme as part of a comprehensive approach to change smoking behaviour of parents and teachers, to create non-smoking policies in schools and other youth settings.8 According to this, this article wants to add scientific evidence that school-based interventions, reinforced by other community actions can change the smoking behaviour among adolescents.
This study was conducted in Barcelona where the PASE (Substance Abuse Prevention in the School) programme, based on a social influences model, was designed and evaluated in 1990, showing some reduction in smoking behaviour.9,10 Other follow-up studies have since been conducted in Barcelona which examined the main determinants in progression to regular smoking.11–15 These findings were used to develop this new school-based intervention and, in the context of the ESFA project, the PASE programme was renewed with complementary activities (new PASE).
The study describes the effects of a smoking prevention programme (new PASE) on regular smoking in the context of a smoking multi-modal intervention in a sample of Barcelona adolescents. Follow-up outcomes up to 36 months are available.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
Design
The ESFA project included an evaluative study, where an experimental group (EG) exposed to an intervention was compared with a control group (CG). In Barcelona, a quasi-experimental design was conducted. One of the 10 districts of the city (10th district) was selected as the EG. All the secondary schools of the district were invited to participate, and 16 of 24 accepted. In total, 46 classes of 1st year of compulsory secondary education (students aged 12–13 years old) participated in the project. The CG was composed of 37 schools (and 37 classes, one class by school), as a representative sample of the other districts. These CG schools were randomly selected after stratifying by type of school, school size, socio-economic status (SES) of the neighbourhood where students lived and the previous implementation of the former PASE programme. The stratification resulted in nine stratums that ensured that schools of each stratum had the same possibility of being included in the sample. At baseline, differences in socio-demographic variables, smoking or other substance use behaviours between EG and CG were minor, none statistically significant.16
Participants and procedure
A questionnaire was administered to 2015 students (response rate: 96.9%). A total of 1969 students (1083: EG, 886: CG) were surveyed, at the end of each year of the intervention. The questionnaire, developed and validated in Maastricht,17 was piloted during 1997–98 school year in each country, and afterwards administered by trained personnel in 1 h of class. Students were informed about confidentiality: a personal code was used to identify subjects and to match responses every year.
Three schools in the EG abandoned the project, one after year 1 and the other after year 2, two of them because the school centres were closed, and the third one because it decided to interrupt the intervention; so that, 13 of 16 schools completed the project and their data analysed. Overall, 690 of 1083 pupils (63.7%) were followed to the end of the project in the EG and 603 of 886 (68.0%) in the CG. Attrition at the end of follow-up was 36.3% in the EG and 32.0% in the CG.
Measures
The questionnaire included pupil's socio-demographic variables. Family structure and parental education were analysed. For SES status, we were unable to use parental occupation due to insufficient data especially at baseline. So that parental education and the Family Economic Capacity Index (FECI) were used. This index uses indicators such as job, electricity consumption, home rental prices or car power18 to make three classifications (<91 low, 91–114 middle, >114 high). Alcohol and other drug consumption were also considered.19 Other variables including smoking attitudes, social pressure, self-efficacy to resist pressure and subjective norms were examined using the I-Change Model that was the basis of the ESFA project.20 Perceptions about the smoking behaviour of others and the intention to smoke in the future were also studied. The main outcome measure was the prevalence of self-reported smoking, classified into four categories (regular, daily/weekly; experimenter, less than once a week; non-smoker: tried smoking once, but did not continue; never smoker).
For ethical approval, a letter was sent to the head of every school, who then informed parents. Data confidentiality was ensured by only providing general data about the survey.
Intervention
The main intervention activities in Barcelona in the three levels of the ESFA Project are summarised in table 1.
|
School-based intervention
This was built upon a pre-existing PASE programme adapted to the ESFA project (new PASE programme). It included six lessons (8 h) by previously trained teachers in year 1, six booster lessons in year 2 and five in year 3.
