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Development of a measurement approach to assess time children participate in organized sport, active travel, outdoor active play, and curriculum-based physical activity

Published on Dec 1, 2018in BMC Public Health2.567
· DOI :10.1186/s12889-018-5268-1
Michael M. Borghese12
Estimated H-index: 12
(Queen's University),
JanssenIan73
Estimated H-index: 73
(Queen's University)
Abstract
Children participate in four main types of physical activity: organized sport, active travel, outdoor active play, and curriculum-based physical activity. The objective of this study was to develop a valid approach that can be used to concurrently measure time spent in each of these types of physical activity. Two samples (sample 1: n = 50; sample 2: n = 83) of children aged 10–13 wore an accelerometer and a GPS watch continuously over 7 days. They also completed a log where they recorded the start and end times of organized sport sessions. Sample 1 also completed an outdoor time log where they recorded the times they went outdoors and a description of the outdoor activity. Sample 2 also completed a curriculum log where they recorded times they participated in physical activity (e.g., physical education) during class time. We describe the development of a measurement approach that can be used to concurrently assess the time children spend participating in specific types of physical activity. The approach uses a combination of data from accelerometers, GPS, and activity logs and relies on merging and then processing these data using several manual (e.g., data checks and cleaning) and automated (e.g., algorithms) procedures. In the new measurement approach time spent in organized sport is estimated using the activity log. Time spent in active travel is estimated using an existing algorithm that uses GPS data. Time spent in outdoor active play is estimated using an algorithm (with a sensitivity and specificity of 85%) that was developed using data collected in sample 1 and which uses all of the data sources. Time spent in curriculum-based physical activity is estimated using an algorithm (with a sensitivity of 78% and specificity of 92%) that was developed using data collected in sample 2 and which uses accelerometer data collected during class time. There was evidence of excellent intra- and inter-rater reliability of the estimates for all of these types of physical activity when the manual steps were duplicated. This novel measurement approach can be used to estimate the time that children participate in different types of physical activity.
  • References (25)
  • Citations (4)
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This study presents a novel method to assess context-specific physical activity patterns using accelerometer and GPS. The method efficiency is investigated by providing descriptive results on the use of domains and subdomains, and assessing how much of children’s and adolescents’ daily activity time can be classified by these domains and subdomains. Four domains and 11 subdomains were defined as important contexts for child and adolescent behaviour. During weekdays (n=367) and weekend days (n=17...
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#1Marta M. Jankowska (UC: University of California)H-Index: 11
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#1Laura K. Callender (Queen's University)
#2Michael M. Borghese (Queen's University)H-Index: 12
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Abstract Purpose The purpose of this study was to determine which intensities, patterns, and types of 24-h movement behaviors are most strongly associated with cardiometabolic risk factors among children. Methods A total of 369 children aged 10–13 years were studied. Participants wore an Actical accelerometer and a Garmin Forerunner 220 GPS logger and completed an activity and sleep log for 7 days. Data from these instruments were combined to estimate average minutes/day spent in 14 intensities,...
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Objectives To use a predominately objective measurement approach to assess and describe: (1) the amount of time that children aged 10–13 years spend participating in outdoor active play, active travel, curriculum-based physical activity at school, and organized sport; (2) the movement intensity composition of these four types of physical activity (i.e., % of time spent at a sedentary, light, or moderate-to-vigorous intensity); and (3) the proportion of each movement intensity obtained by partici...
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#2Emily Borgundvaag (Queen's University)H-Index: 1
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Background A limitation of measuring sedentary time with an accelerometer is device removal. The resulting nonwear time is typically deleted from the data prior to calculating sedentary time. This could impact estimates of sedentary time and its associations with health indicators. We evaluated whether using multiple imputation to replace nonwear accelerometer epochs influences such estimates in children.
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#1Anne P. Macgregor (Queen's University)H-Index: 1
#2Michael M. Borghese (Queen's University)H-Index: 12
Last. JanssenIan (Queen's University)H-Index: 73
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Altering the proportion of total physical activity time accumulated while participating in different types of physical activity may influence health. Our objective was to use observational data to ...
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#1Andrew Nguyen (Queen's University)
#2Michael M. Borghese (Queen's University)H-Index: 12
Last. JanssenIan (Queen's University)H-Index: 73
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Abstract This cross-sectional study examined the independent and interactive associations between objective and perceived measures of neighborhood pedestrian traffic safety and outdoor active play. A total of 458 children aged 10–13 years from Kingston, Canada were studied in 2015–2016. Outdoor active play was measured over 7 days using data from activity logs, accelerometers, and Global Positioning System loggers. Geographic Information System data were collected within 1 km of participants' ho...
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