Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
BMC Medical Research Methodology
Published in: BMC Medical Research Methodology 1/2012

Open Access 01-12-2012 | Research article

Comparison of uniaxial and triaxial accelerometry in the assessment of physical activity among adolescents under free-living conditions: the HELENA study

Authors: Jérémy Vanhelst, Laurent Béghin, Alain Duhamel, Patrick Bergman, Michael Sjöström, Frédéric Gottrand

Published in: BMC Medical Research Methodology | Issue 1/2012

Login to get access

Abstract

Background

Different types of devices are available and the choice about which to use depends on various factors: cost, physical characteristics, performance, and the validity and intra- and interinstrument reliability. Given the large number of studies that have used uniaxial or triaxial devices, it is of interest to know whether the different devices give similar information about PA levels and patterns. The aim of this study was to compare physical activity (PA) levels and patterns obtained simultaneously by triaxial accelerometry and uniaxial accelerometry in adolescents in free-living conditions.

Methods

Sixty-two participants, aged 13-16 years, were recruited in this ancillary study, which is a part of the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA). All participants wore a uniaxial accelerometer (ActiGraph GT1M®, Pensacola, FL) and a triaxial accelerometer (RT3®, Stayhealthy, Monrovia, CA) simultaneously for 7 days. The patterns were calculated by converting accelerometer data output as a percentage of time spent at sedentary, light, moderate, and vigorous PA per day. Analysis of output data from the two accelerometers were assessed by two different tests: Equivalence Test and Bland & Altman method.

Results

The concordance correlation coefficient between the data from the triaxial accelerometer and uniaxial accelerometer at each intensity level was superior to 0.95. The ANOVA test showed a significant difference for the first three lower intensities while no significant difference was found for vigorous intensity. The difference between data obtained with the triaxial accelerometer and the uniaxial monitor never exceeded 2.1% and decreased as PA level increased. The Bland & Altman method showed good agreement between data obtained between the both accelerometers (p < 0.05).

