BackgroundFew researchers have the data required to adequately understand how the school environment impacts youth health behaviour development over time.Methods/DesignCOMPASS is a prospective cohort study designed to annually collect hierarchical longitudinal data from a sample of 90 secondary schools and the 50,000+ grade 9 to 12 students attending those schools. COMPASS uses a rigorous quasi-experimental design to evaluate how changes in school programs, policies, and/or built environment (BE) characteristics are related to changes in multiple youth health behaviours and outcomes over time. These data will allow for the quasi-experimental evaluation of natural experiments that will occur within schools over the course of COMPASS, providing a means for generating “practice based evidence” in school-based prevention programming.DiscussionCOMPASS is the first study with the infrastructure to robustly evaluate the impact that changes in multiple school-level programs, policies, and BE characteristics within or surrounding a school might have on multiple youth health behaviours or outcomes over time. COMPASS will provide valuable new insight for planning, tailoring and targeting of school-based prevention initiatives where they are most likely to have impact.

BackgroundCanadian youth exhibit a number of risky behaviours, some of which are associated with overweight and obesity. The purpose of this study was to examine the prevalence of 15 modifiable risk behaviours in a large sample of Canadian youth, to identify underlying subgroups based on patterns of health behaviours, and to examine the association between identified subgroups and overweight/obesity.MethodsData from 18,587 grades 9–12 students in Year 1 (2012–13) of the COMPASS study and latent class analysis were used to identify patterns and clustering among 15 health behaviours (e.g., physical inactivity, sedentary behaviour, unhealthy eating, substance use). A logistic regression model examined the associations between these clusters and overweight/obesity status.ResultsFour distinct classes were identified: traditional school athletes, inactive screenagers, health conscious, and moderately active substance users. Each behavioural cluster demonstrated a distinct pattern of behaviours, some with a greater number of risk factors than others. Traditional school athletes (odds ratio (OR) 1.15, 95% CI 1.03–1.29), inactive screenagers (OR 1.33; 1.19–1.48), and moderately active substance users (OR 1.27; 1.14–1.43) were all significantly more likely to be overweight/obese compared to the health conscious group.ConclusionsFour distinct subpopulations of youth were identified based on their patterns of health and risk behaviours. The three clusters demonstrating poorer health behaviour were all at an increased risk of being overweight/obese compared to their somewhat healthier peers. Obesity-related public health interventions and health promotion efforts might be more effective if consideration is given to population segments with certain behavioural patterns, targeting subgroups at greatest risk of overweight or obesity.

BackgroundThe COMPASS study is designed to follow a cohort of ~30,000 grade 9 to 12 students attending ~60 secondary schools for four years to understand how changes in school characteristics (policies, programs, built environment) are associated with changes in youth health behaviours. Since the student-level questionnaire for COMPASS (Cq) is designed to facilitate multiple large-scale school-based data collections using passive consent procedures, the Cq is only comprised of self-reported measures. The present study assesses the 1-week (1wk) test-retest reliability and the concurrent validity of the Cq measures for weight status and dietary intake.MethodsValidation study data were collected from 178 grade 9 students in Ontario (Canada). At time 1 (T1), participants completed the Cq and daily recoding of their dietary intake using the web-based eaTracker tool. After one week, (T2), students completed the Cq again, participants submitted their daily eaTracker logs and staff measured their height and weight. Test-retest reliability of the self-reported (SR) weight status and dietary intake measures at T1 and T2, and the concurrent validity of the objectively measured and SR weight status and dietary intake measures at T2 were examined using intraclass correlation coefficients (ICC).ResultsTest-retest reliability for SR height (ICC 0.96), weight (ICC 0.99), and BMI (ICC 0.95) are considered substantial. The concurrent validity for SR height (ICC 0.88), weight (ICC 0.95), and BMI (ICC 0.84) are also considered substantial. The test-retest reliability for SR dietary intake for fruits and vegetables (ICC 0.68) and milk and alternatives (ICC 0.69) are considered moderate, whereas meat and alternatives (ICC 0.41), and grain products (ICC 0.56) are considered fair. The concurrent validity for SR dietary intake identified that fruits and vegetables (ICC 0.53), milk and alternatives (ICC 0.60), and grain products (ICC 0.41) are considered fair, whereas meat and alternatives (ICC 0.34) was considered slight.ConclusionsWhile the test-retest reliability of the measures used in this study were all high, the concurrent validity of the measures was considered acceptable. The results support the use of the self-reported COMPASS weight status and dietary intake measures for use in research where objective measures are not possible.

The study objective was to estimate the proportion of excessive fast-food consumption by youth that is attributable to living and attending school in a neighbourhood with a moderate or high density of fast-food restaurants. This was a cross-sectional study of 6099 Canadian youths (aged 11-15 years) from 255 school neighbourhoods. All participants lived within 1 km of their school. The density of chain fast-food restaurants within a 1-km circular buffer surrounding each school was determined using geographic information systems. Excessive fast-food consumption (≥2 times per week) was assessed by questionnaire. Multilevel logistic regression analysis was used to examine associations. The population attributable risk estimates of excessive fast-food consumption due to neighbourhood exposure to fast-food restaurants were determined based on the prevalence of exposure and the results from the logistic regression. Eight percent of participants were excessive fast-food consumers. After adjusting for sociodemographic factors (i.e., gender, race, and socioeconomic status), it was found that youths from neighbourhoods with a moderate (odds ratio (OR), 1.68; 95% confidence interval (CI), 1.11-2.54) or high (OR 1.70; 95% CI 1.12-2.56) density of chain fast-food restaurants were more likely to be excessive fast-food consumers than were youths from neighbourhoods with no chain fast-food restaurants. Approximately 31% of excessive consumption was attributable to living in neighbourhoods with a moderate or high density of fast-food restaurants. Thus, the fast-food retail environment within which youth live and go to school is an important contributor to their eating behaviours.

BackgroundYouth are engaging in multiple risky behaviours, increasing their risk of overweight, obesity, and related chronic diseases. The objective of this study was to examine the effect of engaging in unique clusters of unhealthy behaviours on youths’ body mass index (BMI) trajectories.MethodsThis study used a linked-longitudinal sample of Grades 9 and 10 students (13 to 17 years of age) participating in the COMPASS host study. Students reported obesity-related and other risky behaviours at baseline and height and weight (to derive BMI) at baseline (2012/2013) and annually for 2 years post-baseline (2013/14 and 2014/15). Students were grouped into behavioural clusters based on response probabilities. Linear mixed effects models, using BMI as a continuous outcome measure, were used to examine the effect of engaging in clusters of risky behaviours on BMI trajectories.ResultsThere were significant differences in BMI of the four behavioural clusters at baseline that remained consistent over time. Higher BMI values were found among youth classified at baseline to be Typical High School Athletes (β = 0.232 kg/m2, [confidence interval (CI): 0.03–0.50]), Inactive High Screen-User (β = 0.348 kg/m2, CI: 0.11–0.59) and Moderately Active Substance Users (β = 0.759 kg/m2, CI: 0.36–1.15) compared to students classified as Health Conscious. Despite these baseline differences, BMI appeared to increase across all behavioural clusters annually by the same amount (β = 0.6097 kg/m2, (CI) = 0.57–0.64).ConclusionsAlthough annual increases in BMI did not differ by behavioural clusters, membership in a particular behavioural cluster was associated with baseline BMI, and these differences remained consistent over time. Results indicate that intervening and modifying unhealthy behaviours earlier might have a greater impact than during adolescence. Health promotion strategies targeting the highest risk youth as they enter secondary school might be promising means to prevent or delay the onset of obesity.