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United States Department of Agriculture

Agricultural Research Service

Title: Energy Expenditure in Children Predicted from Heart Rate and Activity Calibrated Against Respiration Calorimetry

Authors
item Treuth, Margarita - BAYLOR COLL OF MEDICINE
item Adolph, Anne - BAYLOR COLL OF MEDICINE
item Butte, Nancy

Submitted to: American Journal of Physiology - Endocrinology and Metabolism
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 2, 1998
Publication Date: N/A

Interpretive Summary: The objective of this study was to determine whether the energy expenditure of 20 children could be accurately predicted on the basis of measurements of each person's heart rate and movement. These were calibrated against 24- hour room respiration calorimetry. We used respiration calorimetry sensors, leg activity sensors, and portable heart rate monitors to measure the children's activity. We know that the individual's heart rate can be used to estimate energy expenditure, since there is a linear relationship between a person's heart rate and the amount of oxygen he consumes. Respiration calorimetry and the doubly labeled water method are accurate ways to assess daily energy expenditure, but both are expensive and require sophisticated instruments. We wanted to improve the relatively simple heart rate method for use in predicting energy expenditure. Our results showed that the combination of heart rate and activity is an acceptable method for rdetermining energy expenditure not only for groups, but for individuals. W can predict the amount of calories an individual burns in one day based on these measurements.

Technical Abstract: The purpose of this study was to predict energy expenditure (EE) from heart rate (HR) and activity calibrated against 24-h respiration calorimetry in 20 children. HR, VO2, VCO2 and EE were measured during rest, sleep, exercise and over 24 h by room respiration calorimetry on two separate occasions. Activity was monitored by a leg vibration sensor. The calibration day (day 1) consisted of specified behaviors categorized as inactive (lying, sitting, standing) or active (two bicycle sessions). On the validation day (day 2), the child selected activities. Separate regression equations for VO2, VCO2 and EE for Method 1 (combining awake and asleep using HR, HR2 and HR3), Method 2 (separating awake and asleep), and Method 3 (separating awake into active and inactive, and combining activity and heart rate) were developed using the calibration data. For day 1, the errors were similar for 24-h VO2, VCO2 and EE among methods and also among HR, HR2 and HR3. The methods were validated using measured data from day 2 There were no significant differences in HR, VO2, VCO2, RQ and EE values during rest, sleep or over the 24 h between days 1 and 2. Applying the linear HR equations to day 2 data, the errors were the lowest with the combined HR/activity method (-2.6+/-5.2%, -4.1+/-5.9%, -2.9+/-5.1% for VO2, VCO2 and EE, respectively). To demonstrate the utility of the HR/activity method, HR and activity were monitored for 24 h at home (day 3). Free- living EE was predicted as 7410+/-1326 kJ/day. In conclusion, the combination of HR and activity is an acceptable method for determining EE not only for groups of children, but for individuals.

Last Modified: 12/18/2014
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