期刊论文详细信息
International Journal of Behavioral Nutrition and Physical Activity
Using accelerometers and global positioning system devices to assess gender and age differences in children’s school, transport, leisure and home based physical activity
Jens Troelsen1  Annette K Ersbøll2  Jacqueline Kerr4  Hayley Christian3  Jasper Schipperijn1  Charlotte D Klinker1 
[1]Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark
[2]National Institute of Public Health, University of Southern Denmark, Øster Farimagsgade 5A, 1353 Copenhagen K, Denmark
[3]Centre for the Built Environment and Health, School of Population Health, and Telethon Institute for Child Health Research, The University of Western Australia, 35 Stirling Highway, Crawley, Western Australia 6009, Australia
[4]Department of Family and Preventive Medicine, University of California San Diego, La Jolla, California, USA
关键词: Physical activity patterns;    Context-specific;    Spatial behaviour;    Global positioning system (GPS);    Accelerometer;    Physical activity;    Adolescent;    Children;   
Others  :  805615
DOI  :  10.1186/1479-5868-11-8
 received in 2013-09-10, accepted in 2014-01-21,  发布年份 2014
PDF
【 摘 要 】

Background

Knowledge on domain-specific physical activity (PA) has the potential to advance public health interventions and inform new policies promoting children’s PA. The purpose of this study is to identify and assess domains (leisure, school, transport, home) and subdomains (e.g., recess, playgrounds, and urban green space) for week day moderate to vigorous PA (MVPA) using objective measures and investigate gender and age differences.

Methods

Participants included 367 Danish children and adolescents (11–16 years, 52% girls) with combined accelerometer and Global Positioning System (GPS) data (mean 2.5 days, 12.7 hrs/day). The Personal Activity and Location Measurement System and a purpose-built database assessed data in 15-second epochs to determine PA and assign epochs to 4 domains and 11 subdomains. Frequencies and proportions of time spent in MVPA were determined and differences assessed using multi-level modeling.

Results

More than 90% of MVPA was objectively assigned to domains/subdomains. Boys accumulated more MVPA overall, in leisure, school and transport (all p < 0.05). Children compared with adolescents accumulated more MVPA, primarily through more school MVPA (p < 0.05). Boys spent a large proportion of time accumulating MVPA in playgrounds, active transport, Physical Education, sports facilities, urban green space and school grounds. Girls spent a significant proportion of time accumulating MVPA in active transport and playgrounds. No gender or age differences were found in the home domain.

Conclusions

Large variations were found in PA frequency and intensity across domains/subdomains. Significant gender differences were found, with girls being less active in almost all domains and subdomains. Objectively measured patterns of PA across domains/subdomains can be used to better tailor PA interventions and inform future policies for promoting child PA.

