Examination of body image among Canadian adolescents: Relations with physical activity and screen time

Background: Adolescence is a period of life associated with self-perceptions of negative body image. Physical activity levels are low and screen time levels are also high during this stage. These perceptions and behaviours are associated with poor health outcomes, making research on their determinants important. With adolescent populations, certain groups may be at higher risk of body dissatisfaction than others, and body dissatisfaction may influence individual physical activity and screen time levels. Objectives: The objectives of this thesis were to: 1) describe body image among young Canadians, examining possible health inequalities 2) estimate the strength and significance of associations between body satisfaction, physical activity and screen time, and 3) examine the potential etiological role of biological sex. Methods: Objective 1: The 2013/2014 Health Behaviour in School-aged Children study was employed. Sex-stratified Rao-Scott chi-square analyses were conducted to examine associations between socio-demographic factors and body satisfaction. Objective 2: The 2005/2006 and 2013/2014 cross-sectional and 2006 longitudinal HBSC data sets were used. Sex-stratified modified Poisson regressions were conducted and risk estimates and associated confidence intervals obtained. Results: Objective 1: Among males, being older, of East and Southeast Asian ethnicity, and reporting low SES all were associated with body dissatisfaction. Among females, being older, of Arab and West Asian or African ethnicity, being born in Canada, and reporting low SES were all associated with being body dissatisfied. Objective 2: Cross-sectionally, males who reported ‘too fat’ body dissatisfaction were more likely to be physically inactive. Adolescents of both sexes who reported ‘too fat’ body dissatisfaction were more likely to engage in high levels of screen time. Data from the longitudinal component supported the idea that male ‘too fat’ body dissatisfaction temporally leads to physical inactivity, but showed an inverse relationship between body dissatisfaction and screen time. Conclusions: Objective 1: Future prevention efforts in Canada should target subgroups to effectively help those at greatest risk of body dissatisfaction, and ameliorate potential inequalities at the population level. Objective 2: The presence of these relationships may inform future interventions as part of a multi-factorial etiology, in order to increase physical activity and decrease screen time among youth.

The application of PCA as a movement pattern recognition technique: A proof of principle

Quantitative methods can help us understand how underlying attributes contribute to movement patterns. Applying principal components analysis (PCA) to whole-body motion data may provide an objective data-driven method to identify unique and statistically important movement patterns. Therefore, the primary purpose of this study was to determine if athletes’ movement patterns can be differentiated based on skill level or sport played using PCA. Motion capture data from 542 athletes performing three sport-screening movements (i.e. bird-dog, drop jump, T-balance) were analyzed. A PCA-based pattern recognition technique was used to analyze the data. Prior to analyzing the effects of skill level or sport on movement patterns, methodological considerations related to motion analysis reference coordinate system were assessed. All analyses were addressed as case-studies. For the first case study, referencing motion data to a global (lab-based) coordinate system compared to a local (segment-based) coordinate system affected the ability to interpret important movement features. Furthermore, for the second case study, where the interpretability of PCs was assessed when data were referenced to a stationary versus a moving segment-based coordinate system, PCs were more interpretable when data were referenced to a stationary coordinate system for both the bird-dog and T-balance task. As a result of the findings from case study 1 and 2, only stationary segment-based coordinate systems were used in cases 3 and 4. During the bird-dog task, elite athletes had significantly lower scores compared to recreational athletes for principal component (PC) 1. For the T-balance movement, elite athletes had significantly lower scores compared to recreational athletes for PC 2. In both analyses the lower scores in elite athletes represented a greater range of motion. Finally, case study 4 reported differences in athletes’ movement patterns who competed in different sports, and significant differences in technique were detected during the bird-dog task. Through these case studies, this thesis highlights the feasibility of applying PCA as a movement pattern recognition technique in athletes. Future research can build on this proof-of-principle work to develop robust quantitative methods to help us better understand how underlying attributes (e.g. height, sex, ability, injury history, training type) contribute to performance.