Validation of combined tri-axial accelerometry and heart rate for predicting energy expenditure during walking in overweight and obese adults

Howe, Christopher (2012) Validation of combined tri-axial accelerometry and heart rate for predicting energy expenditure during walking in overweight and obese adults. (MSc(R) thesis), Kingston University.

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Abstract

Purpose: To validate previously established (Freedson and VM) and newly generated novel prediction equations in overweight and obese inidividuals during a 30 min treadmill walk and three km external self paced overground walk. Methods: Study 1: Twenty overweight and obese adults performed an incremental treadmill walk. EE was measured using breath-by-breath indirect calorimetry. Activity counts and HR were recorded throughout using an AT accelerometer. Study 2: Ten healthy adult males performed three discontinuous maximal tests comparing the laboratory based Oxycon Pro and K4b[sup]2. Study 3: Ten overweight and obese adults carried out a three km overground walk, whilst EE was neasured via the K4b[sup]2 and activity counts and HR were recorded via the AT. Results: The Freedson and VM prediction equations significant overestimated EE by ~40% and 31% respectively. There was good agreement between the Oxycon Pro and K4b[sup]2 when calibrated immediately before use with a mean difference of 38.4 ml.min[sup]-1 (VO[sub]2), 39.5 ml.min[sup]-1 (VCO[sub]2) and 0.76 L.min[sup]-1 (VE). Novel prediction equations combining VM, BM and HR provided the most accurate estimation of EE during indoor and outdoor walking with no difference between measured and estimated EE (P=0.114) with a SEE=0.82 kcal.min[-1] and showed a strong correlation with measured EE (r=0.891, p<0.001). Conclusion: Both the Freedson and VM equations are unsuitable to predict EE in overweight and obese inidividuals. During walking exercise, novel, multiple regression equations combining VM, BM and HR provide a more accurate estimate of EE in this population during treadmill and overground walking. Future directions should focus on the use of these prediction equations during weight loss intervention programmes.

Item Type: Thesis (MSc(R))
Physical Location: This item is held in stock at Kingston University Library.
Research Area: Pre-clinical and human biological sciences
Sports-related studies
Faculty, School or Research Centre: Faculty of Science, Engineering and Computing > School of Life Sciences
Depositing User: Katrina Clifford
Date Deposited: 08 May 2012 15:05
Last Modified: 08 May 2012 15:05
URI: http://eprints.kingston.ac.uk/id/eprint/22520

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