Clustering of risk-related modifiable behaviours and their association with overweight and obesity among a large sample of youth in the COMPASS study

Abstract

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.

Beyond Their HIV Status: the Occurrence of Multiple Health Risk Behavior Among Adolescents from a Rural Setting of Sub-Saharan Africa

“…This segment of adolescents may potentially represent a vulnerable sub-population with shared cumulative psychosocial risk factors which underlie an unhealthy lifestyle [10]. Our findings of the four class solution are similar to reports from other studies on HRB clustering conducted among rural Chinese [79], Canadian [80], and Dutch adolescents [11]. The proportion of adolescents in the highest risk class (5.9%) in this present study was close to composition of the highest risk group (4%) among rural Chinese adolescents [79], whose mean age (14.7 years) was also similar to the age of our participants (13.7 years).…”

Adolescent multiple risk behaviours cluster by number of risks rather than distinct risk profiles in the ALSPAC cohort

“…The classes were differentially associated with psychological distress, depression and anxiety. Using LCA, Laxer et al [12] examined the associations of 15 MRB and overweight/obesity among Canadian adolescents in grades 9 to 12 (age~14-18 years). All groups were more likely to be overweight/obese when compared to the health conscious group: traditional school athletes odds ratio (OR) = 1.15(95%CI:1.03-1.29), inactive screenagers OR = 1.33(95%CI:1.19-1.48) and moderately active substance users OR = 1.27(95%CI:1.14-1.43).…”

Noncomprehensive and Intermittent Obesity‐Related School Programs and Policies May Not Work: Evidence from the COMPASS Study

“…Approximately half of the students were female (52.5%), a large majority were white (75.9%), and just over half of students were in grade 10 (52.3%). Only 20% of students were considered to be health conscious based on previous research, whereas nearly half of students (44.9%) engaged in high amounts of screen time and low levels of physical activity ( inactive screenagers ) . Average BMI varied slightly across the schools, with discrepancies between the maximum and minimum BMI increasing annually (Y 1 : 2.51 kg/m 2 , Y 2 : 3.12 kg/m 2 , and Y 3 : 3.73 kg/m 2 ).…”

“…Finally, analyses controlled for student behavioral patterns that had been identified by a previous analysis. That analysis identified four clusters of dietary behavior, substance use, sedentary behavior, and physical activity ( Traditional School Athletes, Inactive Screenagers, Health Conscious, and Moderately Active Substance Users ) that were associated with BMI …”

“…These models accounted for the clustered nature of the COMPASS data (students within schools) and the repeated measures of participant over years Y 1 ‐Y 3 . This approach fits 3‐level linear mixed effects models (level 1: school; level 2: students within schools; and level 3: repeated BMI measures over time within students) . Models included a random intercept for school (to account for clustering students within schools) and a random intercept for participants to account for participants' BMI measures over years Y 1 ‐Y 3 .…”