Smoke-free school policy
Teachers were trained about smoking prevention and how to create a smoke-free school. Information was provided about no smoking signs and smoking regulations. Teachers were offered cessation programmes.
Community intervention
This was aimed at parents and leisure time supervisors and included other strategies like posters with positive non-smoking messages and tobacco sales to minors.
A process evaluation through teachers self-reports was conducted to evaluate quality.
Statistical analysis
A bivariate analysis was conducted using 
2 test to compare EG with CG and dropouts with students remaining in the study. Among losses, we also included new students filling only one survey during the follow-up years and unvalid for the matching process. That is the reason of the big size of losses in table 2. Overall results of the ESFA project for all participating countries at 12, 24 and 30 months are available,21–23 but no specific at risk group analyses have yet been conducted. Since low socio-economic groups have a higher risk of becoming smokers,24 and also more girls start smoking earlier,13 we conducted a specific in-depth analysis to explore these two factors. Stratification by school type was also analysed, since smoking is more common in particular types of schools. The statistical package used was SPSS-PC+.25
|
While 13 schools completed the project, 3 of them were shown to participate adequately in year 1, irregularly in year 2 and not at all in year 3. To be considered as having been ‘exposed to the intervention’, 50% of activities must have been completed (right implementation). According with this, only 10 of the 13 schools were included in the analysis. To evaluate the impact of the intervention, a logistic regression analysis was performed, with the intervention as an independent variable and smoking regularly as the dependent variable. The main socio-demographic variables were also introduced in the model. Each variable was adjusted by the rest of them introduced in the model.
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
Attrition analysis
In table 2 the main socio-demographic characteristics are described, comparing EG with CG and also the total sample with the losses for the study (dropouts, non-completers ...). As the study analyses the progress from non-smoker to regular smoker, the 194 smokers at baseline (166 in EG and 28 in CG) and followed to the end were excluded from the analysis. Consequently, 524 pupils in the EG and 575 in the CG were studied for consumption progress differences. There were statistically significant differences between EG and CG in sex (more female), type of school (public), parents’ education (more primary than secondary/university) and FECI (low). Attrition analysis revealed that the losses were significantly older and more common in public schools. No gender or SES differences were found.
Tobacco use
Table 3 summarises progression from non-smoking at baseline to regular smoking at 36 months (1998–2001) in EG and CG by sex, school type and SES. In EG, 4.5% of boys and 5.6% of girls were new regular smokers at 12 months, versus 6.7% of boys and 11.7% of girls in CG. These differences were statistically significant among girls (P < 0.001). At 24 and 36 months, differences among new smokers between groups were also statistically significant for both sexes (P < 0.001). Among boys, 10.7% in EG versus 13.8% in CG smoked regularly at 24 months and 18.6% in EG versus 21.6% in CG at 36 months (NS). Among girls, 13.0% in EG versus 21% in CG smoked at 24 months and 31.2% in EG versus 38.3% in CG, at 36 months.
|
By school type, in the EG, 5.2% were new regular smokers in public schools at 12 months and 15.5% at 24 months versus 11.8 and 22.7%, respectively, in the CG, being these differences statistically significant (P < 0.001). But at 36 months, these differences disappeared. In private and subsidised schools, 5.1% were regular smokers at 12 months, 8.7% at 24 months and 21.0% at 36 months versus 8.6, 16.1 and 29.6%, respectively, in the CG (NS). At 36 months these differences were statistically significant (P < 0.001).
By SES, in the parental education, the differences were not statistically significant and two different patterns emerged. The two first years of the study more children with fathers who had primary studies started to smoke in CG than in EG and at 36 months this pattern changed. For mothers, more students in CG who had mothers with secondary/university studies started to smoke at 12 and at 24 months than in EG. The opposite happened at 36 months.
