Accelerometry-Based Physical Activity Assessment for Children and Adolescents
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Accurate assessment of physical activity (PA) is important to study the associations between PA and health outcomes, to evaluate the effectiveness of interventions and to derive public health recommendations. Despite limitations, accelerometry-based methods generate the best available measures for epidemiological research involving a large number of children and adults. In this chapter, we review the most important methodological issues pertaining to the use of accelerometers to assess the overall volume of PA. We stress the importance of recording and keeping the raw data whenever possible. We review the validation studies using accelerometry to determine energy expenditure and calibration studies that attempt to derive thresholds (“cut-offs”) for differentiating between activity intensity categories. Conceptual and measurement issues due to the use of different thresholds are reviewed, as well as the temporal resolution issues such as sampling rate and epoch length. Different wear time detection algorithms and inclusion criteria are reviewed as well as options in data reduction (deriving meaningful variables from accelerometer data). We present an R package automatising most of the steps in accelerometer data analysis. The chapter concludes with some insights into the future of accelerometry given the wearable revolution and logistical considerations in using accelerometers in large field studies.
KeywordsIntensity Categories Wear Time Moderate-to-vigorous Physical Activity (MVPA) IDEFICS Study Ojiambo
The development of instruments, the baseline data collection, and the first follow-up work as part of the IDEFICS study (www.idefics.eu) were financially supported by the European Commission within the Sixth RTD Framework Programme Contract No. 016181 (FOOD). The most recent follow-up including the development of new instruments and the adaptation of previously used instruments was conducted in the framework of the I.Family study (www.ifamilystudy.eu) which was funded by the European Commission within the Seventh RTD Framework Programme Contract No. 266044 (KBBE 2010–14).
We thank all families for participating in the extensive examinations of the IDEFICS and I.Family studies. We are also grateful for the support from school boards, headmasters, and communities.
- Ahrens W, Siani A, Adan R, De Henauw S, Eiben G, Gwozdz W, et al. I. Family consortium. Cohort profile: the transition from childhood to adolescence in European children—how I.Family extends the IDEFICS cohort. Int J Epidemiol. 2017;46(5):1394–5j.Google Scholar
- Bammann K, Sioen I, Huybrechts I, Casajús J, Vicente-Rodríguez G, Cuthill R, et al. IDEFICS consortium. The IDEFICS validation study on field methods for assessing physical activity and body composition in children: design and data collection. Int J Obes (Lond). 2011;35(Suppl 1):S79–87.CrossRefGoogle Scholar
- Bammann K, Peplies J, Sjöström M, Lissner L, De Henauw S, Galli C, et al. IDEFICS consortium. Assessment of diet, physical activity and biological, social and environmental factors in a multi-centre European project on diet- and lifestyle-related disorders in children (IDEFICS). J Pub Health. 2006;14(5):279–89.CrossRefGoogle Scholar
- Buck C, Kneib T, Tkaczick T, Konstabel K, Pigeot I. Assessing opportunities for physical activity in the built environment of children: interrelation between kernel density and neighborhood scale. Int J Health Geogr. 2015a;22:14–35.Google Scholar
- Bull FC, Expert working groups. Physical activity guidelines in the U.K.: review and recommendations. School of Sport, Exercise and Health Sciences, Loughborough University. 2010. https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/213743/dh_128255.pdf. Accessed 8 Feb 2018.
- Caspersen CJ, Powell KE, Chistenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep. 1985;100:126–31.Google Scholar
- Choi L, Liu Z, Matthews CE, Buchowski MS. Physical activity: process physical activity accelerometer data. R package version 0.1–1. 2011b. https://CRAN.R-project.org/package=PhysicalActivity. Accessed 3 May 2018.
