Cannabis consumption initiation among adolescents: A longitudinal study

Addictive Behaviors 35 (2010) 129–134

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Addictive Behaviors

Cannabis consumption initiation among adolescents: A longitudinal study Anna Pérez a,b,⁎, Carles Ariza a,b, Francesca Sánchez-Martínez a,b, Manel Nebot a,b,c a b c

Evaluation and Intervention Methods Service, Public Health Agency, Barcelona, Plaça Lesseps 1, 08023, Barcelona, Spain CIBER Epidemiología y Salud Pública (CIBERESP), Spain Experimental and Health Sciences Department, Pompeu Fabra University, Barcelona (UPF-CEXS), Spain

a r t i c l e Keywords: Cannabis use Adolescents School-children Longitudinal study Initiation

i n f o

a b s t r a c t This study aimed to investigate factors related to initiation of cannabis consumption among adolescents. A questionnaire was administered to 2043 14–15-year-olds from Barcelona who were followed-up and reinterviewed after 15 months. A bivariate analysis was performed to identify the factors associated with consumption, and multivariate logistic regression was carried out to model cannabis initiation. Among matched students, 23.7% of non-users at baseline had started to consume 15 months later (23.0% boys and 24.2% girls). Among those who had reported occasional cannabis use, 30.3% reported consumption during the previous month at the follow-up survey. Factors associated with cannabis initiation among boys and girls were smoking, risky alcohol use and intention to consume cannabis. Among boys, other associated factors were frequenting bars or discotheques and not having organized activities in leisure time. Among girls, another risk factor for initiation was having cannabis-using friends. Cannabis initiation was facilitated by legal drug use, favorable attitudes and context-related variables. These results highlight the role of behavioral and contextual variables and support the importance of reinforcing social skills in preventive programs. © 2009 Elsevier Ltd. All rights reserved.

1. Introduction Among all the illegal addictive substances, cannabis is currently the most commonly consumed drug in Western countries (Pallarés, Díaz, Barruti, & Espluga, 2005; Walters, 2007). Experimentation with cannabis tends to occur among peers, and is mostly related to leisure time. High social tolerance of consumption, together with increased availability, has led to a decline in risk perception (Bobes, Calafat, & editors, 2000; Plan Nacional Sobre Drogas, 2006). In addition, some studies have shown that the increase in consumption is related to a fall in the age of initiation (Monshouwer, Smit, DE Graaf, van Os, & Vollebergh, 2005). Although trends in cannabis consumption largely differ among European countries, an overall increase in use was observed in most countries during the 1990 s, in addition to a marked increase in treatment demands for cannabis-related problems. Although the prevalence of cannabis use remains high, recent studies suggest a steady or even decreasing trend (EMCDDA, 2008). The reasons for this change are not well known, but might in part be related to changes in perceptions of associated risks, as well as changing attitudes to cigarette smoking (Myers & Prochaska, 2008; EMCDDA, 2008). However, the prevalence of cannabis

⁎ Corresponding author. Evaluation and Intervention Methods Service, Public Health Agency of Barcelona, Plaça Lesseps 1, 08023, Barcelona, Spain. Tel.: + 34 93 202 77 49; fax: + 34 93 292 14 43. E-mail addresses: [email protected] (A. Pérez), [email protected] (C. Ariza), [email protected] (F. Sánchez-Martínez), [email protected] (M. Nebot). 0306-4603/$ – see front matter © 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.addbeh.2009.09.018

use in Europe remains high, with a considerable number of regular and intensive users in many countries (EMCDDA, 2008). Spain is one of the European countries with the highest prevalence of cannabis use. In 2007, the prevalence of cannabis use during the previous year among 15–24-year-olds was 24.3%, while that during the previous month was 18.6%. These figures are higher than the European means of 16.7% and 9.1%, respectively (EMCDDA, 2008). Some studies suggest that experimentation and sporadic use might have stabilized, while monthly and daily consumption continue to rise (Plan Nacional Sobre Drogas, 2007b). Within Spain, Catalonia is one of the regions with the highest rates of consumption (Plan Nacional Sobre Drogas, 2006, 2007a). The results of a survey carried out in Barcelona (Catalonia's capital) in 2005 indicated that experimental use in young people aged between 14 and 15 years old had risen considerably among both boys and girls in recent years; the prevalence of consumption in 2005 was around 37%, twice the observed prevalence in 2000 (Morales, Ariza, Nebot, Perez, & Sanchez, 2008; Nebot, Gimenez, Ariza, & Tomas, 2006). A growing number of studies have analyzed the health consequences of cannabis use. Thus, complications associated with cannabis use have been reported in a variety of organs and systems (Walters, 2007; Gruber & Pope, 2002). Nevertheless, most of the social impact of cannabis use derives from its psychoactive properties (Hall, 2006; Arseneault et al., 2002). The influence of cannabis use on behavior, including impaired school and job performance (Bray, Zarkin, Ringwalt, & Qi, 2000), social isolation (Ashton, 2001; Diego, Field, & Sanders, 2003), risky sexual behaviors and traffic accidents (Hall & Babor, 2000; Bobes, 2006), have been described. These effects of consumption are stronger when the age

