![]() Sleep, screen time, active school travel and sport/exercise participationĪ detailed description of the questions used to assess sleep duration, screen time, active school travel and sport/exercise participation is provided as online supporting information (Additional file 1: Table S1). This MVPA cut-point was developed for the European Youth Heart Study (EYHS), is based on several validation studies and equivalent to a walking speed of > 4 km/h in children and adolescents. ![]() ![]() In order to investigate average time spent in MVPA on weekdays, we applied a cut-point of ≥2000 counts∙min − 1 (CPM) scaled to match the 10 s epochs used, and divided all time spent in MVPA by the number of valid assessment days. The different number of monitoring days is due to the limited storage capacity of the CSA 7164 model compared to the two newer models.Īfter exclusion of data recorded on weekend days, data recorded from 00:00–06:00 and intervals of ≥20 consecutive minutes with no activity counts recorded, we deemed all files with ≥2 weekdays consisting of ≥480 min of activity count recordings eligible for analysis. During school visits, we instructed the participants to wear the monitor on their right hip for four (PANCS1) and seven (PANCS2) consecutive days, and to remove the monitor for sleep and water based activities only. We programmed the accelerometers to start recording at 06:00 on the day after the participants received them, and to sample activity counts in 10 s epochs. We used the RIU (K64, Computer Science & Application Inc., Shalimar, FL) and ActiLife software (ActiGraph, LLC, Pensacola, Florida, USA) to initialize and download the accelerometers PANCS1 and PANCS2, respectively, and KineSoft (v3.3.76 KineSoft, Loughborough, United Kingdom) for further processing of the accelerometer data. In PANCS2, we used the GT1M and GT3X+ models. We assessed PA using ActiGraph accelerometers (ActiGraph, LLC, Pensacola, Florida, USA). To inform future public health strategies and interventions for children and adolescents, we examined the cross-sectional and prospective associations between sleep duration, screen time, active school travel, sport/exercise participation, and PA. In addition, a sub-sample of the participants were followed prospectively from age nine (2005–06) to 15 (2011–12) years. In the Physical Activity among Norwegian Children Study (PANCS), we have collected data on PA, sleep duration, screen time, active school travel and sport/exercise participation in randomly selected, nationally representative samples of 9- and 15-y-olds in 2005––12. Therefore, one cannot infer that organized sport participation predicts a higher PA level at a later time point. As an example, when an association between maintenance/adoption of organized sport participation associates with a beneficial change in PA, it is impossible to rule out that children who are more active and fit choose to continue or adopt organized sport participation. Prospective studies examining determinants of PA have usually modelled these associations as change in the exposure with change in the outcome, which does not determine the direction of association. However, the links between all these four potentially modifiable behaviors and PA stem predominantly from cross-sectional studies, limiting causal inference. The observed associations between the two former behaviors and PA has recently led some authorities to include recommended levels of sleep and screen time to their PA guidelines for children. Some previous research has shown sleep duration, screen time, active school travel, and sport/exercise participation to be associated with PA in children and adolescents. Therefore, there is undeniably a continued need to increase our knowledge about modifiable factors potentially influencing PA in children and adolescents. This knowledge has aided development of interventions designed to increase young people’s PA, but unfortunately, many such interventions have only had limited or moderate success thus far. Research conducted over the last two decades has identified a multitude of factors potentially important for the promotion of PA in children and adolescents. Therefore, it has become a global priority to increase PA in children and adolescents. Convincing evidence has emerged of a pronounced association between low levels of physical activity (PA) and an adverse metabolic profile already at a young age.
0 Comments
Leave a Reply. |