Concerning the FECI indicator, 5.0% of low-SES pupils smoked regularly at 12 months, 13.9% at 24 months and 28.6% at 36 months in the EG, versus 5.6%, 16.2 and 26.8%, respectively, in the CG (NS). Whereas, 4.9% of middle- and high-SES students at 12 months, 9.8% at 24 months and 22.2% at 36 months, smoked regularly in the EG versus 9.8%, 16.2 and 30.0%, respectively, in the CG. All are statistically significant differences (P < 0.001).
In the table 4A, there are the multivariate analysis of factors associated with progression to regular smoking at 12 and 36 months, excluding schools with poor implementation. In the short term (12 months), in the total sample, the main factors associated with progression were sex (girls) [odds ratio (OR) = 1.6; 95% confidence interval (CI): 1.0–2.5] and intervention (control) [OR = 2.0 (95% CI: 1.2–3.3)]. Stratifying by sex, the statistical significance of the intervention was also present in girls [OR = 2.2 (95% CI: 1.1–4.2)]. In the long term (36 months), factors associated with progression were sex (girls) [OR = 2.1 (95% CI: 1.6–2.8)], intervention (control) [OR = 1.4 (95% CI: 1.0–1.9)] and type of school (public) [OR = 1.3 (95% CI: 1.0–1.8)]. By sex, the statistical significance was only present in girls for intervention [OR = 1.5 (95% CI: 1.1–2.3)], type of school (public) [OR = 1.5 (95% CI: 1.0–2.2)], father's studies (secondary or university) [OR = 0.7 (95% CI: 0.6–0.9)] and mother's studies (primary) [OR = 1.2 (95% CI: 1.0–1.5)]. Table 4B collects the same multivariate, including schools with poor implementation. In this case, in the short term (12 months), and the statistical significance remained for the intervention (control) [OR = 1.6 (95% CI: 1.0, 2.7)], but it disappeared at 3rd year. However, most of the predictors remained with small or null variation in the association: sex (girls) [OR = 2.0 (95% CI: 1.6–2.7)], type of school (public) [OR = 1.3 (95% CI: 1.0–1.7)] and father's studies (secondary or university) [OR = 0.8 (95% CI: 0.7–1.0)].
|
|
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
This is the first evaluation of an intervention with a 3-year follow-up in adolescents in Spain. It evaluated an intensive comprehensive intervention in the context of the ESFA project.8 The results show that, one year post-intervention, there was a 46.9% lower onset rate in the EG compared to CG, and, at the end of the study, a 15.3% lower onset rate in the EG was obtained, both statistically significant.
Data were stratified by the main individual risk factors such as sex, type of school and SES. In the multivariate analysis, females, attending public school and intervention, were the main associated factors at the end of the study. Significant associations to progression to regular smoking were only showed in girls. Besides the intervention and attending public school, having a father with secondary/university studies and a mother with only primary studies are the main risk factors.
At 16 years, for every 2 boys who started smoking in the sample, 3 girls started. This increase in females had been observed in this cohort previously26 and also in other nations.22 It is also relevant that the effect of the intervention was only statistically significant in girls. At the end of the project, 30.7% of girls in the EG were new smokers, versus 38.3% in the CG. This suggests that girls respond better to the intervention, possibly due to the psychological and sexual maturity of females in these age groups, as previously stated,27 but we also consider that an higher risk perception for this gender in the current moment was present during the intervention and can influence a better response of girls.
Differences were also found in the effect of the intervention, by type of school. There are more regular smokers in public schools than in private or subsidised centres. By the end of the study, students attending public schools showed a worse response to the intervention than those attending non-public schools, despite ensuring they implemented a similar number of activities. This has been stated in previous studies,28,29 but it is the first evidence available in Spain.
