PURPOSE: Accuracy of estimating activity-related energy expenditure (AEE) from raw body acceleration may improve by using prediction equations that are specific for the type of activity. The current study aims to improve published equations by deriving an equation for overground walking and to evaluate whether overground cycling and stair walking require specific prediction equations. METHODS: Participants (91 male/95 female, 8-81 yr old) were equipped with a triaxial accelerometer (DynaPort MiniMod; McRoberts BV, The Hague, The Netherlands) on their lower back. Total energy expenditure (TEE) was measured using a mobile oxygen analyzer (MetaMax 3b; Cortex Biophysik, Leipzig, Germany). Resting energy expenditure (REE) was measured for 30 min, following which a physical activity course was completed involving walking on level ground at slow (8 min), normal (8 min), and fast speed (3 min), stair walking (3 min), and cycling (8 min). AEE was calculated as TEE - REE, expressed in both absolute (kJ·min) and relative (J·min·kg) units. Mixed linear regression analysis was used for developing regression equations for walking, stair walking, and cycling. RESULTS: Acceleration contributed 76% and 93% (P < 0.001) to explained variance in walking AEE for absolute and relative AEE models, respectively. Age and gender improved estimation accuracy by <1%. Applying a conservative walking equation, AEE (J·min·kg) = -40.19 + 816.11 acceleration (g) (root-mean-square error = 34.00 J·min·kg), to cycling and stair walking resulted in mean bias (95% limits of agreement) of -253 (-449, 46) and -276 (-442, 109) J·min·kg, respectively (approximately 50% bias). Acceleration added 35% and 42% to explained variance in relative AEE (J·min·kg) during cycling and stair walking, respectively; this fraction was approximately 20% for absolute AEE (kJ·min) in both activities. CONCLUSION: AEE during walking can be predicted across a wide age range using raw acceleration, but activity-specific equations are needed for cycling and stair walking.
PURPOSE: Accuracy of estimating activity-related energy expenditure (AEE) from raw body acceleration may improve by using prediction equations that are specific for the type of activity. The current study aims to improve published equations by deriving an equation for overground walking and to evaluate whether overground cycling and stair walking require specific prediction equations. METHODS: Participants (91 male/95 female, 8-81 yr old) were equipped with a triaxial accelerometer (DynaPort MiniMod; McRoberts BV, The Hague, The Netherlands) on their lower back. Total energy expenditure (TEE) was measured using a mobile oxygen analyzer (MetaMax 3b; Cortex Biophysik, Leipzig, Germany). Resting energy expenditure (REE) was measured for 30 min, following which a physical activity course was completed involving walking on level ground at slow (8 min), normal (8 min), and fast speed (3 min), stair walking (3 min), and cycling (8 min). AEE was calculated as TEE - REE, expressed in both absolute (kJ·min) and relative (J·min·kg) units. Mixed linear regression analysis was used for developing regression equations for walking, stair walking, and cycling. RESULTS: Acceleration contributed 76% and 93% (P < 0.001) to explained variance in walking AEE for absolute and relative AEE models, respectively. Age and gender improved estimation accuracy by <1%. Applying a conservative walking equation, AEE (J·min·kg) = -40.19 + 816.11 acceleration (g) (root-mean-square error = 34.00 J·min·kg), to cycling and stair walking resulted in mean bias (95% limits of agreement) of -253 (-449, 46) and -276 (-442, 109) J·min·kg, respectively (approximately 50% bias). Acceleration added 35% and 42% to explained variance in relative AEE (J·min·kg) during cycling and stair walking, respectively; this fraction was approximately 20% for absolute AEE (kJ·min) in both activities. CONCLUSION: AEE during walking can be predicted across a wide age range using raw acceleration, but activity-specific equations are needed for cycling and stair walking.
Authors: Jos Hendrikx; Loes S Ruijs; Lieke Ge Cox; Paul Mc Lemmens; Erik Gp Schuijers; Annelies Hc Goris Journal: JMIR Mhealth Uhealth Date: 2017-02-02 Impact factor: 4.773
Authors: Dafne van Kuppevelt; Joe Heywood; Mark Hamer; Séverine Sabia; Emla Fitzsimons; Vincent van Hees Journal: PLoS One Date: 2019-01-09 Impact factor: 3.240
Authors: Marcel den Hoed; Søren Brage; Jing Hua Zhao; Kate Westgate; Ayrun Nessa; Ulf Ekelund; Tim D Spector; Nicholas J Wareham; Ruth J F Loos Journal: Am J Clin Nutr Date: 2013-09-18 Impact factor: 7.045
Authors: Christiane A Hoppmann; Jessica Chak Man Lee; Jochen P Ziegelmann; Peter Graf; Karim M Khan; Maureen C Ashe Journal: J Gerontol B Psychol Sci Soc Sci Date: 2017-09-01 Impact factor: 4.077
Authors: Soren Brage; Tim Lindsay; Michelle Venables; Katrien Wijndaele; Kate Westgate; David Collins; Caireen Roberts; Les Bluck; Nick Wareham; Polly Page Journal: Int J Epidemiol Date: 2020-06-01 Impact factor: 7.196