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Published in: BMC Public Health 1/2018

Open Access 01-12-2018 | Research article

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

Authors: Michael M. Borghese, Ian Janssen

Published in: BMC Public Health | Issue 1/2018

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Abstract

Background

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.

Methods

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.

Results

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.

Conclusions

This novel measurement approach can be used to estimate the time that children participate in different types of physical activity.
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Literature
1.
go back to reference Poitras VJ, Gray CE, Borghese MM, Carson V, Chaput J-P, Janssen I, et al. Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Appl Physiol Nutr Metab. 2016;41:S197–239.CrossRefPubMed Poitras VJ, Gray CE, Borghese MM, Carson V, Chaput J-P, Janssen I, et al. Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Appl Physiol Nutr Metab. 2016;41:S197–239.CrossRefPubMed
2.
go back to reference Veitch J, Salmon J, Ball K. Children’s active free play in local neighborhoods: a behavioral mapping study. Health Educ Res. 2008;23:870–9.CrossRefPubMed Veitch J, Salmon J, Ball K. Children’s active free play in local neighborhoods: a behavioral mapping study. Health Educ Res. 2008;23:870–9.CrossRefPubMed
4.
go back to reference Larouche R, Saunders TJ, Faulkner GEJ, Colley R, Tremblay M. Associations between active school transport and physical activity, body composition, and cardiovascular fitness: a systematic review of 68 studies. J Phys Act Health. 2014;11:206–27.CrossRefPubMed Larouche R, Saunders TJ, Faulkner GEJ, Colley R, Tremblay M. Associations between active school transport and physical activity, body composition, and cardiovascular fitness: a systematic review of 68 studies. J Phys Act Health. 2014;11:206–27.CrossRefPubMed
5.
go back to reference Panter JR, Jones AP, van Sluijs EM. Environmental determinants of active travel in youth: a review and framework for future research. Int J Behav Nutr Phys Act. 2008;5:34.CrossRefPubMedPubMedCentral Panter JR, Jones AP, van Sluijs EM. Environmental determinants of active travel in youth: a review and framework for future research. Int J Behav Nutr Phys Act. 2008;5:34.CrossRefPubMedPubMedCentral
6.
go back to reference Gray C, Gibbons R, Larouche R, Sandseter EBH, Bienenstock A, Brussoni M, et al. What is the relationship between outdoor time and physical activity, sedentary behaviour, and physical fitness in children? A systematic review. Int J Environ Res Public Health. 2015;12:6455–74.CrossRefPubMedPubMedCentral Gray C, Gibbons R, Larouche R, Sandseter EBH, Bienenstock A, Brussoni M, et al. What is the relationship between outdoor time and physical activity, sedentary behaviour, and physical fitness in children? A systematic review. Int J Environ Res Public Health. 2015;12:6455–74.CrossRefPubMedPubMedCentral
7.
go back to reference Tremblay MS, Gray C, Babcock S, Barnes J, Bradstreet CC, Carr D, et al. Position statement on active outdoor play. Int J Environ Res Public Health. 2015;12:6475–505.CrossRefPubMedPubMedCentral Tremblay MS, Gray C, Babcock S, Barnes J, Bradstreet CC, Carr D, et al. Position statement on active outdoor play. Int J Environ Res Public Health. 2015;12:6475–505.CrossRefPubMedPubMedCentral
8.
go back to reference Collins P, Al-Nakeeb Y, Nevill A, Lyons M. The impact of the built environment on young People’s physical activity patterns: a suburban-rural comparison using GPS. Int J Environ Res Public Health. 2012;9:3030–50.CrossRefPubMedPubMedCentral Collins P, Al-Nakeeb Y, Nevill A, Lyons M. The impact of the built environment on young People’s physical activity patterns: a suburban-rural comparison using GPS. Int J Environ Res Public Health. 2012;9:3030–50.CrossRefPubMedPubMedCentral
