Estimation of Free-Living Energy Expenditure by Heart Rate and Movement Sensing: A Doubly-Labelled Water Study

PLOS ONE, Dec 2019

Background Accurate assessment of energy expenditure (EE) is important for the study of energy balance and metabolic disorders. Combined heart rate (HR) and acceleration (ACC) sensing may increase precision of physical activity EE (PAEE) which is the most variable component of total EE (TEE). Objective To evaluate estimates of EE using ACC and HR data with or without individual calibration against doubly-labelled water (DLW) estimates of EE. Design 23 women and 23 men (22–55 yrs, 48–104 kg, 8–46%body fat) underwent 45-min resting EE (REE) measurement and completed a 20-min treadmill test, an 8-min step test, and a 3-min walk test for individual calibration. ACC and HR were monitored and TEE measured over 14 days using DLW. Diet-induced thermogenesis (DIT) was calculated from food-frequency questionnaire. PAEE (TEE ÷ REE ÷ DIT) and TEE were compared to estimates from ACC and HR using bias, root mean square error (RMSE), and correlation statistics. Results Mean(SD) measured PAEE and TEE were 66(25) kJ·day-1·kg-1, and 12(2.6) MJ·day-1, respectively. Estimated PAEE from ACC was 54(15) kJ·day-1·kg-1 (p<0.001), with RMSE 24 kJ·day-1·kg-1 and correlation r = 0.52. PAEE estimated from HR and ACC+HR with treadmill calibration were 67(42) and 69(25) kJ·day-1·kg-1 (bias non-significant), with RMSE 34 and 20 kJ·day-1·kg-1 and correlations r = 0.58 and r = 0.67, respectively. Similar results were obtained with step-calibrated and walk-calibrated models, whereas non-calibrated models were less precise (RMSE: 37 and 24 kJ·day-1·kg-1, r = 0.40 and r = 0.55). TEE models also had high validity, with biases <5%, and correlations r = 0.71 (ACC), r = 0.66–0.76 (HR), and r = 0.76–0.83 (ACC+HR). Conclusions Both accelerometry and heart rate may be used to estimate EE in adult European men and women, with improved precision if combined and if heart rate is individually calibrated.

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Estimation of Free-Living Energy Expenditure by Heart Rate and Movement Sensing: A Doubly-Labelled Water Study

September Estimation of Free-Living Energy Expenditure by Heart Rate and Movement Sensing: A Doubly-Labelled Water Study Editor: François Criscuolo 0 CNRS 0 FRANCE 0 Søren Brage 0 Kate Westgate 0 Paul W. Franks 0 Oliver Stegle 0 Antony Wright 0 Ulf Ekelund 0 Nicholas J. Wareham 0 0 1 MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom, 2 Department of Clinical Sciences, Lund University , Malmö , Sweden , 3 Department of Physics, University of Cambridge, Cambridge, United Kingdom, 4 European Molecular Biology Laboratory, European Bioinformatics Institute , Hinxton, Cambridge , United Kingdom , 5 MRC Human Nutrition Research, Cambridge , United Kingdom - Data Availability Statement: The authors can confirm that all non-identifiable data are available on request to the corresponding author. Their consent prevents the authors from making these data available publicly; third-party researchers would need to sign a collaborative agreement. The authors' data sharing policies and processes meet the requirements and expectations of MRC policy on sharing of data from population and patient cohorts: http://www.mrc.ac.uk/research/research-policy-ethics/ data-sharing/policy/. These policies and processes are in place to ensure that the use of data from this study is within the bounds of consent given previously Accurate assessment of energy expenditure (EE) is important for the study of energy balance and metabolic disorders. Combined heart rate (HR) and acceleration (ACC) sensing may increase precision of physical activity EE (PAEE) which is the most variable component of total EE (TEE). To evaluate estimates of EE using ACC and HR data with or without individual calibration against doubly-labelled water (DLW) estimates of EE. 23 women and 23 men (22–55 yrs, 48–104 kg, 8–46%body fat) underwent 45-min resting EE (REE) measurement and completed a 20-min treadmill test, an 8-min step test, and a 3-min walk test for individual calibration. ACC and HR were monitored and TEE measured over 14 days using DLW. Diet-induced thermogenesis (DIT) was calculated from food-frequency questionnaire. PAEE (TEE REE DIT) and TEE were compared to estimates from ACC and HR using bias, root mean square error (RMSE), and correlation statistics. Mean(SD) measured PAEE and TEE were 66(25) kJ day-1 kg-1, and 12(2.6) MJ day-1, respectively. Estimated PAEE from ACC was 54(15) kJ day-1 kg-1 (p<0.001), with RMSE 24 kJ day-1 kg-1 and correlation r = 0.52. PAEE estimated from HR and ACC+HR with treadmill calibration were 67(42) and 69(25) kJ day-1 kg-1 (bias non-significant), with RMSE 34 and 20 kJ day-1 kg-1 and correlations r = 0.58 and r = 0.67, respectively. Similar results were obtained with step-calibrated and walk-calibrated models, whereas non-calibrated by study members, complies with MRC guidance on ethics and research governance, and meets rigorous MRC data security standards. Funding: This study received funding from Medical Research Council (MC_UU_12015/3), Wellcome Trust, Unilever UK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript Competing Interests: This study was partly funded by Unilever UK. There are no patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors. models were less precise (RMSE: 37 and 24 kJ day-1 kg-1, r = 0.40 and r = 0.55). TEE models also had high validity, with biases <5%, and correlations r = 0.71 (ACC), r = 0.66–0.76 (HR), and r = 0.76–0.83 (ACC+HR). Both accelerometry and heart rate may be used to estimate EE in adult European men and women, with improved precision if combined and if heart rate is individually calibrated. Precise assessment of energy expenditure (EE) is essential for studies of energy balance and has been used to identify underreporting of food intake [1]. Physical activity energy expenditure (PAEE) is the most variable component of total energy expenditure (TEE) and the most difficult to assess during free-living conditions. The most accurate method is doubly-labelled water (DLW) assessment of TEE combined with measurement of the resting metabolic rate (RMR) via indirect calorimetry [2,3]. These procedures require high levels of technical expertise, are relatively expensive, and yield no information about underlying patterns of energy expenditure over shorter periods of time, e.g. the intensity profile. Wearable sensors have potential to provide estimates of PAEE which may be combined with estimates of REE; an approach which holds promise for better quantifying dose-response relationships between EE and health outcomes, as well as assessing intervention effects in trials, where self-report measures could be biased [4]. For the assessment of PAEE, previous studies have demonstrated the advantage of integrating physiological measures, li (...truncated)


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Søren Brage, Kate Westgate, Paul W. Franks, Oliver Stegle, Antony Wright, Ulf Ekelund, Nicholas J. Wareham. Estimation of Free-Living Energy Expenditure by Heart Rate and Movement Sensing: A Doubly-Labelled Water Study, PLOS ONE, 2015, 9, DOI: 10.1371/journal.pone.0137206