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ABSTRACT

Average acceleration (AvAcc) and intensity gradient (IG) have been proposed as standardised metrics describing physical activity (PA) volume and intensity, respectively. We examined hypothesised between-group PA differences in AvAcc and IG, and their associations with health and well-being indicators in children. ActiGraph GT9X wrist accelerometers were worn for 24-h·d?1 over 7days by 145 children aged 9–10. Raw accelerations were averaged per 5-s epoch to represent AvAcc over 24-h. IG represented the relationship between log values for intensity and time. Moderate-to-vigorous PA (MVPA) was estimated using youth cutpoints. BMI z-scores, waist-to-height ratio (WHtR), peak oxygen uptake (VO2peak), Metabolic Syndrome risk (MetS score), and well-being were assessed cross-sectionally, and 8-weeks later. Hypothesised between-group differences were consistently observed for IG only (p < .001). AvAcc was strongly correlated with MVPA (r = 0.96), while moderate correlations were observed between IG and MVPA (r = 0.50) and AvAcc (r = 0.54). IG was significantly associated with health indicators, independent of AvAcc (p < .001). AvAcc was associated with well-being, independent of IG (p < .05). IG was significantly associated with WHtR (p < .01) and MetS score (p < .05) at 8-weeks follow-up. IG is sensitive as a gauge of PA intensity that is independent of total PA volume, and which relates to important health indicators in children.  相似文献   
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This study examined differences in physical activity (PA) estimates provided from raw and counts processing methods. One hundred and sixty-five children (87 girls) wore a hip-mounted ActiGraph GT3X+ accelerometer for 7 days. Data were available for 129 participants. Time in moderate PA (MPA), vigorous PA (VPA) and moderate-vigorous PA (MVPA) were calculated using R-package GGIR and ActiLife. Participants meeting the wear time criteria for both processing methods were included in the analysis. Time spent in MPA (?21.4 min.d?1, 95%CI ?21 to ?20) and VPA (?36 min.d?1, 95%CI ?40 to ?33) from count data were higher (< 0.001) than raw data. Time spent in MVPA between the two processing methods revealed significant differences (All < 0.001). Bland-Altman plots suggest that the mean bias for time spent in MPA, VPA and MVPA were large when comparing raw and count methods. Equivalence tests showed that estimates from raw and count processing methods across all activity intensities lacked equivalence. Lack of equivalence and poor agreement between raw and count processing methods suggest the two approaches to estimate PA are not comparable. Further work to facilitate the comparison of findings between studies that process and report raw and count physical activity data may be necessary.  相似文献   
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