Using objective physical activity measures with youth: How many days of monitoring are needed?
ABSTRACT The purpose of this study was to establish the minimal number of days of monitoring required for accelerometers to assess usual physical activity in children.
A total of 381 students (189 M, 192 F) wore a CSA 7164 uniaxial accelerometer for seven consecutive days. To examine age-related trends students were grouped as follows: Group I: grades 1-3 (N = 92); Group II: grades 4-6 (N = 98); Group III: grades 7-9 (N = 97); Group IV: grades 10-12 (N = 94). Average daily time spent in moderate-to-vigorous physical activity (MVPA) was calculated from minute-by-minute activity counts using the regression equation developed by Freedson et al. (1997).
Compared with adolescents in grades 7 to 12, children in grades 1 to 6 exhibited less day-to-day variability in MVPA behavior. Spearman-Brown analyses indicated that between 4 and 5 d of monitoring would be necessary to a achieve a reliability of 0.80 in children, and between 8 and 9 d of monitoring would be necessary to achieve a reliability of 0.80 in adolescents. Within all grade levels, the 7-d monitoring protocol produced acceptable estimates of daily participation in MVPA (R = 0.76 (0.71-0.81) to 0.87 (0.84-0.90)). Compared with weekdays, children exhibited significantly higher levels of MVPA on weekends, whereas adolescents exhibited significantly lower levels of MVPA on weekends. Principal components analysis revealed two distinct time components for MVPA during the day for children (early morning, rest of the day), and three distinct time components for MVPA during the day for adolescents (morning, afternoon, early evening).
These results indicate that a 7-d monitoring protocol provides reliable estimates of usual physical activity behavior in children and adolescents and accounts for potentially important differences in weekend versus weekday activity behavior as well as differences in activity patterns within a given day.
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ABSTRACT: Assessing physical activity (PA) is a challenging task and many different approaches have been proposed. Direct observation (DO) techniques can objectively code both the behavior and the context in which it occurred, however, they have significant limitations such as the cost and burden associated with collecting and processing data. Therefore, this study evaluated the utility of an automated video analysis system (CAM) designed to record and discriminate the intensity of PA using a subject tracking methodology. The relative utility of the CAM system and DO were compared with criterion data from an objective accelerometry-based device (Actigraph GT3X+). Eight 10 year old children (three girls and five boys) wore the GT3X+ during a standard basketball session. PA was analyzed by two observers using the SOPLAY instrument and by the CAM system. The GT3X+ and the CAM were both set up to collect data at 30 Hz while the DO was performed every two minutes, with 10 s of observation for each gender. The GT3X+ was processed using cut points by Evanson and the outcome measure was the percentage of time spent in different intensities of PA. The CAM data were processed similarly using the same speed thresholds as were used in establishing the Evenson cut-off points (light: 4 mph). Similar outcomes were computed from the SOPLAY default analyses. A chi-square test was used to test differences in the percentage of time at the three intensity zones (light, walking and very active). The Yates’ correction was used to prevent overestimation of statistical significance for small data. When compared with GT3X+, the CAM had better results than the SOPLAY. The chi-square test yielded the following pairwise comparisons: CAM versus GT3x+ was χ 2 (5) = 24.18, p < .001; SOPLAY2 versus GT3x+ was χ 2 (5) = 144.44, p < .001; SOPLAY1 versus GT3x+ was χ 2 (5) = 119.55, p < .001. The differences were smaller between CAM and GT3x+, suggesting that the video tracking system provided better agreement than DO. The small sample size precludes a definitive evaluation but the results show that the CAM video system may have promise for automated coding of physical activity behavior.Physiological Measurement 04/2015; 36(5-5):1037. DOI:10.1088/0967-3334/36/5/1037 · 1.62 Impact Factor
1º edição 01/2014; Novas Edições Acadêmicas., ISBN: 978-3-639-68775-0
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ABSTRACT: The purpose of this study was to identify the independent association of frequency of walking trips between home and school with daily physical activity in a sample of school-aged children. Participants were 109 children (mean age = 12.05 years [±0.71]) attending nine primary schools in Adelaide, South Australia. Physical activity was derived from accelerometers with total counts as the outcome variable. Transport patterns were self-reported for each of the previous five school days. Walking trips were summed for each day and across the school week. The relationship between the number of active transport journeys and individual school day and school week physical activity was modelled separately in boys and girls using multiple linear regression. Frequency of walking was positively associated with school day and school week accelerometer counts in boys, accounting for 6% and 12% of the explained variance in total counts, respectively. There were no significant associations among girls. Despite sex-specific differences in associations between active transport to school and total physical activity, active transport is likely to have important ancillary benefits for development of independence and physical activity habits, and should continue to be promoted.BMC Public Health 05/2015; 15(1):445. DOI:10.1186/s12889-015-1765-7 · 2.32 Impact Factor