【 授权许可】

   
2014 Klinker et al.; licensee BioMed Central Ltd.

【 预 览 】
附件列表
Files Size Format View
20140708081628964.pdf 188KB PDF download
【 参考文献 】
  • [1]Andersen LB, Riddoch C, Kriemler S, Hills AP: Physical activity and cardiovascular risk factors in children. Br J Sports Med 2011, 45:871-876.
  • [2]Hallal PC, Andersen LB, Bull FC, Guthold R, Haskell W, Ekelund U: Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet 2012, 380:247-257.
  • [3]Kristensen PL, Moller NC, Korsholm L, Wedderkopp N, Andersen LB, Froberg K: Tracking of objectively measured physical activity from childhood to adolescence: the European youth heart study. Scand J Med Sci Sports 2008, 18:171-178.
  • [4]Telama R: Tracking of physical activity from childhood to adulthood: a review. Obes Facts 2009, 2:187-195.
  • [5]Pratt M, Macera CA, Sallis JF, O’Donnell M, Frank LD: Economic interventions to promote physical activity: application of the SLOTH model. Am J Prev Med 2004, 27:136-145.
  • [6]Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJ, Martin BW: Correlates of physical activity: why are some people physically active and others not? Lancet 2012, 380:258-271.
  • [7]Jones AP, Coombes EG, Griffin SJ, van Sluijs EM: Environmental supportiveness for physical activity in English schoolchildren: a study using Global Positioning Systems. Int J Behav Nutr Phys Act 2009, 6:42. BioMed Central Full Text
  • [8]Krenn PJ, Titze S, Oja P, Jones A, Ogilvie D: Use of global positioning systems to study physical activity and the environment: a systematic review. Am J Prev Med 2011, 41:508-515.
  • [9]Lachowycz K, Jones AP, Page AS, Wheeler BW, Cooper AR: What can global positioning systems tell us about the contribution of different types of urban greenspace to children’s physical activity? Health Place 2012, 18:586-594.
  • [10]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-e96.
  • [11]Wheeler BW, Cooper AR, Page AS, Jago R: Greenspace and children’s physical activity: a GPS/GIS analysis of the PEACH project. Prev Med 2010, 51:148-152.
  • [12]Maddison R, Jiang Y, Vander HS, 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.
  • [13]Chaix B, Kestens Y, Perchoux C, Karusisi N, Merlo J, Labadi K: An interactive mapping tool to assess individual mobility patterns in neighborhood studies. Am J Prev Med 2012, 43:440-450.
  • [14]Oreskovic NM, Blossom J, Field AE, Chiang SR, Winickoff JP, Kleinman RE: Combining global positioning system and accelerometer data to determine the locations of physical activity in children. Geospat Health 2012, 6:263-272.
  • [15]Guinhouya BC, Lemdani M, Vilhelm C, Hubert H, Apete GK, Durocher A: How school time physical activity is the “big one” for daily activity among schoolchildren: a semi-experimental approach. J Phys Act Health 2009, 6:510-519.
  • [16]Quigg R, Gray A, Reeder AI, Holt A, Waters DL: Using accelerometers and GPS units to identify the proportion of daily physical activity located in parks with playgrounds in New Zealand children. Prev Med 2010, 50:235-240.
  • [17]Reed JA, Hooker SP: Where are youth physically active? A descriptive examination of 45 parks in a southeastern community. Child Obes 2012, 8:124-131.
  • [18]Niclasen B, Petzold M, Schnohr CW: The association between high recreational physical activity and physical activity as a part of daily living in adolescents and availability of local indoor sports facilities and sports clubs. Scand J Public Health 2012, 40:614-620.
  • [19]Southward EF, Page AS, Wheeler BW, Cooper AR: Contribution of the school journey to daily physical activity in children aged 11–12 years. Am J Prev Med 2012, 43:201-204.
  • [20]Copenhagen Municipality: Haraldsgadekvarterets områdeløft. Kvarterplan 2007–2012. Copenhagen: Copenhagen Municipality; 2006.
  • [21]Copenhagen Municipality: Fælles boligsocial helhedsplan for Haraldsgadekvarteret. Copenhagen: Copenhagen Municipality; 2007.
  • [22]Danmarks Statistik: Indvandrere i Danmark 2012. 2013.
  • [23]Santelli JS, Smith RA, Rosenfeld WD, DuRant RH, Dubler N, Morreale M, et al.: Guidelines for adolescent health research. A position paper of the Society for Adolescent Medicine. J Adolesc Health 2003, 33:396-409.
  • [24]Kerr J, Duncan S, Schipperijn J: Using global positioning systems in health research: a practical approach to data collection and processing. Am J Prev Med 2011, 41:532-540.
  • [25]Duncan S, Stewart TI, Oliver M, Mavoa S, MacRae D, Badland HM, et al.: Portable global positioning system receivers: static validity and environmental conditions. Am J Prev Med 2013, 44:e19-e29.
  • [26]Trost SG, Pate RR, Freedson PS, Sallis JF, Taylor WC: Using objective physical activity measures with youth: how many days of monitoring are needed? Med Sci Sports Exerc 2000, 32:426-431.
  • [27]Demchak B, Kerr J, Raab F, Patrick K, Krüger I: PALMS: a modern coevolution of community and computing - using policy driven development. Proc Hawaii Int Conf Syst Sci 2011.
  • [28]The Physical Activity and Location Measurement (PALMS). [http://ucsd-palms-project.wikispaces.com/ webcite] 2013
  • [29]Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG: Calibration of two objective measures of physical activity for children. J Sports Sci 2008, 26:1557-1565.
  • [30]Trost SG, Loprinzi PD, Moore R, Pfeiffer KA: Comparison of accelerometer cut points for predicting activity intensity in youth. Med Sci Sports Exerc 2011, 43:1360-1368.
  • [31]Pedersen CB: The Danish Civil Registration System. Scand J Public Health 2011, 39:22-25.
  • [32]Petersson F, Baadsgaard M, Thygesen LC: Danish registers on personal labour market affiliation. Scand J Public Health 2011, 39:95-98.
  • [33]Cole TJ, Bellizzi MC, Flegal KM, Dietz WH: Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000, 320:1240-1243.
  • [34]Griew P, Page A, Thomas S, Hillsdon M, Cooper AR: The school effect on children’s school time physical activity: the PEACH Project. Prev Med 2010, 51:282-286.
  • [35]Dessing D, Pierik FH, Sterkenburg RP, van DP, Maas J, De Vries SI: Schoolyard physical activity of 6–11 year old children assessed by GPS and accelerometry. Int J Behav Nutr Phys Act 2013, 10:97. BioMed Central Full Text
  • [36]van Sluijs EM, Fearne VA, Mattocks C, Riddoch C, Griffin SJ, Ness A: The contribution of active travel to children’s physical activity levels: cross-sectional results from the ALSPAC study. Prev Med 2009, 48:519-524.
  • [37]Ridgers ND, Salmon J, Parrish AM, Stanley RM, Okely AD: Physical activity during school recess: a systematic review. Am J Prev Med 2012, 43:320-328.
  • [38]Parrish AM, Okely AD, Stanley RM, Ridgers ND: The effect of school recess interventions on physical activity: a systematic review. Sports Med 2013, 43:287-299.
  • [39]Arundell L, Ridgers ND, Veitch J, Salmon J, Hinkley T, Timperio A: 5-year changes in afterschool physical activity and sedentary behavior. Am J Prev Med 2013, 44:605-611.
  文献评价指标  
  下载次数:6次 浏览次数:15次