Students with middle or high SES on the FECI show statistically significant lower rates of regular smoking in the EG than students in the CG. Girls whose father has a university education and mother a primary education would appear to have greater risk of progressing to regular smoking and worse performance in the intervention. This is difficult to interpret, but they are perhaps from middle–low social environments where parent's smoking is higher30 and therefore there is a greater possibility of these children becoming smokers. Different studies have described social inequalities in smoking onset and also in the implementation of smoking prevention interventions.31–33 It has also been stated that an intervention based on peer pressure decreases the proportion of adolescents with lower education who start smoking.34
Strengths and limitations
It is well established that a school-based programme without additional components is usually ineffective.7,35–37 However, not enough evidence about effectiveness of multi-modal smoking prevention programmes is still reported.38 That is why one of the strengths of the study is that this intervention was the first conducted in Spain that combined individual, school and community components. The pre-existing PASE programme was adapted to the ESFA framework, with the addition of new self-efficacy, general life and refusal skills activities. The programme was prepared closely with previously trained teachers. Besides, the introduction of cessation programmes for teachers and other community-based activities revealed clear differences between schools of both groups, as previously stated.39 The follow-up period of this study (3 years) and the evaluation of the multi-modal intervention are two strengths of the study and also two of the restriction criteria used by Wiehe37 to be critical with the effectiveness of school-based programmes. The results were similar to those obtained in Finland23 and Portugal22 and are consistent with previous studies that showed continuing significant effects on year 1 and 3 post intervention.3,40–47
There are study limitations relating to internal validity. In Barcelona, the pre-existing PASE programme made randomisation impossible. To minimise contamination, the EG was selected from an isolated district of the city; the intervention was offered to all schools wishing to participate in this district; and both groups were stratified according to having completed the PASE programme the previous year or not. Poor implementation of the intervention was found in 3 of the 13 schools, during year 2 and 3. According to Resnicow and Botvin,48 the main cause of the decreased effects of good programmes over time is poor implementation. We therefore analysed the model with logistic regression at 12 months including the 13 schools and the intervention was a statistically significant factor to reducing new smokers, but the significance disappeared at 24 and 36 months (table 4B). The process evaluation revealed poor implementation in these three schools during the last two years, and they were therefore excluded.
A potential problem concerning external validity is attrition.7 It has been reported that dropouts smoke more than the others.35,49 Subjects remaining in the study were mainly female, younger and attending a private/subsidised school. Nevertheless, these variables, except school type, did not influence the effect of the intervention while smoking regularly at the end of the study was adjusted for these variables in the logistic regression.
Finally, different studies have suggested a ‘school effect’ on pupil outcomes. Besides the anti-smoking policy,50,51 students smoking in the school periphery52 and the school climate53 also influenced smoking behaviour in the multi-level analysis. Although we tried to assess these influences, the lack of well defined school variables, made it impossible to measure this school effect.
There are well conducted randomised controlled trials to examine the effects of social influences interventions, but there is a lack of high-quality evidence about the effectiveness of multi-modal programmes including community interventions.38 This study conducted in Spain contributes more evidence to support that rigorous school-based programmes plus complementary actions in the schools (cessation for teachers and anti-smoking policies) and in the community (actions addressed to family and other intermediaries) can achieve significant effects after three years on adolescent smoking behaviour.
The interventions have to be intensive, reinforcing the main programme during the following years, with the acceptability and collaboration of teachers and the involvement of adults who influence adolescents. Besides, these interventions should take into account individual risk variables such as sex, type of school and SES that interfere with the final effect of the intervention on the smoking behaviour of adolescents. On this matter, the life skills training of school-based programmes could present different situations to play and analyse, according with the majority of individual characteristics of each group or school.
|
Acknowledgements |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
The authors would like to thank G.Castillo, C.Cruz, M.A.Fernández, D.Gutiérrez, P.Palau, S.Segura and M.C.Velasco, nurses from Barcelona, for their important contribution to the Project. We would also like to thank all 53 schools (co-ordinators, teachers and students), without their contribution this study would not have been possible. Finally, we appreciate Emily Ahonen's comments for the improvement of this manuscript. This research and intervention was supported by the grants: EC 2427/93 from the European Commission; Exp 99/748 from the Spanish Health Research Fund (FIS); RCESP, C03/09 from the Spanish Network of Epidemiology and Public Health Centres.