- de Vet E, Verkooijen KT. Self-control and physical activity. Disentangling the pathways to health. In: de Ridder D, Adriaanse M, Fujita K, editors. The Routledge international handbook of self-control in health and well-being. London: Routledge; 2018. p. 276–87.Google Scholar
- Dencker M, Andersen LB. Health-related aspects of objectively measured daily PA in children. J Sports Med. 2008;28:133–44.Google Scholar
- Gabriel KP, McClain JJ, Schmid KK, Storti KL, High RR, Underwood DA, et al. Issues in accelerometer methodology: the role of epoch length on estimates of physical activity and relationships with health outcomes in overweight, post-menopausal women. Int J Beh Nutr Phy Activ. 2010;7:53.CrossRefGoogle Scholar
- Gorber SC, Tremblay MS. Self-report and direct measures of health: bias and implications. In: Shephard RJ, Tudor-Locke C, editors. The objective monitoring of physical activity: contributions of accelerometry to epidemiology, exercise science and rehabilitation. New York: Springer; 2016. p. 369–76.CrossRefGoogle Scholar
- Ihaka R, Gentleman R. R: A language for data analysis and graphics. J Comput Graph Stat. 1996;5:299–314.Google Scholar
- Konstabel K, Mäestu J, Rääsk T, Lätt E, Jürimäe J. Decline in light-intensity activity is a major component of the longitudinal decline in physical activity in adolescent boys. Acta Paediatr. 2017;106(Suppl 470):24.Google Scholar
- Konstabel K. accelerate: an R package for accelerometry data analysis version 1.0.1. 2018. https://osf.io/s42a3/.
- Manohar CU, McCrady SK, Fujiki Y, Pavlidis IT, Levine JA. Evaluation of the accuracy of a triaxial accelerometer embedded into a cell phone platform for measuring physical activity. J Obes Weight Loss Ther. 2011;1(106):3309.Google Scholar
- Ojiambo RM, Konstabel K, Veidebaum T, Reilly JJ, Verbestel V, Casajús JA, et al. IDEFICS consortium. Validity of hip-mounted uniaxial accelerometry with heart-rate monitoring versus triaxial accelerometry in the assessment of free-living energy expenditure in young children: the IDEFICS validation study. J Appl Physiol. 2012;113(10):1530–6.CrossRefGoogle Scholar
- Pitsi T, Zilmer M, Vaask S, Ehala-Aleksejev K, Kuu S, Löhmus K, et al. Eesti toitumis- ja liikumissoovitused 2015 (Estonian guidelines on nutrition and physical activity). Tallinn: Tervise Arengu Instituut. 2017. https://intra.tai.ee//images/prints/documents/149019033869_eesti%20toitumis-%20ja%20liikumissoovitused.pdf. Assessed 2 Feb 2018.
- R Core Team. R. A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. 2017. https://www.R-project.org/. Accessed 3 May 2018.
- Treuth MS, Schmitz K, Catellier DJ, McMurray RG, Murray DM, Almeida MJ, et al. Defining accelerometer thresholds for activity intensities in adolescent girls. Med Sci Sports Exerc. 2004;36(7):1259–66.Google Scholar
- van Cauwenberghe EV, Labarque V, Trost SG, De Bourdeaudhuij I, Cardon G. Calibration and comparison of accelerometer cut points in preschool children. Int J Pediatr Obes. 2010;6(2–2):e582–9.Google Scholar
- van Hees VT. GGIR: raw accelerometer data analysis. R package version 1.5–16. 2018. https://CRAN.R-project.org/package=GGIR. Accessed 2 May 2018.
- Wareham N, Rennie K. The assessment of physical activity in individuals and populations: why try to be more precise about how physical activity is assessed? Int J Obes (Lond). 1998;22:S30–8.Google Scholar
- Whelton PK, He J, Appel LJ, Cutler JA, Havas S, Kotchen TA, et al. National high blood pressure education program coordinating committee. Primary prevention of hypertension: clinical and public health advisory from the national high blood pressure education program. JAMA. 2002;288(15):1882–8.CrossRefGoogle Scholar
- World Health Organization. Global recommendations on physical activity for health. 2010. http://www.who.int/dietphysicalactivity/publications/9789241599979/en/. Accessed 2 May 2018.
- Zhou W, Owen N. Sedentary behavior and health concepts, assessments, and interventions. Champaign, IL: Human Kinetics; 2017.Google Scholar