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of initiation is lower (Arseneault et al., 2002). According to the Spanish Drug Use Observatory, treatments for cannabis abuse and dependence, as well as the prevalence of consumption-related medical problems seen in emergency departments, have increased in the last few years (Plan Nacional Sobre Drogas, 2006). Knowledge of the factors associated with initiation of cannabis use is crucial for the development of effective prevention programs. So far, most studies addressing these factors carried out in Spain have used a cross-sectional design and have not allowed the natural history of cannabis consumption to be clearly identified. Longitudinal studies are the appropriate design to identify predictive factors of cannabis initiation or progression (Guxens, Nebot, & Ariza, 2007a). These studies have reported a range of risk factors for initiation but most have considered only a few variables, although the range of potential risk factors is wide. Such studies would probably need to include a larger set of independent variables to obtain sufficiently explicative predictive models (Kosterman, Hawkins, Guo, Catalano, & Abbott, 2000; Hammer & Vaglum, 1990; von Sydow, Lieb, Pfister, Hofler, & Wittchen, 2002; Poikolainen et al., 2001; Pedersen, Mastekaasa, & Wichstrom, 2001; Bailey & Hubbard, 1990; Diego et al., 2003; Brook, Kessler, & Cohen, 1999; Hofler et al., 1999; Guxens, Nebot, Ariza, & Ochoa, 2007b; Guxens, Nebot, & Ariza, 2006; Kandel, Yamaguchi, & Chen, 1992; Kandel & Logan, 1984; Anthony, 2002; Morral, McCaffrey, & Paddock, 2002a,b; Bobes et al., 2000). Given the scarcity of longitudinal studies exploring the risk factors for cannabis initiation and the natural history of consumption in Spain, and taking into account previous results showing that the greatest absolute increase in consumption occurred between the third year (ninth grade) and fourth year (tenth grade) of secondary school (Guxens et al., 2007a) we designed the present study. The objective of this study was to identify the factors associated with initiation of cannabis consumption among a cohort of secondary school students in Barcelona. 2. Methods 2.1. Design and selection of the sample A longitudinal study was carried out among a sample of 1 328 schoolchildren aged 14–15 years old from 47 secondary education centers in Barcelona. The students were attending their third year of secondary school (ninth grade) during the 2004–2005 academic year. The centers were randomly selected as a comparison group in a study designed to evaluate the effectiveness of a specific cannabis use preventive intervention. The sample was representative of the school distribution in the city according to the Family Economic Capacity Index (FECI) of the neighborhood and type of school. 2.2. Procedure Data were obtained through a self-reported questionnaire. The questionnaire was administered, taking 1 h of class time, by personnel from the Public Health Agency, Barcelona without participation by the teachers of each school. Measurements were made at two time points. Baseline data were obtained between January and March of 2005, while the follow-up questionnaire was administered between April and May, 2006. A personal, alphanumeric code based on the student's date of birth and initials of their parents' names allowed the baseline questionnaires to be linked to the follow-up questionnaires. 2.3. Variables The questionnaire included the following demographic variables: sex, age (years), type of school, socioeconomic position, family situation, self-perceived academic performance, and amount of weekly personal allowance. The type of school was categorized into state, private or

