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http://dx.doi.org/10.4162/nrp.2022.16.5.565

Energy cost of walking in older adults: accuracy of the ActiGraph accelerometer predictive equations  

Ndahimana, Didace (Department of Food and Nutrition, Gangneung-Wonju National University)
Kim, Ye-Jin (Department of Food and Nutrition, Gangneung-Wonju National University)
Wang, Cui-Sang (Department of Food and Nutrition, Gangneung-Wonju National University)
Kim, Eun-Kyung (Department of Food and Nutrition, Gangneung-Wonju National University)
Publication Information
Nutrition Research and Practice / v.16, no.5, 2022 , pp. 565-576 More about this Journal
Abstract
BACKGROUND/OBJECTIVES: Various accelerometer equations are used to predict energy expenditure (EE). On the other hand, the development of these equations and their validation studies have been conducted primarily without including older adults. This study assessed the accuracy of 8 ActiGraph accelerometer equations to predict the energy cost of walking in older adults. SUBJECTS/METHODS: Thirty-one participants with a mean age of 74.3 ± 3.3 yrs were enrolled in this study (20 men and 11 women). The participants completed 8 walking activities, including 5 treadmill and 3 self-paced walking activities. The EE was measured using a portable indirect calorimeter, with each participant simultaneously wearing the ActiGraph accelerometer. Eight ActiGraph equations were assessed for accuracy by comparing the predicted EE with indirect calorimetry results. RESULTS: All equations resulted in an overall underestimation of the EE across the activities (bias -1 to -1.8 kcal·min-1 and -0.7 to -1.8 metabolic equivalents [METs]), as well as during treadmill-based (bias -1.5 to -2.9 kcal·min-1 and -0.9 to -2.1 METs) and self-paced (bias -1.2 to -1.7 kcal·min-1 and -0.2 to -1.3 METs) walking. In addition, there were higher rates of activity intensity misclassifications, particularly among vigorous physical activities. CONCLUSIONS: The ActiGraph equations underestimated the EE for walking activities in older adults. In addition, these equations inaccurately classified the activities based on their intensities. The present study suggests a need to develop ActiGraph equations specific to older adults.
Keywords
Physical activity; elderly; energy expenditure;
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1 Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, O'Brien WL, Bassett DR, Schmitz KH, Emplaincourt PO, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc 2000;32:S498-516.   DOI
2 Institute of Medicine of the National Academies (US). Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids. Washington, D.C.: National Academies Press; 2002.
3 Robusto KM, Trost SG. Comparison of three generations of ActiGraphTM activity monitors in children and adolescents. J Sports Sci 2012;30:1429-35.   DOI
4 Swartz AM, Strath SJ, Bassett DR Jr, O'Brien WL, King GA, Ainsworth BE. Estimation of energy expenditure using CSA accelerometers at hip and wrist sites. Med Sci Sports Exerc 2000;32:S450-6.   DOI
5 Yngve A, Nilsson A, Sjostrom M, Ekelund U. Effect of monitor placement and of activity setting on the MTI accelerometer output. Med Sci Sports Exerc 2003;35:320-6.   DOI
6 Bird SR, Hawley JA. Update on the effects of physical activity on insulin sensitivity in humans. BMJ Open Sport Exerc Med 2017;2:e000143.
7 Mansikkamaki K, Raitanen J, Nygard CH, Tomas E, Rutanen R, Luoto R. Long-term effect of physical activity on health-related quality of life among menopausal women: a 4-year follow-up study to a randomised controlled trial. BMJ Open 2015;5:e008232.
