Accuracy of Accelerometers for Measuring Physical Activity and Levels of Sedentary Behavior in Children: A Systematic Review

Overview

Journal J Prim Care Community Health

Publisher Sage Publications

Specialty Health Services

Date 2019 Sep 12

PMID 31509061

Citations 23

Authors

Brian A Lynch

Tara K Kaufman

Tamim I Rajjo

K Mohammed

Seema Kumar

M Hassan Murad

Natalie E Gentile

Gabriel A Koepp

Shelly K McCrady-Spitzer

James A Levine

Affiliations

Soon will be listed here.

Abstract

This systematic review evaluated the accuracy of triaxial and omnidirectional accelerometers for measuring physical activity and sedentary behavior in children. Systematic review of the literature. We comprehensively searched several databases for studies published from January 1996 through June 2018 that reported diagnostic accuracy measures in children and adolescents (age 3-18 years) and compared accelerometers with energy expenditure using indirect calorimetry. We included 11 studies that enrolled 570 participants. All studies used indirect calorimetry as the reference standard. Across the studies, median sensitivity ranged from 46% to 96% and median specificity ranged from 71% to 96%. Median area under the curve ranged from 69% to 98%. Accuracy measures were greatest when detecting sedentary behavior and lowest when detecting light physical activity. Accuracy was higher when the accelerometer was placed on the hip compared with the wrist. The current evidence suggests that triaxial and omnidirectional accelerometers are accurate in measuring sedentary behavior and physical activity levels in children.

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References

Crouter S, Flynn J, Bassett Jr D . Estimating physical activity in youth using a wrist accelerometer. Med Sci Sports Exerc. 2014; 47(5):944-51. PMC: 4362848. DOI: 10.1249/MSS.0000000000000502. View

Lyden K, Keadle S, Staudenmayer J, Freedson P, Alhassan S . Energy cost of common activities in children and adolescents. J Phys Act Health. 2012; 10(1):62-9. PMC: 4007486. DOI: 10.1123/jpah.10.1.62. View

Roscoe C, James R, Duncan M . Calibration of GENEActiv accelerometer wrist cut-points for the assessment of physical activity intensity of preschool aged children. Eur J Pediatr. 2017; 176(8):1093-1098. DOI: 10.1007/s00431-017-2948-2. View

van Ekris E, Altenburg T, Singh A, Proper K, Heymans M, Chinapaw M . An evidence-update on the prospective relationship between childhood sedentary behaviour and biomedical health indicators: a systematic review and meta-analysis. Obes Rev. 2016; 17(9):833-49. DOI: 10.1111/obr.12426. View

Moher D, Liberati A, Tetzlaff J, Altman D . Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009; 6(7):e1000097. PMC: 2707599. DOI: 10.1371/journal.pmed.1000097. View

Hager E, Treuth M, Gormely C, Epps L, Snitker S, Black M . Ankle Accelerometry for Assessing Physical Activity Among Adolescent Girls: Threshold Determination, Validity, Reliability, and Feasibility. Res Q Exerc Sport. 2015; 86(4):397-405. PMC: 4775231. DOI: 10.1080/02701367.2015.1063574. View

Rosenberger M, Haskell W, Albinali F, Mota S, Nawyn J, Intille S . Estimating activity and sedentary behavior from an accelerometer on the hip or wrist. Med Sci Sports Exerc. 2012; 45(5):964-75. PMC: 3631449. DOI: 10.1249/MSS.0b013e31827f0d9c. View

Hills A, Mokhtar N, Byrne N . Assessment of physical activity and energy expenditure: an overview of objective measures. Front Nutr. 2015; 1:5. PMC: 4428382. DOI: 10.3389/fnut.2014.00005. View

Lubans D, Hesketh K, Cliff D, Barnett L, Salmon J, Dollman J . A systematic review of the validity and reliability of sedentary behaviour measures used with children and adolescents. Obes Rev. 2011; 12(10):781-99. DOI: 10.1111/j.1467-789X.2011.00896.x. View

10.

Duncan M, Wilson S, Tallis J, Eyre E . Validation of the Phillips et al. GENEActiv accelerometer wrist cut-points in children aged 5-8 years old. Eur J Pediatr. 2016; 175(12):2019-2021. DOI: 10.1007/s00431-016-2795-6. View

11.

Tremblay M, Aubert S, Barnes J, Saunders T, Carson V, Latimer-Cheung A . Sedentary Behavior Research Network (SBRN) - Terminology Consensus Project process and outcome. Int J Behav Nutr Phys Act. 2017; 14(1):75. PMC: 5466781. DOI: 10.1186/s12966-017-0525-8. View

12.

Whiting P, Rutjes A, Westwood M, Mallett S, Deeks J, Reitsma J . QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011; 155(8):529-36. DOI: 10.7326/0003-4819-155-8-201110180-00009. View

13.

Trost S, McIver K, Pate R . Conducting accelerometer-based activity assessments in field-based research. Med Sci Sports Exerc. 2005; 37(11 Suppl):S531-43. DOI: 10.1249/01.mss.0000185657.86065.98. View

14.

Chu E, McManus A, Yu C . Calibration of the RT3 accelerometer for ambulation and nonambulation in children. Med Sci Sports Exerc. 2007; 39(11):2085-91. DOI: 10.1249/mss.0b013e318148436c. View

15.

Fairclough S, Noonan R, Rowlands A, van Hees V, Knowles Z, Boddy L . Wear Compliance and Activity in Children Wearing Wrist- and Hip-Mounted Accelerometers. Med Sci Sports Exerc. 2015; 48(2):245-53. DOI: 10.1249/MSS.0000000000000771. View

16.

Santos-Lozano A, Santin-Medeiros F, Cardon G, Torres-Luque G, Bailon R, Bergmeir C . Actigraph GT3X: validation and determination of physical activity intensity cut points. Int J Sports Med. 2013; 34(11):975-82. DOI: 10.1055/s-0033-1337945. View

17.

Heil D, Brage S, Rothney M . Modeling physical activity outcomes from wearable monitors. Med Sci Sports Exerc. 2011; 44(1 Suppl 1):S50-60. DOI: 10.1249/MSS.0b013e3182399dcc. View

18.

Tudor-Locke C, Barreira T, Schuna Jr J . Comparison of step outputs for waist and wrist accelerometer attachment sites. Med Sci Sports Exerc. 2014; 47(4):839-42. DOI: 10.1249/MSS.0000000000000476. View

19.

Hurter L, Fairclough S, Knowles Z, Porcellato L, Cooper-Ryan A, Boddy L . Establishing Raw Acceleration Thresholds to Classify Sedentary and Stationary Behaviour in Children. Children (Basel). 2018; 5(12). PMC: 6306859. DOI: 10.3390/children5120172. View

20.

Kim Y, Beets M, Welk G . Everything you wanted to know about selecting the "right" Actigraph accelerometer cut-points for youth, but…: a systematic review. J Sci Med Sport. 2012; 15(4):311-21. DOI: 10.1016/j.jsams.2011.12.001. View