subsidized. As an approximation to socioeconomic position, the FECI, which was developed and validated in 1996, was used (Ventura, Canals, García, Pujol, & Tomás, 1999). This ecologic score reflects the wealth of the student's neighborhood of residence, which, for the purpose of the analysis, was categorized as high, medium or low. A question on family situation referred to whether the family lived in a bi-parental household or other situations. The students had to indicate their perceived relative position regarding academic performance (high, medium or low). The students' weekly allowance was categorized as 0 euros, less than 10euros, 10–30 euros and more than 30 euros. Students were asked about consumption of substances such as smoking cigarettes, drinking alcohol and cannabis use. Occasional smokers were those who reported smoking cigarettes at least once a month but not every week. Regular smokers were those who declared smoking at least once a week. Risky alcohol consumption was defined as having been drunk at least once or having drunk five or more alcoholic beverages on one occasion. According to cannabis consumption, students were classified as non-users (having never tried it), occasional users (having consumed it at least once but not in the previous 30 days) and previous month users (having consumed it in the previous 30 days). A cannabis user was defined as a student who had used cannabis at least once (grouping occasional users and previous month users together). The students were also asked about cannabis use by friends and fellow students. Two questions about leisure time were asked mainly to identify participation in organized activities (i.e. playing sport or attending a youth club) and going out to bars or discotheques. Antisocial behaviors were studied through four items identified in previous studies, related to individual behavior: “truancy”, “getting into fights”, “breaking things”, and “stealing things from others” (Nebot et al., 2006). Among the psychosocial variables studied, “self-efficacy” was defined as the ability to refuse an offer to consume cannabis products. The intention to consume cannabis in the future was also investigated. The role of expectations about the effects of consuming cannabis was measured through six items obtained by factorial analysis from the short version of the “Marijuana Effects Expectancy Questionnaire” (Aarons, Brown, Stice, & Coe, 2001; Schafer & Brown, 1991; Simons & Carey, 2003). The adolescents were asked about the expected consequences of cannabis on the intellect, behavior, relaxation, social and sexual relations, cognitive and perceptive capacity, and health, as well as about withdrawal syndrome. 2.4. Statistical analysis To study the natural history of cannabis consumption and associated factors, the baseline and the follow-up survey databases were matched, using the personal code. Matched individuals (n= 1 328) were compared with those who completed the first questionnaire but not the second (n =715). A bivariate analysis was carried out to study differences in sociodemographic and substance use characteristics associated with the follow-up status. Percentages (for qualitative variables) were compared using the х2 test, while means (for quantitative variables) were compared using Student's t test. Initiation of consumption and related factors were studied among followed-up adolescents who were non-consumers in the third year of secondary school (ninth grade). A bivariate analysis was initially done and statistically significant variables (p b 0.05) were included in the multivariate analysis. Logistic regression analysis was carried out, in which the dependent variable was cannabis consumption defined as non-user (having never tried it) and cannabis user (having consumed it at least once). The independent variables were the statistically significant variables previously described. A multivariate logistic regression analysis was carried out to obtain adjusted odds ratios (OR) with 95% confidence intervals (CI), using the backward stepwise method. The analysis was carried out using the SPSS version 13 statistical package.

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3. Results

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Table 1 Sociodemographic and drug consumption characteristics of the initial sample according to the follow up.

3.1. Attrition During the 2004–2005 academic year, the participating schools all together had 2259 students enrolled in their third secondary school year (ninth grade), of whom 2043 were surveyed (initial response rate: 90.4%). In the following academic year, the second questionnaire was administered to 1847 students in the fourth year (tenth grade). Of the initial sample surveyed, 196 students (9.6%) were lost mostly because they had repeated the course or had changed school after the third year or were absent when the second questionnaire was administered. The number of students who completed both questionnaires and whose codes could be matched was 1328 (65% of students surveyed at the baseline, 2005 and 71.9% of those surveyed at follow-up) (Fig. 1). 3.2. Cannabis consumption Table 1 describes the main sociodemographic characteristics and variables related to substance consumption in students who were followed-up and matched and compares them with those who were lost during one of those two processes. The average age of the followed-up sample was 14.4 years and 51% were girls. Half of the individuals (49.8%) lived with families with a medium FECI, and 26.7% with families with a low FECI. Sixty-nine percent of the students attended private or subsidized schools, 89% considered their academic performance to be medium or high, 81.4% lived in bi-parental families and 86% received a weekly allowance in the range of 0–10€. The prevalence of occasional cannabis use was 23.3%, and consumption during the previous month was 6.7%; 39.1% reported they occasionally smoked tobacco and 12.1% smoked regularly; 38.3% of the sample reported risky alcohol use. When matched students were compared with those who were lost to follow-up, statistically significant differences (p b 0.05) were observed for most variables. Students lost to follow-up were older, belonged to a lower socioeconomic level, were mainly boys, more frequently lived in non bi-parental families, and a higher percentage went to public schools; these students also reported lower academic performance, higher weekly allowances and more substance consumption than those followed-up. The trend in cannabis use in students followed-up from 2005 to 2006 is shown in Table 2. Of the 929 third-year students (ninth grade at baseline) who had never consumed at the baseline survey, 23.7% (n = 220) had initiated cannabis use by the following year, 18.3% of them (n = 170) being occasional users and 5.4% (n = 50) previous month users. Of those consuming occasionally (n = 310) in 2005, 30.3% (n = 94) progressed to previous month consumption 15 months later. Among those who had consumed during the previous month at baseline, 41.6% reported the same frequency of consumption by the next year. A total of 4.2% of those who reported occasional cannabis use and 2.2% of those who reported previous month use at the beginning of the study reported no cannabis use at the end of the study. Table 3 shows the results of the bivariate and multivariate analyses of the factors associated with cannabis use initiation among boys reporting