8 Ortega JD, Farley CT. Individual limb work does not explain the greater metabolic cost of walking in elderly adults. J Appl Physiol (1985) 2007;102:2266-73.   DOI
9 Lyden K, Kozey SL, Staudenmeyer JW, Freedson PS. A comprehensive evaluation of commonly used accelerometer energy expenditure and MET prediction equations. Eur J Appl Physiol 2011;111:187-201.   DOI
10 Santos-Lozano A, Santin-Medeiros F, Cardon G, Torres-Luque G, Bailon R, Bergmeir C, Ruiz JR, Lucia A, Garatachea N. ActiGraph GT3X: validation and determination of physical activity intensity cut points. Int J Sports Med 2013;34:975-82.   DOI
11 Hall KS, Howe CA, Rana SR, Martin CL, Morey MC. METs and accelerometry of walking in older adults: standard versus measured energy cost. Med Sci Sports Exerc 2013;45:574-82.   DOI
12 Jones LM, Waters DL, Legge M. Walking speed at self-selected exercise pace is lower but energy cost higher in older versus younger women. J Phys Act Health 2009;6:327-32.   DOI
13 Pinnington HC, Wong P, Tay J, Green D, Dawson B. The level of accuracy and agreement in measures of FEO2, FECO2 and VE between the Cosmed K4b2 portable, respiratory gas analysis system and a metabolic cart. J Sci Med Sport 2001;4:324-35.   DOI
14 McLaughlin JE, King GA, Howley ET, Bassett DR Jr, Ainsworth BE. Validation of the COSMED K4 b2 portable metabolic system. Int J Sports Med 2001;22:280-4.   DOI
15 United Nations. World Population Ageing 2017 - Highlights (ST/ESA/SER.A/397). New York (NY): UN; 2017.
16 Mcminn D, Acharya R, Rowe DA, Gray SR, Allan JL. Measuring activity energy expenditure: accuracy of the GT3X+ and Actiheart monitors. Int J Exerc Sci 2013;6:217-29.
17 Aadland E, Ylvisaker E. Reliability of the ActiGraph GT3X+ accelerometer in adults under free-living conditions. PLoS One 2015;10:e0134606.
18 Sasaki JE, John D, Freedson PS. Validation and comparison of ActiGraph activity monitors. J Sci Med Sport 2011;14:411-6.   DOI
19 Arredondo A, Aviles R. Costs and epidemiological changes of chronic diseases: implications and challenges for health systems. PLoS One 2015;10:e0118611.
20 Mian OS, Thom JM, Ardigo LP, Narici MV, Minetti AE. Metabolic cost, mechanical work, and efficiency during walking in young and older men. Acta Physiol (Oxf) 2006;186:127-39.   DOI
21 Iolascon G, Di Pietro G, Gimigliano F, Mauro GL, Moretti A, Giamattei MT, Ortolani S, Tarantino U, Brandi ML. Physical exercise and sarcopenia in older people: position paper of the Italian Society of Orthopaedics and Medicine (OrtoMed). Clin Cases Miner Bone Metab 2014;11:215-21.
22 Kennedy BK, Berger SL, Brunet A, Campisi J, Cuervo AM, Epel ES, Franceschi C, Lithgow GJ, Morimoto RI, Pessin JE, et al. Aging: a common driver of chronic diseases and a target for novel interventions. Cell 2014;159:709-13.   DOI
23 Hanson MA, Cooper C, Aihie Sayer A, Eendebak RJ, Clough GF, Beard JR. Developmental aspects of a life course approach to healthy ageing. J Physiol 2016;594:2147-60.   DOI
24 Friedenreich CM, Neilson HK, Farris MS, Courneya KS. Physical activity and cancer outcomes: a precision medicine approach. Clin Cancer Res 2016;22:4766-75.   DOI
25 Pinheiro Volp AC, Esteves de Oliveira FC, Duarte Moreira Alves R, Esteves EA, Bressan J. Energy expenditure: components and evaluation methods. Nutr Hosp 2011;26:430-40.