9.
go back to reference Biddle SJH, Atkin AJ, Cavill N, Foster C. Correlates of physical activity in youth: a review of quantitative systematic reviews. Int Rev Sport Exerc Psychol. 2011;4:25–49.CrossRef Biddle SJH, Atkin AJ, Cavill N, Foster C. Correlates of physical activity in youth: a review of quantitative systematic reviews. Int Rev Sport Exerc Psychol. 2011;4:25–49.CrossRef
10.
go back to reference Burdette HL, Whitaker RC. Resurrecting free play in young children: looking beyond fitness and fatness to attention, affiliation, and affect. Arch Pediatr Adolesc Med. 2005;159:46–50.CrossRefPubMed Burdette HL, Whitaker RC. Resurrecting free play in young children: looking beyond fitness and fatness to attention, affiliation, and affect. Arch Pediatr Adolesc Med. 2005;159:46–50.CrossRefPubMed
11.
go back to reference Marques A, Ekelund U, Sardinha LB. Associations between organized sports participation and objectively measured physical activity, sedentary time and weight status in youth. J Sci Med Sport. 2016;19:154–7.CrossRefPubMed Marques A, Ekelund U, Sardinha LB. Associations between organized sports participation and objectively measured physical activity, sedentary time and weight status in youth. J Sci Med Sport. 2016;19:154–7.CrossRefPubMed
12.
go back to reference Carlson JA, Jankowska MM, Meseck K, Godbole S, Natarajan L, Raab F, et al. Validity of PALMS GPS scoring of active and passive travel compared with SenseCam. Med Sci Sports Exerc. 2015;47:662–7.CrossRefPubMedPubMedCentral Carlson JA, Jankowska MM, Meseck K, Godbole S, Natarajan L, Raab F, et al. Validity of PALMS GPS scoring of active and passive travel compared with SenseCam. Med Sci Sports Exerc. 2015;47:662–7.CrossRefPubMedPubMedCentral
16.
go back to reference Jankowska MM, Schipperijn J, Kerr J. A framework for using GPS data in physical activity and sedentary behavior studies. Exerc Sport Sci Rev. 2015;43:48–56.CrossRefPubMedPubMedCentral Jankowska MM, Schipperijn J, Kerr J. A framework for using GPS data in physical activity and sedentary behavior studies. Exerc Sport Sci Rev. 2015;43:48–56.CrossRefPubMedPubMedCentral
17.
go back to reference Klinker CD, Schipperijn J, Toftager M, Kerr J, Troelsen J. When cities move children: development of a new methodology to assess context-specific physical activity behaviour among children and adolescents using accelerometers and GPS. Health Place. 2015;31:90–9.CrossRef Klinker CD, Schipperijn J, Toftager M, Kerr J, Troelsen J. When cities move children: development of a new methodology to assess context-specific physical activity behaviour among children and adolescents using accelerometers and GPS. Health Place. 2015;31:90–9.CrossRef
18.
go back to reference Colley R, Gorber S, Tremblay M. Quality control and data reduction procedures for accelerometry-derived measures of physical activity. Health Rep. 2010;21:63–9.PubMed Colley R, Gorber S, Tremblay M. Quality control and data reduction procedures for accelerometry-derived measures of physical activity. Health Rep. 2010;21:63–9.PubMed
19.
go back to reference Colley RC, Tremblay MS. Moderate and vigorous physical activity intensity cut-points for the Actical accelerometer. J Sports Sci. 2011;29:783–9.CrossRefPubMed Colley RC, Tremblay MS. Moderate and vigorous physical activity intensity cut-points for the Actical accelerometer. J Sports Sci. 2011;29:783–9.CrossRefPubMed
20.
go back to reference Wong SL, Colley R, Connor Gorber S, Tremblay M. Actical accelerometer sedentary activity thresholds for adults. J Phys Act Health. 2011;8:587–91.CrossRefPubMed Wong SL, Colley R, Connor Gorber S, Tremblay M. Actical accelerometer sedentary activity thresholds for adults. J Phys Act Health. 2011;8:587–91.CrossRefPubMed