Age ( ± SD) Sex Boy Girl FECI High Medium Low Type of school Private/subsidized State Academic performance High Medium Low Family situation Two parent family Other Weekly allowance (euros) 0b 10 10–30 N30 Cannabis use Never Occasional Previous month Tobacco use Never Occasional Regular Risky alcohol use No Yes Total

Followed up

Lost to follow up

n

n

%

p-value

%

14.43 (± 0.592)

14.77 (± 0.747)

b0.001

650 677

48.9 51.0

386 328

54.1 45.9

b0.05

130 661 354

9.8 49.8 26.7

75 294 259

10.5 41.2 36.3

917 411

69.1 31.0

392 323

54.9 45.2

b0.001

428 752 130

32.2 56.6 9.8

110 399 193

15.4 55.9 27.0

b0.001

1081 247

81.4 18.6

479 214

67.1 30.0

b0.001

566 576 160 16

42.6 43.4 12.1 1.2

226 309 138 34

31.7 43.3 19.3 4.8

929 310 89

70.0 23.3 6.7

347 244 123

48.6 34.2 17.2

b0.001

636 519 161

47.9 39.1 12.1

234 268 211

32.8 37.5 29.6

b0.001

804 509 1328

60.5 38.3

305 398 715

42.7 55.7

b0.001

b0.001

b0.001

never having used cannabis at baseline. Statistically significant differences were found in cannabis initiation among legal substance (tobacco and alcohol) users and those who had cannabis-using friends. Low selfefficacy to resist offers to consume, easy access to the substance and intention to use cannabis also significantly affected initiation. Of the antisocial behavior variables, truancy was more frequent among students initiating cannabis consumption. Other factors associated with cannabis initiation were frequenting bars or discotheques and not having planned activities in leisure time. Favorable expectations about consumption showed differences in cannabis initiation but were not statistically significant. In the multivariate analysis, predictive factors for cannabis initiation among boys were occasional or regular smoking (OR=3.9; 95% CI=[2.2–7.0]), risky alcohol use (OR=2.3; 95%CI=[1.3–4.3]), frequenting bars or discotheques (OR=2.7; 95%CI=[1.3–5.7]), not having organized activities in leisure time (OR=1.8; 95%CI=[1.0–3.1]) and intending to consume cannabis (OR=5.6; 95% CI=[29–11]). Associated factors for cannabis initiation among girls are shown in Table 4. Girls who received more than 10euros a week at baseline more

Fig. 1. Attrition of matched students from baseline to follow-up.

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Table 2 Progression of self-reported cannabis use among the followed-up students. Consumption status in the 9th GRADE

No users (n = 929) Occasional users (n = 310) Previous month users (n = 89) Total 1328

Consumption status in the 10th GRADE Non-users

Occasional users

Previous month users

n (%)

n (%)

n (%)

n

170 (18.3)

50 (5.4)

220 (23.7)

13 (4.2)

203 (65.5)

94 (30.3)

297 (95.8)

2 (2.2)

50 (56.2)

37 (41.6)

87 (97.8)

724

423

181

604

frequently initiated cannabis use. Significant differences in cannabis initiation were found among girls who reported tobacco and risky alcohol use at baseline. Having cannabis-using friends, low self efficacy and reporting easy access to the substance were strongly associated with cannabis initiation as well as reporting intention to use. Going to bars and discotheques in leisure time was also associated with a higher level of cannabis initiation among non-users at baseline. The multivariate model obtained for girls included occasional or regular smoking (OR = 5.3; 95%CI = [3.0–9.4]), risky alcohol use (OR = 2.9; 95%CI = [1.6–5.0]), having cannabis-using friends (OR = 2.0; 95%CI= [1.1–3.8]) and intending to consume cannabis (OR = 3.1; 95%CI = [1.8–5.5]).