Conflict of interest: None declared.
Key points
|
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
1 Skara S, Sussman S. A review of 25 long-term adolescent tobacco and other drug use prevention program evaluations. Prev Med (2003) 37:451–74.[CrossRef][Web of Science][Medline]
2 Evans RI. Smoking in children: developing a social psychological strategy of deterrence. Prev Med (1976) 5:122–7.[CrossRef][Web of Science][Medline]
3 Botvin GJ, Eng A, Williams CL. Preventing the onset of cigarette smoking through life skills training. Prev Med (1980) 9:135–43.[CrossRef][Web of Science][Medline]
4 Sussman S, Dent CW, Stacy AW, et al. Project towards no tobacco use: implementation, process and post-test knowledge evaluation. Health Educ Res (1993) 8:109–23.
5 Elder JP, Wildey M, De Moor C, et al. The long-term prevention of tobacco use among junior high school students: classroom and telephone interventions. Am J Pub Health (1993) 83:1239–44.
6 Peterson AV Jr, Kealey KA, Mann SL, et al. Hutchinson Smoking Prevention Project: long-term randomized trial in school-based tobacco use prevention-results on smoking. J Nat Cancer Institute (2000) 92:1979–91.[CrossRef]
7 Pentz MA, MacKinnon DP, Dwyer JH, et al. Longitudinal effects of the Midwestern prevention Project on regular and experimental smoking in adolescents. Prev Med (1989) 18:304–21.[CrossRef][Web of Science][Medline]
8 De Vries H, Mudde A, Leijs I, et al. The European Smoking prevention Framework Approach (ESFA): an example of integral prevention. Health Educ Res (2003a) 18:611–26.
9 Villalbí JR, Aubà J, García González A. Resultados de un programa escolar de prevención del abuso de sustancias adictivas: proyecto piloto PASE de Barcelona [Results of a school preventive program of addictive substance abuse: the pilot PASE project of Barcelona]. Gac Sanit (1993) 7:70–7.[Medline]
10 Villalbí JR, Ballestín M, Nebot M, et al. The prevention of substance abuse in schools: a process evaluation of the adoption of a standardised education module. Promot Educ (1997) IV:15–19.
11 Ariza C, Nebot M. Factores asociados al consumo de tabaco en una muestra de escolares de enseñanza primaria y secundaria [Associated factors to smoking in a sample of Secondary and Primary students]. Gac Sanit (1995) 9:101–9.[Medline]
12 Díez E, Villalbí JR, Nebot M, et al. El inicio del consumo de tabaco en escolares: estudio transversal y longitudinal de los factores predictivos. [The onset of smoking in schoolchildren: a cross section and longitudinal study of predictive factors]. Med Clin (Barc) (1998) 110:334–9.[Medline]
13 Ariza C, Nebot M. Predictores de la iniciación al consumo de tabaco en escolares de enseñanza secundaria de Barcelona y Lleida [Predictors of smoking onset in Barcelona & Lleida schoolchildren]. Rev EspSal Pub (2002a) 76:227–38.
14 Ariza C, Nebot M. Factors associated with smoking progression among Spanish adolescents. Health Educ Res (2002b) 17:750–60.
15 Nebot M, Tomas Z, Ariza C, et al. Factors associated with smoking onset: 3-year cohort study of schoolchildren. Arch Bronconeumol (2004a) 40:495–501.[Web of Science][Medline]
16 Ariza C, Nebot M, Jané M, et al. El proyecto ESFA en Barcelona: un programa comunitario de prevención del tabaquismo en jóvenes [The ESFA Project in Barcelona: a community-based program of smoking prevention for youth]. Prev Tab (2001) 3:70–7.
