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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 Health2.57
· DOI :10.1186/s12889-018-5268-1
Michael M. Borghese12
Estimated H-index: 12
(Queen's University),
JanssenIan65
Estimated H-index: 65
(Queen's University)
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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 (2)
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References25
Newest
Published on Jun 27, 2016
Rahel Bürgi3
Estimated H-index: 3
,
E. D. de Bruin36
Estimated H-index: 36
Targeting the weekend to promote physical activity (PA) in children seems to be promising given that they tend to be less physically active and, particularly, as the age-related decline in PA is more marked during weekends. Considering the ambiguity of why children are not able to maintain their PA level on weekends, the aim of the present study was to objectively investigate differences in children’s spatial PA patterns between week and weekend days using the combination of Global Positioning S...
Published on Jun 1, 2016in Applied Physiology, Nutrition, and Metabolism3.46
Veronica J. Poitras13
Estimated H-index: 13
,
Casey E Gray18
Estimated H-index: 18
+ 9 AuthorsE KhoMichelle32
Estimated H-index: 32
Moderate-to-vigorous physical activity (MVPA) is essential for disease prevention and health promotion. Emerging evidence suggests other intensities of physical activity (PA), including light-intensity activity (LPA), may also be important, but there has been no rigorous evaluation of the evidence. The purpose of this systematic review was to examine the relationships between objectively measured PA (total and all intensities) and health indicators in school-aged children and youth. Online datab...
Published on Feb 1, 2016in Journal of Science and Medicine in Sport3.62
Adilson Marques14
Estimated H-index: 14
(University of Lisbon),
Ulf Ekelund78
Estimated H-index: 78
(University of Cambridge),
Luís B. Sardinha53
Estimated H-index: 53
(University of Lisbon)
Abstract Objectives The purpose of this study was to examine whether participation in organized sports is related to achieving physical activity recommendations, body mass index (BMI), objectively measured PA intensity and time spent sedentary. Design Cross-sectional study. Methods The sample comprised 973 children and adolescents (427 boys, 546 girls) aged 10-18 years (Mage=14.1±2.4). Organized sport was self-reported. Physical activity and time spent in moderate and vigorous intensity PA (MVPA...
Published on Jan 1, 2016in Pediatrics5.40
Jordan A. Carlson21
Estimated H-index: 21
(Children's Mercy Hospital),
Jasper Schipperijn23
Estimated H-index: 23
(University of Southern Denmark)
+ 8 AuthorsKelli L. Cain35
Estimated H-index: 35
(UCSD: University of California, San Diego)
OBJECTIVES: To compare adolescents’ physical activity at home, near home, at school, near school, and at other locations. METHODS: Adolescents ( N = 549) were ages 12 to 16 years (49.9% girls, 31.3% nonwhite or Hispanic) from 447 census block groups in 2 US regions. Accelerometers and Global Positioning System devices assessed minutes of and proportion of time spent in moderate to vigorous physical activity (MVPA) in each of the 5 locations. Mixed-effects regression compared MVPA across location...
S TremblayMark67
Estimated H-index: 67
,
Casey E Gray18
Estimated H-index: 18
+ 16 AuthorsCam Collyer1
Estimated H-index: 1
A diverse, cross-sectorial group of partners, stakeholders and researchers, collaborated to develop an evidence-informed Position Statement on active outdoor play for children aged 3–12 years. The Position Statement was created in response to practitioner, academic, legal, insurance and public debate, dialogue and disagreement on the relative benefits and harms of active (including risky) outdoor play. The Position Statement development process was informed by two systematic reviews, a critical ...
Casey E Gray18
Estimated H-index: 18
,
Rebecca Gibbons2
Estimated H-index: 2
+ 11 AuthorsWilliam Pickett45
Estimated H-index: 45
The objective of this systematic review was to examine the relationship between outdoor time and: (1) physical activity, (2) cardiorespiratory fitness, (3) musculoskeletal fitness, (4) sedentary behaviour; or (5) motor skill development in children aged 3–12 years. We identified 28 relevant studies that were assessed for quality using the GRADE framework. The systematic review revealed overall positive effects of outdoor time on physical activity, sedentary behaviour, and cardiorespiratory fitne...
