Young et al. BMC Public Health 2011, 11:874 http://www.biomedcentral.com/1471-2458/11/874 school environment, teacher-pupil relationships, pupil involvement, and school engagement [47]. With one exception, all measures were obtained from pupils at age 15. Briefly, these were largely derived from Rutter like ‘school ethos’ or ‘school climate’ items [3], full details of these items and the underlying factors are available elsewhere [14]. In relation to environment, pupils rated various physical (playground, library, gym/ sports facilities, quiet places, etc.) and teacher-related (teaching, teacher control, teacher enthusiasm, etc.) aspects of their school as ‘good’, ‘average’ or ‘bad’. Fac- tor analysis produced a single dominant school environ- ment factor combining both aspects. School involvement and engagement was assessed via seven items, using 4- point (strongly agree to strongly disagree) scales. Factor analysis produced two factors, the first loaded highly with items reflecting school involvement (like school, feel part of school, etc.); the second with items reflecting school (dis)engagement (don’t like school, school a waste of time, etc.). The quality of teacher/pupil relationships was assessed by a single question, ‘how many teachers would you say you get on well with?’ with the response options, ‘all most’, ‘about half’, ‘a few’, ‘only one’, or ‘none’. Finally, to adjust for the potential perceptual bias or general negative affectivity linked to primary school experiences, a measure of prior school engagement was computed from three items (like school, school a waste of time, skip school) which pupils completed at age 11, prior to starting secondary school. A scale for each con- struct was produced by summing items loading on each factor, which were then centered. School context In order to measure school context, we computed the mean scores for every school connectedness measure for each of the 43 schools, although one school was omitted due to missing data. These were averaged within school to give an overall school ethos score. This ‘collective per- ception’ of school ethos may provide a broader, more ‘objective’ assessment of school context then individual perceptions. More objective measures of school context were also included; school roll, extracted from publicly available education reports and statistics for the years 1998/1999, divided into quintiles and ranked from small to large; school denomination, (Catholic or non-denomi- national) and a school rating score (1-9), based on eva- luations of features such as ‘welcome’, ‘organization’, ‘pupil behaviour’, etc., made by research nurses on com- pletion of the survey in each school. Statistical analysis Variables representing school connectedness and school context were centred, positive scores indicating poorer ratings, (less involvement or engagement, and fewer tea- chers known). A binary dummy variable indicated a mismatch between individual religion and school Page 7 of 15 denomination. Mismatched pupils included Catholic pupils attending a nondenominational (non-Catholic) school and non-Catholic pupils (Protestant, other reli- gious groups and those with no religious beliefs) attend- ing a Catholic school. Each of these groups describes pupils exposed to some form of mismatch between indi- vidual and institutional religious orientation. Due to low frequencies and conceptual similarity in risk, we com- bined both mismatched groups. Analyses used multilevel logistic regression to deter- mine associations between both individual and contex- tual variables and attempted suicide, suicide-risk at age 15 and self-harm at 19. Initial estimates were obtained by iterative generalized least squares estimation using the software package MLwiN 2.20 [48]. The final multi- variate models were estimated by Markov chain Monte Carlo methods [49]. In order to estimate the impact of the covariates on attempted suicide, suicide-risk and self-harm we calculated the ICC of both the and fully adjusted models. Odds ratios for both univariate and multivariate (mutually adjusted for background fac- tors) and age 11 indicators of mental health are reported. We explored the cross-level interaction between individual religion and school denomination using a dummy variable, its significance tested both uni- variately and multivariately by adding the term to the final adjusted model. Finally, in order to maximize power we used the ranked risk or likelihood of future attempted suicide’ score (for the sake of brevity hence- forth termed ‘suicidality score’) to test for an interaction using normal multilevel regression. Results Descriptive statistics Table 1 shows the prevalence rates for attempted suicide (ever) by age 15 (6.1%), suicide-risk at age 15 (9.4%) and self-harm (ever) by age 19 (6.8%), as well as frequencies of categorical covariates. Table 2 reports the descriptive statistics for the continuous covariates. Most continuous covariates are factor scores, or have been centred. Descriptive statistics for deprivation and prior depres- sion are reported uncentred, because they are estab- lished interpretable scales. The impact of missing data on centred covariates resulted in only trivial departures from zero and re-centering these made no substantive difference to results. Univariate results Tables 3, 4 and 5 show relationships between each covari- ate (grouped by type) and each outcome as univariate odds ratios. As expected, age 11 depression and victimisation were significantly associated with all outcomes, but psy- chiatric service use at or before age 11 was significantly associated with only age 15 suicide-risk. Perception of