17 De Vries H, Dijkstra M, Kuhlman P. Self-efficacy: the third factor besides attitudes and subjective norms as a predictor of behavioral intentions. Health Educ Res (1988) 3:273–82.
18 Ventura A, Càrcel C, Canals RM, et al. Index de capacitat económica familiar II [Family economic capacity index II] (1999) Barcelona: Gabinet de Programació. Publicacions de l’Ajuntament de Barcelona.
19 Comín E, Nebot M, Villalbí JR. Ejercicio y consumo de tabaco y alcohol de los escolares de Barcelona [Physical activity, smoking and alcohol consumption in Barcelona schoolchildren]. Gac Sanit (1989) 3:355–65.[Medline]
20 De Vries H, Backvier E, Kok G, Dijkstra M. The impact of social influences in the context of attitude, self efficacy, intention and previous behavior as predictors of smoking onset. J Applied Soc Psychol (1995) 25:237–57.[CrossRef]
21 De Vries H, Mudde A, Kremers S, et al. The European Smoking Prevention Framework Approach (ESFA): short-term effects. Health Educ Res (2003b) 18:649–63.
22 De Vries H, Dijk F, Wetzels J, et al. The European Smoking prevention Framework Approach (ESFA): effects after 24 and 30 months. Health Educ Res (2006) 21:116–32.
23 Vartiainen E, Pennanen M, Haukkala A, et al. The effects of a three-year smoking prevention programme in secondary schools in Helsinki. Eur J Public Health (2007) 17:249–56.
24 Fernández E, Schiaffino A, Borrell C, et al. Social class, education and smoking cessation: long-term follow-up of patients treated at a smoking cessation unit. Nicotine Tob Res (2006) 8:29–36.[Abstract]
25 Norussis MJ. SPSS/PC+ for the IBM/PC/XT/AT (1986) Chicago: SPSS Inc.
26 Ariza C, Nebot M, Villalbí JR, et al. Tendencias en el consumo de tabaco, alcohol y cannabis de los escolares de Barcelona (1987–1999) [Trends in smoking, alcohol and cannabis consumption of Barcelona schoolchildren (1987–1999)]. Gac Sanit (2003) 17:190–5.[CrossRef][Medline]
27 Tell GS. Cardiovascular disease risk factors related to sexual maturity in the Oslo Youth Study. J Chron Dis (1985) 38:633–42.[CrossRef][Web of Science][Medline]
28 Lippert P, Lopez H, Wunschmann E, Hoffmeister H. Necessities and possibilities fort he prevention of cardiovascular and pulmonary diseases in childhood and adolescence. Monatsschr Kinderheilkd (1982) 130:753–7.[Medline]
29 Chaix B, Guilbert P, Chauvin P. A multilevel analysis of tobacco use and tobacco consumption levels in France: are there any combination risk groups? Eur J Public Health (2004) 14:186–90.
30 Nebot M, Tomás Z, López MJ, et al. Cambios en el consumo de tabaco en la población general en Barcelona, 1983–2000 [Changes in smoking of Barcelona general population, 1983–2000]. Atención Primaria (2004b) 34:457–64.[CrossRef][Medline]
31 Scarinci IC, Robinson LA, Alfano CM, et al. The relationship between socioeconomic status ethnicity and cigarette smoking in urban adolescents. Prev Med (2002) 34:171–8.[CrossRef][Web of Science][Medline]
32 Gilman SE, Abrams DB, Buka SL. Socioeconomic status over the life course and stages of cigarette use: initiation, regular use and cessation. J Epidemiol Com Health (2003) 57:802–8.
33 Chuang YC, Cubbin C, Ahn D, et al. Effects of neighbourhood socioeconomic status and convenience store concentration on individual level smoking. J Epidemiol Com Health (2005) 59:568–73.
34 Chrone MR, Reijneveld SA, Willemsen MC, et al. Prevention of smoking in adolescents with lower education: a school based intervention study. J Epidemiol Com Health (2003) 57:675–80.
