Validation and Comparison of Two Methods to Assess Human Energy Expenditure during Free-Living Activities

Background The measurement of activity energy expenditure (AEE) via accelerometry is the most commonly used objective method for assessing human daily physical activity and has gained increasing importance in the medical, sports and psychological science research in recent years. Objective The purpose of this study was to determine which of the following procedures is more accurate to determine the energy cost during the most common everyday life activities; a single regression or an activity based approach. For this we used a device that utilizes single regression models (GT3X, ActiGraph Manufacturing Technology Inc., FL., USA) and a device using activity-dependent calculation models (move II, movisens GmbH, Karlsruhe, Germany). Material and Methods Nineteen adults (11 male, 8 female; 30.4±9.0 years) wore the activity monitors attached to the waist and a portable indirect calorimeter (IC) as reference measure for AEE while performing several typical daily activities. The accuracy of the two devices for estimating AEE was assessed as the mean differences between their output and the reference and evaluated using Bland-Altman analysis. Results The GT3X overestimated the AEE of walking (GT3X minus reference, 1.26 kcal/min), walking fast (1.72 kcal/min), walking up−/downhill (1.45 kcal/min) and walking upstairs (1.92 kcal/min) and underestimated the AEE of jogging (−1.30 kcal/min) and walking upstairs (−2.46 kcal/min). The errors for move II were smaller than those for GT3X for all activities. The move II overestimated AEE of walking (move II minus reference, 0.21 kcal/min), walking up−/downhill (0.06 kcal/min) and stair walking (upstairs: 0.13 kcal/min; downstairs: 0.29 kcal/min) and underestimated AEE of walking fast (−0.11 kcal/min) and jogging (−0.93 kcal/min). Conclusions Our data suggest that the activity monitor using activity-dependent calculation models is more appropriate for predicting AEE in daily life than the activity monitor using a single regression model.

[1]  J. Bussmann,et al.  Ambulatory activity monitoring: Progress in measurement of activity, posture, and specific motion patterns in daily life. , 2009 .

[2]  Dinesh John,et al.  Validation and comparison of ActiGraph activity monitors. , 2011, Journal of science and medicine in sport.

[3]  U. Ekelund,et al.  Assessing physical activity using wearable monitors: measures of physical activity. , 2012, Medicine and science in sports and exercise.

[4]  James E. Graham,et al.  Assessing walking speed in clinical research: a systematic review. , 2008, Journal of evaluation in clinical practice.

[5]  G Plasqui,et al.  Improving assessment of daily energy expenditure by identifying types of physical activity with a single accelerometer. , 2009, Journal of applied physiology.

[6]  R. Allen Ambulatory Activity Monitoring , 2013 .

[7]  K. Campbell,et al.  Field evaluation of energy expenditure in women using Tritrac accelerometers. , 2002, Medicine and science in sports and exercise.

[8]  I-Min Lee,et al.  Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. , 2007, Medicine and science in sports and exercise.

[9]  Paolo Bonato,et al.  Advances in wearable technology and applications in physical medicine and rehabilitation , 2005, Journal of NeuroEngineering and Rehabilitation.

[10]  Gregory J Welk,et al.  Field Validation of the MTI Actigraph and BodyMedia Armband Monitor Using the IDEEA Monitor , 2007, Obesity.

[11]  Klaus Bös,et al.  Estimation of energy expenditure using accelerometers and activity-based energy models—validation of a new device , 2011, European Review of Aging and Physical Activity.

[12]  Ulf Ekelund,et al.  Assessment of physical activity – a review of methodologies with reference to epidemiological research: a report of the exercise physiology section of the European Association of Cardiovascular Prevention and Rehabilitation , 2010, European journal of cardiovascular prevention and rehabilitation : official journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology.

[13]  P. Williams,et al.  Physical activity and public health. , 1995, JAMA.

[14]  D. Warburton,et al.  Health benefits of physical activity: the evidence , 2006, Canadian Medical Association Journal.

[15]  P. A. Mauer,et al.  Physical activity and public health. , 1995, JAMA.

[16]  Scott E Crouter,et al.  Refined two-regression model for the ActiGraph accelerometer. , 2010, Medicine and science in sports and exercise.

[17]  S. Blair,et al.  Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy , 2012, BDJ.

[18]  K. Carlsen,et al.  Validity of physical activity monitors in adults participating in free-living activities , 2008, British Journal of Sports Medicine.

[19]  D A Schoeller,et al.  Measurement of energy expenditure in humans by doubly labeled water method. , 1982, Journal of applied physiology: respiratory, environmental and exercise physiology.

[20]  Emily L. C. Shepard,et al.  Use of overall dynamic body acceleration for estimating energy expenditure in cormorants: Does locomotion in different media affect relationships? , 2011 .

[21]  H. Haugen,et al.  Indirect calorimetry: a practical guide for clinicians. , 2007, Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition.

[22]  D. Altman,et al.  STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT , 1986, The Lancet.

[23]  Stewart G Trost,et al.  Conducting accelerometer-based activity assessments in field-based research. , 2005, Medicine and science in sports and exercise.

[24]  D. Bassett,et al.  Estimating energy expenditure using accelerometers , 2006, European Journal of Applied Physiology.

[25]  Charlie Potter,et al.  Comparison of activity monitors to estimate energy cost of treadmill exercise. , 2004, Medicine and science in sports and exercise.

[26]  C. Maffeis,et al.  Physical activity: an effective way to control weight in children? , 2007, Nutrition, metabolism, and cardiovascular diseases : NMCD.

[27]  J M Bland,et al.  Statistical methods for assessing agreement between two methods of clinical measurement , 1986 .

[28]  Thierry Troosters,et al.  Validity of Six Activity Monitors in Chronic Obstructive Pulmonary Disease: A Comparison with Indirect Calorimetry , 2012, PloS one.

[29]  K Aminian,et al.  Can accelerometry accurately predict the energy cost of uphill/downhill walking? , 2001, Ergonomics.

[30]  D. Macfarlane,et al.  Validity, reliability and stability of the portable Cortex Metamax 3B gas analysis system , 2011, European Journal of Applied Physiology.

[31]  D. Bassett,et al.  Use of a two-regression model for estimating energy expenditure in children. , 2011, Medicine and science in sports and exercise.