Table 3 Factors associated with cannabis use initiation among boys who were non-users at the baseline survey.

n Weekly allowance 16 (more than 10 euros) Yes 90 No Tobacco use Occasional or regular 55 Never 49 Risky alcohol use Yes 40 No 64 Cannabis use among friends Yes 74 No 33 Self efficacy No 20 Yes 79 Favorable expectations Yes 100 No 4 Easy access Yes 73 No 31 Truancy Yes 20 No 87 Leisure time in bars or discos Yes 90 No 17 Organized activities in leisure time No 60 Yes 46 Intention to consume cannabis Yes 66 No 37

p-value Crude OR

% 32.7

95% CI 0.086

Adjusted ORa 95% CI

1.8 (0.9–3.3)

p-value

Crude OR

Adjusted ORa

95% CI

95% CI

b 0.05

2.1 (1.0–4.3)

45.5 8.4

b 0.001

9.1 (5.4.15.3)

5.3 (3.0–9.4)

48.7 15.7

b 0.001

5.1 (3.2–8.1)

2.9 (1.6–5.0)

31.4 12.7

b 0.001

3.2 (1.9–5.3)

2.0 (1.1–3.8)

39.7 21.2

0.001

2.5 (1.5–4.1)

24.9 16.1

NS

1.7 (0.6–4.6)

32.7 17.6

b 0.001

2.3 (1.5–3.5)

32 22.6

0.082

1.6 (0.9–2.8)

31.3 20.6

b 0.05

2.3 (1.3–4.1)

27.1 21.3

NS

1.4 (0.9–2.1)

54.8 15.4

b 0.001

6.6 (4.1–10.7)

Cannabis user

Total users

709 (76.3)

Cannabis users

Table 4 Factors associated with cannabis use initiation among girls who were non-users at the baseline survey.

Weekly allowance 14 (more than 10 euros) Yes 98 No Tobacco use Occasional or regular 90 Never 22 Risky alcohol use Yes 58 No 53 Cannabis use among friends Yes 89 No 22 Self efficacy No 31 Yes 77 Favorable expectations Yes 107 No 5 Easy access Yes 68 No 42 Truancy Yes 24 No 87 Leisure time in bars or discos Yes 50 No 62 Organized activities in leisure time No 62 Yes 49 Intention to consume cannabis Yes 57 No 55

% 38.9 23.1

3.1 (1.8–5.5)

a Adjusted odds ratio: model includes the variables that were statistically significant in the bivariate analysis.

21.7

4. Discussion 48.7 14.3

b0.001 5.7 (3.5–9.2)

3.9 (2.2–7.0)

40.4 17.7

b0.001 3.1 (1.9–5.1)

2.3 (1.3–4.3)

28 16.4

b0.05

2.0 (1.3–3.1)

37 20.8

b0.05

2.2 (1.2–4.1)

23.4 12.5

NS

2.1 (0.7–6.2)

31.1 14.2

b0.001 2.7 (1.7–4.4)

40.8 21.1

b0.05

28.8 11.2

b0.001 3.2 (1.8–5.6)

26.9 19.2

b0.05

55.2 16.8

b0.001 6.1 (3.5–10.6)

2.6 (1.4–4.8) 2.7 (1.3– 5.7)

1.8 (1.0–3.1) 1.5 (1–2.4) 5.6 (2.9–11.0)

a Adjusted odds ratio: model includes the variables that were statistically significant in the bivariate analysis.