21.
go back to reference Tudor-Locke C, Barreira TV, Schuna JM, Mire EF, Katzmarzyk PT. Fully automated waist-worn accelerometer algorithm for detecting children’s sleep-period time separate from 24-h physical activity or sedentary behaviors. Appl. Physiol. Nutr. Metab. 2014;39:53–7.CrossRefPubMed Tudor-Locke C, Barreira TV, Schuna JM, Mire EF, Katzmarzyk PT. Fully automated waist-worn accelerometer algorithm for detecting children’s sleep-period time separate from 24-h physical activity or sedentary behaviors. Appl. Physiol. Nutr. Metab. 2014;39:53–7.CrossRefPubMed
22.
go back to reference Tandon PS, Saelens BE, Zhou C, Kerr J, Christakis DA. Indoor versus outdoor time in preschoolers at child care. Am J Prev Med. 2013;44:85–8.CrossRefPubMed Tandon PS, Saelens BE, Zhou C, Kerr J, Christakis DA. Indoor versus outdoor time in preschoolers at child care. Am J Prev Med. 2013;44:85–8.CrossRefPubMed
23.
go back to reference David J. Harding. Measuring Children’s Time Use: A Review of Methodologies and Findings. Bendheim-Thoman Center for Research on Child Wellbeing, Princeton University; 1997 Oct. Report No.: Working Paper # 97–1. David J. Harding. Measuring Children’s Time Use: A Review of Methodologies and Findings. Bendheim-Thoman Center for Research on Child Wellbeing, Princeton University; 1997 Oct. Report No.: Working Paper # 97–1.
24.
go back to reference Juster FT, Stafford FP. The allocation of time: empirical findings, behavioral models, and problems ofMeasurement. J Econ Lit. 1991;29:471–522. Juster FT, Stafford FP. The allocation of time: empirical findings, behavioral models, and problems ofMeasurement. J Econ Lit. 1991;29:471–522.
26.
go back to reference Carlson JA, Schipperijn J, Kerr J, Saelens BE, Natarajan L, Frank LD, et al. Locations of physical activity as assessed by GPS in young adolescents. Pediatrics. 2015;137:e20152430.CrossRef Carlson JA, Schipperijn J, Kerr J, Saelens BE, Natarajan L, Frank LD, et al. Locations of physical activity as assessed by GPS in young adolescents. Pediatrics. 2015;137:e20152430.CrossRef
27.
go back to reference Bürgi R, de Bruin ED. Differences in spatial physical activity patterns between weekdays and weekends in primary school children: a cross-sectional study using Accelerometry and global positioning system. Sports. 2016;4:36.CrossRef Bürgi R, de Bruin ED. Differences in spatial physical activity patterns between weekdays and weekends in primary school children: a cross-sectional study using Accelerometry and global positioning system. Sports. 2016;4:36.CrossRef
28.
go back to reference Maddison R, Jiang Y, Vander Hoorn S, Exeter D, Mhurchu CN, Dorey E. Describing patterns of physical activity in adolescents using global positioning systems and accelerometry. Pediatr Exerc Sci. 2010;22:392–407.CrossRefPubMed Maddison R, Jiang Y, Vander Hoorn S, Exeter D, Mhurchu CN, Dorey E. Describing patterns of physical activity in adolescents using global positioning systems and accelerometry. Pediatr Exerc Sci. 2010;22:392–407.CrossRefPubMed
29.
go back to reference Rainham DG, Bates CJ, Blanchard CM, Dummer TJ, Kirk SF, Shearer CL. Spatial classification of youth physical activity patterns. Am J Prev Med. 2012;42:e87–96.CrossRefPubMed Rainham DG, Bates CJ, Blanchard CM, Dummer TJ, Kirk SF, Shearer CL. Spatial classification of youth physical activity patterns. Am J Prev Med. 2012;42:e87–96.CrossRefPubMed
Metadata
Title
Development of a measurement approach to assess time children participate in organized sport, active travel, outdoor active play, and curriculum-based physical activity
Authors
Michael M. Borghese
Ian Janssen
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2018
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-018-5268-1

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