Time use clusters of New Zealand adolescents are associated with weight status, diet and ethnicity

What Can Be Learned From Adolescent Time Diary Research

“…Cluster associations with sociodemographic, anthropometric, health, and dietary variables were analyzed. Ferrar et al [83] also used cluster analysis in their examination of New Zealand adolescents' (n ¼ 679, 10e16 years) multidimensional time use. Different activity patterns characterized the three female clusters (social sporty, screenie tasker, and super studious) and three male clusters (techno-active, quiet movers, and social studious).…”

Time Use and Daily Activities of Late Adolescents in Contemporary Ireland

“…Furthermore, Wight et al (2009) found that family income correlated positively with adolescents' paid work, homework, computer use and time eating with parents, but was negatively correlated with sleep. Looking specifically at health-related time use patterns captured with the MARCA, Ferrar, Olds, Maher, and Gomersall (2012) reported consistent time use differences amongst Australian children and adolescents (n = 2,200; 9-16 years) from the four different household income groups represented in their sample. Participants from higher income families spent significantly more time reading, doing homework, playing instruments, playing…”

“…Distinct gender specific time use clusters emerged, namely social tasker, techno-active and techno-studious for boys and social screenie, quiet active and techno-studious for girls. In New Zealand, Ferrar, Olds, Maher, and Maddison (2013) used the same method in their study of time use clusters of adolescents (n = 679, 10-16 years). Different activity patterns characterised the three girls' clusters (social sporty, screenie tasker and super studious) and three boys' clusters (techno-active, quiet movers and social studious).…”

Interactions between sleep, movement and other non‐movement behaviours in the pathogenesis of childhood obesity

“…Although underlying differences exist between the two methods, overall, both methods are person centred and identify mutually exclusive subgroups of participants that have similar patterns of movement behaviours . Few studies using these methods have investigated the association between patterns of physical activity, sedentary behaviour and sleep, and adiposity markers in children and adolescents . Evidence that does exist suggests associations may differ by sex .…”

“…Few studies using these methods have investigated the association between patterns of physical activity, sedentary behaviour and sleep, and adiposity markers in children and adolescents . Evidence that does exist suggests associations may differ by sex . For example, in a sample of approximately 20,000 youth, ‘active screenies’ (higher physical activity and higher screen time) and ‘unhealthiest movers’ (lower physical activity, shorter sleep, higher screen time) subgroups had increased odds of overweight and obesity compared to the ‘healthiest movers’ (lower screen time, longer sleep, higher physical activity) subgroup among females but not males .…”