The findings of this study show that almost one in every four of the 14-year-olds who were non-consumers of cannabis at baseline initiated its use 15 months later, being the prevalence of total cannabis users in the fourth year (tenth grade) more than 1.5-fold that of ninth-grade cannabis users. One in every three occasional consumers at baseline increased the frequency of consumption, becoming previous month users. Among those who reported previous month use at baseline, almost half reported the same frequency of consumption at the post test. The factors identified as predictors of initiation of cannabis use for boys were smoking tobacco at least once a month, risky alcohol use, frequenting bars or discotheques, not having planned activities in leisure time and intending to use cannabis in the future. Predictive factors for girls were smoking tobacco at least once a month, risky alcohol use, having cannabis-consuming friends and intending to use cannabis. The risk of becoming a cannabis user among occasional or regular smokers was almost 4-fold greater than that of non-smokers among boys (more than 5 in the case of girls), emphasizing the current importance of smoking as a vector to cannabis use in the Spanish context. The identification of variables related to consumption of other substances as predictive factors is consistent with previous studies (Diego et al., 2003; Brook et al., 1999; Hall & Babor, 2000; von Sydow et al., 2002; Brook et al., 1980; Hofler et al., 1999; Guxens et al., 2007b). This finding would support the gateway theory, which postulates that there are sequential steps in drug initiation, starting with legal drugs that would facilitate

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cannabis use, which would then become the gateway for consumption of other illegal drugs (Kandel and Logan 1984; Kandel et al., 1992). However, this model is still controversial and other authors support theories based on a common individual factor, leading people to be prone to drug consumption and influencing each substance use in each age range (Anthony, 2002; Morral et al., 2002a,b). So far, no biochemical chains have been identified that would explain progression from certain substances to more addictive ones. Therefore, a probability relation among different consumptions might exist but was not identified in the present study (Bobes et al., 2000; Jessor, Chase, & Donovan, 1980; Van Etten & Anthony, 1999). Self-efficacy to refuse offers to consume seems to play a role in avoiding or delaying cannabis initiation, although this variable lost significance in the adjusted model. As suggested by other authors (von Sydow et al., 2002), another intermediate behavior variable, such as intending to consume cannabis in the future, appeared as a predictor of cannabis initiation among both boys and girls , stressing the need to address changes in attitudes in preventive programs (Hofler et al., 1999). Among substance availability variables, easy access to cannabis appeared as a factor facilitating cannabis consumption, as well as having friends or family who were consumers (Hofler et al., 1999; von Sydow et al., 2002), confirming the results of other studies which have associated the availability of drugs with their use (Congress of the United States, 2007) and have related consumption and social tolerance (Amos, Wiltshire, Bostock, Haw, & McNeill, 2004). In this study, however, the variable of “easy access” lost its effect when adjusted by the remaining associated factors. Another variable potentially related to substance availability is cannabis use by friends (Hofler et al., 1999; von Sydow et al., 2002), which remained statistically significant only among girls. Thus, girls may be more vulnerable than boys to peer pressure. Leisure time activities are also an important factor for cannabis use (Kuntsche, Simons-Morton, Fotiou, ter Bogt, & Kokkevi, 2009). As found in other studies (Guxens et al., 2006), frequenting bars or discotheques was a predictive factor for cannabis use among boys. In addition, having organized activities in leisure time was negatively associated with cannabis initiation, which could reflect the role of a normative environment where there are fewer opportunities to consume. Overall, these results reinforce the importance of offering activities for young people which allow them to enjoy leisure time without consuming drugs. Expectations about the effects of consuming cannabis is one of the points of interest of the present study, since this factor has been shown to have predictive value and to affect patterns of consumption in other studies (Schafer and Brown 1991; Simons, Christopher, Oliver, & Stanage, 2006). Previous results were consistent with this theory of mediation when differences between consumers and non-consumers at baseline were analyzed (Morales et al., 2008). However no statistically significant results were obtained when trends in patterns of consumption were evaluated in the multivariate logistic model. Nevertheless, changes in expectations were significantly associated with changes in intentions (Skenderian, Siegel, Crano, Alvaro, & Lac, 2008); thus, the effect of expectations on cannabis initiation could be dispelled by the “intention to use” variable. In this study, gender did not act as a predictor of cannabis initiation, although several studies have found higher consumption among boys (Kosterman et al., 2000; Hammer & Vaglum 1990; von Sydow et al., 2002; Poikolainen et al., 2001). This pattern may have been true in the past, as with smoking tobacco, but recently seems to have changed. Nevertheless, the risk factors for initiation do differ and more gender differences might have been observed if more frequent and risky cannabis use had been studied. Importantly, some studies point to an approximation of cannabis use prevalence between boys and girls when the frequency of use is low, but for daily or risky use boys remain heavier consumers (EMCDDA, 2008). These results are consistent and add more information to those found in a previous study performed in Barcelona from 1998 to 2001, which concluded that the determinants of cannabis initiation were buying tobacco, intending to use cannabis and frequenting bars and discothe-