Conclusions

Uniaxial and triaxial accelerometers do not differ in their measurement of PA in population studies, and either could be used in such studies.
Appendix
Available only for authorised users
Literature
1.
Fox KR, Stathi A, McKenna J, Davis MG: Physical activity and mental well-being in older people participating in the Better Ageing Project. Eur J Appl Physiol. 2007, 100: 591-602. 10.1007/s00421-007-0392-0.CrossRefPubMed
2.
Patrick K, Norman GJ, Calfas KJ, Sallis JF, Zabinski MF, Rupp J, Cella J: Diet, physical activity, and sedentary behaviors as risk factors for overweight in adolescence. Arch Pediatr Adolesc Med. 2004, 158: 385-90. 10.1001/archpedi.158.4.385.CrossRefPubMed
3.
Toschke JA, von Kries R, Rosenfeld E, Toschke AM: Reliability of physical activity measures from accelerometry among preschoolers in free-living conditions. Clin Nutr. 2007, 26: 416-20. 10.1016/j.clnu.2007.03.009.CrossRefPubMed
4.
Chen KY, Bassett DR: The technology of accelerometry-based activity monitors: current and future. Med Sci Sports Exerc. 2005, 37 (11 Suppl): S490-500.CrossRefPubMed
5.
Moreno LA, González-Gross M, Kersting M, Molnár D, de Henauw S, Beghin L, Sjöström M, Hagströmer M, Manios Y, Gilbert CC, et al: Assessing, understanding and modifying nutritional status, eating habits and physical activity in European adolescents. The HELENA Study. Public Health Nutr. 2008, 11: 288-299.CrossRefPubMed
6.
Cole TJ, Bellizzi MC, Flegal KM, Dietz WH: Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ. 2000, 320: 1240-3. 10.1136/bmj.320.7244.1240.CrossRefPubMedPubMedCentral
7.
Tanner JM: Normal growth and techniques of growth assessment. Clin Endocrinol Metab. 1986, 15: 411-51. 10.1016/S0300-595X(86)80005-6.CrossRefPubMed
8.
Béghin L, Castera M, Manios Y, Gilbert CC, Kersting M, De Henauw S, Kafatos A, Gottrand F, Molnar D, Sjöström M, et al: Quality assurance of ethical issues and regulatory aspects relating to good clinical practices in the HELENA Cross-Sectional Study. Int J Obes. 2008, 32: S12-8.CrossRef
9.
Powell SM, Jones DI, Rowlands AV: Technical variability of the RT3 accelerometer. Med Sci Sports Exerc. 2003, 35: 1773-8. 10.1249/01.MSS.0000089341.68754.BA.CrossRefPubMed
10.
Vanhelst J, Béghin L, Rasoamanana P, Theunynck D, Meskini T, Iliescu C, Duhamel A, Turck D, Gottrand F: RT3 accelerometer thresholds for physical activity levels in children and adolescents. J Sports Sci. 2010, 28: 381-7. 10.1080/02640410903508821.CrossRefPubMed
11.
Krasnoff JB, Kohn MA, Choy FK, Doyle J, Johansen K, Painter PL: Interunit and intraunit reliability of the RT3 triaxial accelerometer. J Phys Act Health. 2008, 5: 527-38.PubMed
12.
Reneman M, Helmus M: Interinstrument reliability of the RT3 accelerometer. Int J Rehabil Res. 2010, 33: 178-9. 10.1097/MRR.0b013e32832c1e73.CrossRefPubMed
13.
Vanhelst J, Theunynck D, Gottrand F, Béghin L: Reliability of the RT3 accelerometer for measurement of physical activity in adolescents. J Sports Sci. 2010, 28: 375-9. 10.1080/02640410903502790.CrossRefPubMed
14.
Vanhelst J, Béghin L, Turck D, Gottrand F: New validated thresholds for various intensities of physical activity in adolescents using the Actigraph accelerometer. Int J Rehabil Res. 2011, 34: 175-77. 10.1097/MRR.0b013e328340129e.CrossRefPubMed
15.
Esliger DW, Tremblay MS: Technical reliability assessment of three accelerometer models in a mechanical setup. Med Sci Sports Exerc. 2006, 38: 2173-81. 10.1249/01.mss.0000239394.55461.08.CrossRefPubMed
16.
Fleiss JL: Design and analysis of clinical experiments. New York. Edited by: York N. 1986, NY: USA
17.
Bland JM, Altman DG: Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986, 1: 307-310.CrossRefPubMed
18.
Eston RG, Rowlands AV, Ingledew DK: Validity of heart rate, pedometry, and accelerometry for predicting the energy cost of children's activities. J Appl Physiol. 1998, 84: 362-71.PubMed
19.
Plasqui G, Joosen AM, Kester AD, Goris AH, Westerterp KR: Measuring free-living energy expenditure and physical activity with triaxial accelerometry. Obes Res. 2005, 13: 1363-9. 10.1038/oby.2005.165.CrossRefPubMed
20.
Westerterp KR: Assessment of physical activity level in relation to obesity: current evidence and research issues. Med Sci Sports Exerc. 1999, 31: S522-5. 10.1097/00005768-199911001-00006.CrossRefPubMed
21.
Howe CA, Staudenmayer JW, Freedson PS: Accelerometer prediction of energy expenditure: vector magnitude versus vertical axis. Med Sci Sports Exerc. 2009, 41: 2199-206. 10.1249/MSS.0b013e3181aa3a0e.CrossRefPubMed
22.
Macfarlane DJ, Lee CC, Ho EY, Chan KL, Chan D: Convergent validity of six methods to assess physical activity in daily life. J Appl Physiol. 2006, 101: 1328-34. 10.1152/japplphysiol.00336.2006.CrossRefPubMed
23.
Paul DR, Kramer M, Moshfegh AJ, Baer DJ, Rumpler WV: Comparison of two different physical activity monitors. BMC Med Res Methodol. 2007, 7: 26-10.1186/1471-2288-7-26.CrossRefPubMedPubMedCentral
24.
Rothney MP, Schaefer EV, Neumann MM, Choi L, Chen KY: Validity of physical activity intensity predictions by ActiGraph, Actical, and RT3 accelerometers. Obesity. 2008, 16: 1946-52. 10.1038/oby.2008.279.CrossRefPubMedPubMedCentral
25.
Leenders NY, Sherman WM, Nagaraja HN: Energy expenditure estimated by accelerometry and doubly labeled water: do they agree?. Med Sci Sports Exerc. 2006, 38: 2165-72. 10.1249/01.mss.0000235883.94357.95.CrossRefPubMed
26.
Baquet G, Stratton G, Van Praagh E, Berthoin S: Improving physical activity assessment in prepubertal children with high-frequency accelerometry monitoring: a methodological issue. Prev Med. 2007, 44: 143-7. 10.1016/j.ypmed.2006.10.004.CrossRefPubMed
27.
Treuth MS, Schmitz K, Catellier DJ, McMurray RG, Murray DM, Almeida MJ, Going S, Norman JE, Pate R: Defining accelerometer thresholds for activity intensities in adolescent girls. Med Sci Sports Exerc. 2004, 36: 1259-66.CrossRefPubMedPubMedCentral
28.
Puyau MR, Adolph AL, Vohra FA, Butte NF: Validation and calibration of physical activity monitors in children. Obes Res. 2002, 10: 150-7. 10.1038/oby.2002.24.CrossRefPubMed
29.
Ekelund U, Sardinha LB, Anderssen SA, Harro M, Franks PW, Brage S, Cooper AR, Andersen LB, Riddoch C, Froberg K: Associations between objectively assessed physical activity and indicators of body fatness in 9 to 10-year-old European children: a population-based study from 4 distinct regions in Europe (the European Youth Heart Study). Am J Clin Nutr. 2004, 80: 584-590.PubMed
Metadata
Title
Comparison of uniaxial and triaxial accelerometry in the assessment of physical activity among adolescents under free-living conditions: the HELENA study
Authors
Jérémy Vanhelst
Laurent Béghin
Alain Duhamel
Patrick Bergman
Michael Sjöström
Frédéric Gottrand
Publication date
01-12-2012
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2012
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/1471-2288-12-26

Other articles of this Issue 1/2012

BMC Medical Research Methodology 1/2012 Go to the issue

Research article

Determination of inflammatory biomarkers in patients with COPD: a comparison of different assays

Correspondence

The quality of the evidence base for clinical pathway effectiveness: Room for improvement in the design of evaluation trials

Research article

Classification of positive blood cultures: computer algorithms versus physicians' assessment - development of tools for surveillance of bloodstream infection prognosis using population-based laboratory databases

Research article

Including mixed methods research in systematic reviews: Examples from qualitative syntheses in TB and malaria control

Research article

Quality of life of Chinese urban community residents: a psychometric study of the mainland Chinese version of the WHOQOL-BREF

Research article

Do health care institutions value research? A mixed methods study of barriers and facilitators to methodological rigor in pediatric randomized trials