Berten et al. BMC Public Health 2012, 12:215 http://www.biomedcentral.com/1471-2458/12/215 are overrepresented within the migrant population and due to the fact that Islamic cultures religiously and often legally prohibit the use of alcohol and cannabis [37,38], one can expect that SES differences in substance use are much more clear for native than for migrant students. As such, their religion may act as a buffer for the effect of education type on risk behaviors such as drinking alcohol or using cannabis. In summary, the present study contributes to the lit- erature by elucidating the role of education type in stu- dents’ alcohol and cannabis use, controlling for parental SES markers (i.e. parents educational level and work sta- tus). The aim of the study is twofold. First, in line with Bourdieu and Passeron [31], we expect that differences in students’ consumption pattern not merely reflect the different backgrounds of these students, but that the school environment contributes something unique. Sec- ond, given the strong representation of migrants from Islamic countries in Brussels’ schools, and given the enforcing rule of abstinence that is dictated in Islamic culture, we expect education type to have a an effect on native students’ substance use in the first place. Methods Data The data used in this study were derived from the ‘JOP- monitor Brussels’. This is a self-report school survey administered by the Youth Research Platform in 2009- 2010. The data consists of a sample (N = 2,513) of 12- 20 year old students in all grades (i.e. 1st to 6th year) of Flemish secondary education in Brussels. All Dutch- speaking secondary schools (N = 42) in the Brussels region were repeatedly invited to participate: 32 schools (76.2%) agreed to participate, a number that is quite high for this kind of surveys. The reason why the remaining ten schools did not participate is due to the fact that Flemish schools are commonly swamped with survey requests from researchers, generally resulting in a ‘first come, first served’ outcome. In each of the partici- pating schools, classes were selected randomly based on study year and type of education. This in order to achieve a balanced representation of the Brussels stu- dent population. After being informed about the pur- pose and the voluntary nature of their participation, 88,6% of the students in these 32 schools (N = 2,513) actually filled in the questionnaire. The remaining 11.4% could not participate due to absence caused by illness or class excursions. The questionnaire was administrated in the presence of a researcher and a teacher during regu- lar class periods. The data collection was approved by the Ethics Committee of the Faculty of Psychology and Educational Sciences of Ghent University. Since the subdivision between the previously described education types only exists from the 3rd year onwards, Page 3 of 9 we selected respondents in the 3rd to 6th year only, resulting in a subsample of 1,488 students (i.e. 61.8% of the total sample). Despite the high representativeness of the data on both the school and class level [39] this study suffered, like most public survey data, of a sub- stantial percentage of missing values. The variables responsible for most missing observations were the out- come variables (all around 27%), parental work status (22.7%), and parents’ educational level (23.6%). The ‘mi’ package in R developed by Gelman et al. [40] for multi- ple imputation was used to deal with the missings in the model. Measures In this paper we measured last month incidence rates of (1) beer/wine, (2) spirits and (3) cannabis by using a dichotomized scale (0) ‘abstainers and moderate users’ versus (1) ‘frequent users’. ‘Frequent users’ are those adolescents who used respectively beers/wines, spirits or cannabis more than three times in the last month. Familial socio-economic background was operationa- lized by using information about the educational and occupational level of students’ parents. Regarding the parents’ occupational status we distinguished between three categories: 1) families where both parents are unemployed; 2) families where only one parent is employed and 3) families where both parents are employed. Likewise, the parents’ educational level con- sists of three categories: 1) ‘low-educated families’ where none of the parents obtained an university degree or equivalent, 2) ‘middle-educated families’ where only one parent has a university degree or equivalent, and 3)’high-educated families’ where both parents have a university degree or equivalent. Education type in secondary school consists of three main categories: general education, technical education, and vocational education. Control variables included gender (male vs. female), age and cultural background (native vs. migrant students). ‘Native students’ are those who have the Belgian nationality, speak French or Dutch with at least one of their parents and have at least one parent of Belgian origin. Results Education type and student characteristics The results in Table 1 illustrate that the inflow of stu- dents in the different education types is strongly deter- mined by their socio-economic background. Considering the two extremes within education type, it becomes clear that 51.7% of the students in general education grow up in a two income-family. In vocational education this is the case for only 32.1% of the students. In con- trast, we counted approximately twice as much unem- ployed households in vocational education (24.4%) as