Published on Mar 1, 2015in Medicine and Science in Sports and Exercise4.48
Jordan A. Carlson21
Estimated H-index: 21
,
Marta M. Jankowska10
Estimated H-index: 10
+ 6 AuthorsJacqueline Kerr51
Estimated H-index: 51
AB Purpose: The objective of this study is to assess validity of the personal activity location measurement system (PALMS) for deriving time spent walking/running, bicycling, and in vehicle, using SenseCam (Microsoft, Redmond, WA) as the comparison. Methods: Forty adult cyclists wore a Qstarz BT-Q1000XT GPS data logger (Qstarz International Co., Taipei, Taiwan) and SenseCam (camera worn around the neck capturing multiple images every minute) for a mean time of 4 d. PALMS used distance and speed ...
Published on Jan 1, 2015in Health & Place3.20
Charlotte Demant Klinker6
Estimated H-index: 6
(University of Southern Denmark),
Jasper Schipperijn23
Estimated H-index: 23
(University of Southern Denmark)
+ 2 AuthorsJens Troelsen18
Estimated H-index: 18
(University of Southern Denmark)
Abstract 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...
Published on Jan 1, 2015in Exercise and Sport Sciences Reviews4.74
Marta M. Jankowska10
Estimated H-index: 10
(UC: University of California),
Jasper Schipperijn23
Estimated H-index: 23
,
Jacqueline Kerr51
Estimated H-index: 51
Global Positioning Systems (GPS) are increasingly applied in activity studies, yet significant theoretical and methodological challenges remain. This paper presents a framework for integrating GPS data with other technologies to create dynamic representations of behaviors in context. Utilizing more accurate and sensitive measures to link behavior and environmental exposures allows for new research questions and methods to be developed.
Published on Jan 1, 2014in Journal of Physical Activity and Health2.08
Richard Larouche14
Estimated H-index: 14
,
Travis J. Saunders22
Estimated H-index: 22
+ 2 AuthorsS TremblayMark67
Estimated H-index: 67
Background: The impact of active school transport (AST) on daily physical activity (PA) levels, body composition and cardiovascular fitness remains unclear. Methods: A systematic review was conducted to examine differences in PA, body composition and cardiovascular fitness between active and passive travelers. The Medline, PubMed, Embase, PsycInfo, and ProQuest databases were searched and 10 key informants were consulted. Quality of evidence was assessed with GRADE and with the Effective Public ...
Cited By2
Newest
Michael M. Borghese12
Estimated H-index: 12
(Queen's University),
Emily Borgundvaag1
Estimated H-index: 1
(Queen's University)
+ 1 AuthorsJanssenIan65
Estimated H-index: 65
(Queen's University)
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.
Published on Jan 17, 2019in Applied Physiology, Nutrition, and Metabolism3.46
Anne P Macgregor (UM: University of Michigan), Michael M Borghese (UM: University of Michigan)+ 0 AuthorsIan Janssen (UM: University of Michigan)
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 estimate whether replacing time from one physical activity type with another is associated with physical and mental health indicators among children. Participants were 385 children aged 10-13 years. They wore a Global Positioning System watch and accelerometer and completed an activity log for 7 days. ...
Published on Jun 1, 2019in Journal of Sport and Health Science3.64
Laura K. Callender (Queen's University), Michael M. Borghese12
Estimated H-index: 12
(Queen's University),
JanssenIan65
Estimated H-index: 65
(Queen's University)
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,...
Published on Jun 1, 2018in Preventive medicine reports
Andrew Nguyen (Queen's University), Michael M. Borghese12
Estimated H-index: 12
(Queen's University),
JanssenIan65
Estimated H-index: 65
(Queen's University)
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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