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ques for boys. In girls, associated factors were attending a public school, smoking tobacco, risky alcohol use, antisocial behavior and intending to use cannabis (Guxens et al., 2006). Other sociodemographic predictive factors for cannabis use reported in other studies were living in a singleparent family (Kosterman et al., 2000; Hammer & Vaglum 1990; von Sydow et al., 2002; Poikolainen et al., 2001; Pedersen et al., 2001), poor academic performance (Bailey & Hubbard 1990; Diego et al., 2003), antisocial behaviors such as school absenteeism (Bailey & Hubbard 1990), some mental conditions (Diego et al., 2003) and difficulties in communicating with the family (Guxens et al., 2007b). The variable of school absenteeism showed an association only in the bivariate analysis. Mental condition and family communication were not studied. Among the limitations of this study there is selection bias as this investigation was part of the evaluation of a preventive intervention. All the selected school centers were involved in a general drug prevention program, in order to ensure that the baseline conditions for drug-related factors were similar among schools from both groups (comparison group and intervention group). In addition, losses to follow-up could have affected the results, since students who were lost to follow-up showed a higher prevalence of cannabis use at baseline and a higher proportion of risk factors, aspects which have already been observed in other studies of drug consumption in these ages (Guxens et al., 2007a). Losses to follow-up could explain why the increase in consumption among individuals followed-up was slightly lower than expected. Moreover, variables were collected based on a self-reported questionnaire, implying a possible information bias. However, the variables expected to be most affected by that bias would be those related to the context such as social variables or parental substance use, which were not identified in any of the models. This type of questionnaire has been demonstrated to have good validity and reliability in Spain for studying tobacco and alcohol, but these parameters are yet to be established for cannabis (Comín, Torrubia, Mor, Villalbí, & Nebot, 1997; Moncada & Pérez, 2002). The use of the individual code could also have led to information bias, in particular fear of being identified could have led students to alter some answers, particularly in reference to substance consumption. Furthermore, mistakes in the code resulted in the loss of individuals from the follow-up sample although in this case attrition is lower than in other studies (Galanti et al., 2007). The individual code allowed most students to be followed-up and the possibility of studying factors related to the progression of an individual's cannabis consumption. Some controversy surrounds the methods of follow-up and matching. The code created by the students is considered to contribute to attrition through loss of individuals in the matching; however, this code is also considered to reduce information bias, since it is confidential and avoids the need to request personal details. The predictive model was constructed by collapsing any frequency of cannabis use due to the sample size. Nevertheless, the indicators of cannabis consumption used in this study allow more precise estimations of the magnitude of the frequency of cannabis use than those used in most previous studies. In summary, this study adds further information to current knowledge of the natural history of cannabis consumption among students aged around 14–16 years old. Individual follow-up allows the factors associated with cannabis initiation to be identified. Starting to consume legalized addictive substances, having cannabis-using friends and not attending organized activities in leisure time (in the case of boys) increase access to cannabis and initiation of consumption. It would be interesting to study whether the risk factors identified for initiation coincide with those influencing consolidation or cessation, as postulated by some authors (Kandel et al., 1992; Hammer & Vaglum 1990). Studies with larger sample sizes are required to allow better models to be constructed for progression and cessation of consumption, taking into account the difficulties of following-up a cohort with these characteristics and the successive reduction in the number of individuals in each sub-sample. Considering the results, the possibility of increasing alternative drug-free

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leisure time activities for adolescents should be considered. Furthermore, the importance found for intermediate behavior variables confirms the need to specifically address the area of social and life skill training in preventive programs. Role of funding sources "Fundació Viure i Conviure" funded the program design and development and "Plan Nacional sobre Drogas" funded the evaluation study. Contributors None. Conflict of interest We warrant that there is no conflict of interest to declare. Acknowledgements We wish to acknowledge the teachers and students in the participating schools, and the community health teams of each district of Barcelona that collaborated in the completion of the questionnaires. The authors also thank their colleagues in the Evaluation and Intervention Methods Service from the Public Health Agency from Barcelona for their willingness to provide technical support and assistance with field work when needed. This study is partly funded by the Plan Nacional Sobre Drogas (2005) and the “Fundació Viure i Conviure” de l'Obra Social de Caixa Catalunya.

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