Adolescent Time Use Clusters: A Systematic Review

Ferrar, Katia; Chang, Cindy Y.; Li, Ming; Olds, Tim

doi:10.1016/j.jadohealth.2012.06.015

Cited by 74 publications

(91 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In addition to these calls for data collection from across the whole day, there is growing recognition of the need to analyze activity patterns as multidimensional units, that is, the overall activity pattern rather than discrete activities in isolation [48,57,97,98]. This is not surprising given that "time devoted to one domain of activity takes on full meaning only when viewed in terms of its functional relation to time spent in other domains" [99, p.386].…”

Section: Variable-or Person-centered Analysesmentioning

confidence: 99%

“…For example, it is hypothesized that screen time displaces physical activity [55,56]. However, high levels of physical activity can coexist with high levels of sedentary behavior [57,58]. Therefore, unique patterns that are not represented by the aggregate-level average may be identified by person-centered rather than more traditional variable-centered approaches [59,60].…”

mentioning

confidence: 99%

“…Ferrar et al [57] identified 19 studies published in the past 10 years that used person-centered cluster analytic techniques to empirically describe adolescent time-use patterns, measured by a variety of methods including studyspecific stylized time-use estimates or established tools such as the Self-Administered Physical Activity Checklist [67]. Only one study used a 24-hour activity recall, the computer-administered Multimedia Activity Recall for Children and Adolescents (MARCA) [68].…”

mentioning

confidence: 99%

“…Although not a primary focus of their review Ferrar et al [57] did note that, with the exception of weight status, few health-related variables were included as correlates in the adolescent time-use cluster studies they reviewed.…”

mentioning

confidence: 99%

See 3 more Smart Citations

What Can Be Learned From Adolescent Time Diary Research

Hunt

McKay

2015

Journal of Adolescent Health

View full text Add to dashboard Cite

Section: Variable-or Person-centered Analysesmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

What Can Be Learned From Adolescent Time Diary Research

Hunt

McKay

2015

Journal of Adolescent Health

View full text Add to dashboard Cite

“…Until recently, research has examined relationships of movement behaviours, including sleep, sedentary behaviour, physical activity, with health indicators individually and in isolation of each other (Ferrar et al 2013), ignoring the intrinsic and empirical interactions between these behaviours (Foti et al 2011). In a review of sedentary behaviour studies, Pedisic (2014) found that most studies only partially adjusted for other behaviours on the movement continuum.…”

Section: Introductionmentioning

confidence: 99%

Associations between sleep duration, sedentary time, physical activity, and health indicators among Canadian children and youth using compositional analyses

Carson

Tremblay

Chaput

et al. 2016

Appl. Physiol. Nutr. Metab.

340

397

View full text Add to dashboard Cite

Abstract:The purpose of this study was to examine the relationships between movement behaviours (sleep duration, sedentary time, physical activity) and health indicators in a representative sample of children and youth using compositional analyses. Cross-sectional findings are based on 4169 children and youth (aged 6-17 years) from cycles 1 to 3 of the Canadian Health Measures Survey. Sedentary time (SB), light-intensity physical activity (LPA), and moderate-to vigorous-intensity physical activity (MVPA) were accelerometer-derived. Sleep duration was subjectively measured. Body mass index z scores, waist circumference, blood pressure, behavioural strengths and difficulties, and aerobic fitness were measured in the full sample. Triglycerides, high-density lipoprotein-cholesterol, C-reactive protein, and insulin were measured in a fasting subsample. The composition of movement behaviours was entered into linear regression models via an isometric log ratio transformation and was found to be associated with all health indicators (p < 0.01). Relative to other movement behaviours, time spent in SB or LPA was positively associated (p < 0.04) and time spent in MVPA or sleep was negatively associated (p < 0.02) with obesity risk markers. Similarly, LPA was positively associated (p < 0.005) and sleep was negatively associated (p < 0.03) with unfavourable behavioural strengths and difficulties scores and systolic blood pressure. Relative to other movement behaviours, time spent in SB was negatively associated (p < 0.001) and time spent in MVPA (p < 0.001) was positively associated with aerobic fitness. Likewise, MVPA was also negatively associated with several cardiometabolic risk markers (p < 0.008). Compositional data analyses provide novel insights into collective health implications of 24-h movement behaviours and can facilitate interesting avenues for future investigations.Key words: physical activity, sedentary behaviour, sleep, obesity, fitness, metabolic syndrome, cardiovascular disease, compositional analysis, children, youth.Résumé : Cette étude a pour objectif d'analyser la relation entre les comportements kinésiques (durée du sommeil, temps sédentaire, activité physique) et les indicateurs de santé dans un échantillon représentatif d'enfants et de jeunes en utilisant des analyses compositionnelles. Ces observations transversales sont basées sur 4169 enfants et jeunes (conclusions transversales sont basées sur 4169 enfants et les jeunes (âgés de 6-17 ans) des cycles 1 à 3 de l'Enquête canadienne sur les mesures de la santé. Le temps de sédentarité (« SB »), l'activité physique d'intensité légère (« LPA ») et l'activité physique d'intensité modérée à vigoureuse (« MVPA ») sont des mesures provenant d'accéléromètres. La durée du sommeil est mesurée subjectivement. Chez tous les jeunes, on mesure la cote z de l'indice de masse corporelle, le tour de taille, la pression sanguine, les forces et les faiblesses comportementales et la condition physique aérobie. Dans un sous-échantillon à jeun, on mesure les triglycérid...

show abstract