26 Schneller MB, Pedersen MT, Gupta N, Aadahl M, Holtermann A. Validation of five minimally obstructive methods to estimate physical activity energy expenditure in young adults in semi-standardized settings. Sensors (Basel) 2015;15:6133-51.   DOI
27 ActiGraph, LLC. Kcal estimates from activity counts using the potential energy method. Pensacola (FL): ActiGraph, LLC.; 1998 [cited 2017 October 24]. Available from: http://actigraphcorp.com/researchdatabase/kcal-estimates-from-activity-counts-using-the-potential-energy-method/.
28 Aguilar-Farias N, Peeters GM, Brychta RJ, Chen KY, Brown WJ. Comparing ActiGraph equations for estimating energy expenditure in older adults. J Sports Sci 2019;37:188-95.   DOI
29 Whitcher L, Papadopoulos C. Accelerometer derived activity counts and oxygen consumption between young and older individuals. J Aging Res 2014;2014:184693.
30 Schrack JA, Simonsick EM, Ferrucci L. Comparison of the Cosmed K4b2 portable metabolic system in measuring steady-state walking energy expenditure. PLoS One 2010;5:e9292.
31 Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc 1998;30:777-81.   DOI
32 Brooks AG, Gunn SM, Withers RT, Gore CJ, Plummer JL. Predicting walking METs and energy expenditure from speed or accelerometry. Med Sci Sports Exerc 2005;37:1216-23.   DOI
33 Kwan M, Woo J, Kwok T. The standard oxygen consumption value equivalent to one metabolic equivalent (3.5 ml/min/kg) is not appropriate for elderly people. Int J Food Sci Nutr 2004;55:179-82.   DOI
34 Bherer L, Erickson KI, Liu-Ambrose T. A review of the effects of physical activity and exercise on cognitive and brain functions in older adults. J Aging Res 2013;2013:657508.
35 Crouter SE, Churilla JR, Bassett DR Jr. Estimating energy expenditure using accelerometers. Eur J Appl Physiol 2006;98:601-12.   DOI
36 Byrne NM, Hills AP, Hunter GR, Weinsier RL, Schutz Y. Metabolic equivalent: one size does not fit all. J Appl Physiol (1985) 2005;99:1112-9.   DOI
37 Population Reference Bureau. Noncommunicable diseases among older adults in low- and middleincome countries. Washington, D.C.: Population Reference Bureau; 2012 [cited 2021 December 26]. Available from: https://www.prb.org/resources/noncommunicable-diseases-among-older-adults-in-lowand-middle-income-countries/.
38 Sowa A, Tobiasz-Adamczyk B, Topor-Madry R, Poscia A, la Milia DI. Predictors of healthy ageing: public health policy targets. BMC Health Serv Res 2016;16 Suppl 5:289.
39 Crichton GE, Alkerwi A. Physical activity, sedentary behavior time and lipid levels in the Observation of Cardiovascular Risk Factors in Luxembourg study. Lipids Health Dis 2015;14:87.
40 Qiu S, Cai X, Schumann U, Velders M, Sun Z, Steinacker JM. Impact of walking on glycemic control and other cardiovascular risk factors in type 2 diabetes: a meta-analysis. PLoS One 2014;9:e109767.
41 Steffl M, Bohannon RW, Sontakova L, Tufano JJ, Shiells K, Holmerova I. Relationship between sarcopenia and physical activity in older people: a systematic review and meta-analysis. Clin Interv Aging 2017;12:835-45.   DOI
42 Welk GJ. Physical Activity Assessments for Health-Related Research. Champaign (IL): Human Kinetics; 2002.
43 WHO. Global Recommendations on Physical Activity for Health. Geneva: WHO Press; 2010.
44 Crouter SE, Clowers KG, Bassett DR Jr. A novel method for using accelerometer data to predict energy expenditure. J Appl Physiol (1985) 2006;100:1324-31.   DOI
45 Ndahimana D, Kim EK. Measurement methods for physical activity and energy expenditure: a review. Clin Nutr Res 2017;6:68-80.   DOI