35 Stead M, Hastings G, Tudor-Smith C. Preventing adolescent smoking: a review of options. Health Educ J (1996) 55:31–54.
36 Backinger CL, Fagan P, Matthews E, Grana R. Adolescent and young adult tobacco prevention and cessation: current status and future directions. Tobacco Control (2003) 12(Suppl IV):iv46–53.
37 Wiehe SE, Garrison MM, Christakis DA, et al. A systematic review of school-based smoking prevention trials with long-term follow-up. J Adolesc Health (2005) 36:162–9.[CrossRef][Web of Science][Medline]
38 Thomas R. School-based programmes for preventing smoking (Cochrane Review). The cochrane library (2004) Chichester, UK: John Wiley & Sons, Ltd.
39 Valmayor S, Ariza C, Tomás Z, Nebot M. Evaluación de una intervención de prevención del tabaquismo en el entorno escolar [Evaluation of a school-based smoking prevention intervention]. Prev Tab (2004) 6:18–25.
40 Pentz MA. Effective prevention programs for tobacco use. Nicotine Tob Res (1999) 1(Suppl 2):S99–107.[Abstract]
41 Telch MJ, Killen JD, McAllister AL, et al. Long-term follow-up of a pilot project on smoking prevention with adolescents. J Behav Med (1982) 5:1–8.[CrossRef][Web of Science][Medline]
42 Vartiainen E, Paavola M, McAlister A, Puska P. Fifteen year follow-up of smoking prevention effects in the North Karelia youth project. Am J Pub Health (1998) 88:81–5.
43 Perry CL, Kelder SH, Murray DM, Klepp KI. Communitywide smoking prevention: long-term outcomes of the Minnesota Heart Health Program and the Class of 1989 Study. Am J Pub Health (1992) 82:1210–6.
44 Klepp KI, Tell G, Vellar OD. Ten-year follow-up of the Oslo Youth Study. Smoking Prevention Program [see comments]. Prev Med (1993) 22:453–62.[CrossRef][Web of Science][Medline]
45 Botvin GJ, Baker E, Dusenbury L, et al. Long-term follow-up results of a randomized drug abuse prevention trial in a white middle class population. JAMA (1995) 273:1106–12.
46 Sussman S, Sun P, McCuller WJ, et al. Project Towards No Drug Abuse: two- year outcomes of a trial that compares health educator delivery to self-instruction. Prev Med (2003) 37:155–62.[CrossRef][Web of Science][Medline]
47 Sussman S, Unger J, Rorhbach LA, et al. School-based smoking prevention research. J Adolesc Health (2005) 37:4.[CrossRef][Web of Science][Medline]
48 Resnicow K, Botvin G. School-based substance use prevention programs: why do effects decay? Prev Med (1993) 22:484–90.[CrossRef][Web of Science][Medline]
49 Pirie PL, Murray DM, Luepker RV. Smoking prevalence in a cohort of adolescents including absentees, dropouts and transfers. Am J Pub Health (1988) 78:176–8.
50 Pinilla J, González B, Barber P, et al. Smoking in young adolescents: an approach with multilevel discrete choice models. J Epidemiol Com Health (2002) 56:227–32.
51 Hamilton G, Cross D, Lower T, et al. School policy: what helps to reduce teenage smoking? Nicotine Tob Res (2003) 5:507–13.[Web of Science][Medline]
52 Leatherdale ST, Brown KS, Cameron R, et al. Social modelling in the school environment, student characteristics, and smoking susceptibility: a multilevel analysis. J Adolesc Health (2005) 37:330–6.[CrossRef][Web of Science][Medline]
53 Sellström E, Bremberg S. Is there a "school effect" on pupil outcomes? A review of multilevel studies. J Epidemiol Com Health (2006) 60:149–55.
CiteULike 
Connotea 
Del.icio.us What's this?
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||