Behavioural patterns only predict concurrent BMI status and not BMI trajectories in a sample of youth in Ontario, Canada

Abstract

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.

Gender differences in the longitudinal association between multilevel latent classes of chronic disease risk behaviours and body mass index in adolescents

“…TV viewing, video games). 37 Consistent with earlier research, 5,6 our analyses indicate that there are annual increases in BMI across genders but that the predictors of the annual increase differ. Physical activity and substance use are not likely predictors of increasing BMI in females.…”

“…Similar studies that only adjusted for gender might have not found any association because they did not stratify by gender. 6 In addition, we accounted for monotone type missingness by using maximum likelihood models, based on the assumption that data are missing at random. These models are preferable over those that are based on complete case analysis because the latter assume the outcome is missing entirely at random.…”

“…Wave 1 was collected in the 2013/14 school year, Wave 2 in the 2014/15 school year and Wave 3 in the 2015/16 school year. Consistent with earlier research, 6,17 we chose to focus our attention on Ontario data as these constitute 92% of the observations for these waves of COMPASS data. Schools that participated in at least two of the three waves (n = 70 in each wave) were included in this study.…”

“…[11][12][13] Another notable shortcoming of previous research has been the lack of assessment of the role of sex/gender in the association between CDRB and obesity. 6,9,14,15 For instance, Laxer et al reported that males were associated with a higher increase in BMI, but did not conduct sex/genderspecific modelling. 6 Published studies have demonstrated sex/gender differences in BMI 16,17 and in CDRB engagement-including physical inactivity and substance use 17,18 , indicating that sex/gender-specific models are warranted.…”

“…6,9,14,15 For instance, Laxer et al reported that males were associated with a higher increase in BMI, but did not conduct sex/genderspecific modelling. 6 Published studies have demonstrated sex/gender differences in BMI 16,17 and in CDRB engagement-including physical inactivity and substance use 17,18 , indicating that sex/gender-specific models are warranted. Research has also found that physical inactivity and substance use play roles in youth overweight and obesity, 14,15,17,19,20 showing the importance of incorporating substance use, as well as sex/gender-stratified analyses, into research of obesity in youth.…”