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  • Title: Associations between sleep duration, sedentary time, physical activity, and health indicators among Canadian children and youth using compositional analyses.
    Author: Carson V, Tremblay MS, Chaput JP, Chastin SF.
    Journal: Appl Physiol Nutr Metab; 2016 Jun; 41(6 Suppl 3):S294-302. PubMed ID: 27306435.
    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.
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