Location: Food Components and Health LaboratoryTitle: Estimation of metabolic energy expenditure from core temperature using a human thermoregulatory model
|WELLES, ALEXANDER - Us Army Natick Center|
|BULLER, MARK - Us Army Natick Center|
|LOONEY, DAVID - Us Army Natick Center|
|GRIBOK, ANDREI - Department Of Energy|
|HOYT, REED - Us Army Natick Center|
Submitted to: Journal of Thermal Biology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/20/2017
Publication Date: 1/1/2018
Citation: Welles, A., Buller, M.J., Looney, D.P., Rumpler, W.V., Gribok, A.V., Hoyt, R.W. 2018. Estimation of metabolic energy expenditure from core temperature using a human thermoregulatory model. Journal of Thermal Biology. 72:44-52. https://doi.org/10.1016/j.jtherbio.2017.12.007.
Interpretive Summary: Measuring the amount of calories burned by people may provide a means of monitoring and reducing obesity, estimating nutritional requirements, reducing obesity, maintaining energy balance during athletics, and modeling human body temperature responses. However, measuring the rate of calories burned is challenging as the equipment required (gas exchange analyzers, face masks, and/or sealed chambers) can limit the type and intensity of activity during measurement. It is now possible to continuously monitor the body temperature of individual (BT) over extended periods of time by the volunteer ingesting a non toxic, indigestible pill containing a radio transmitter and a temperature sensor. In this study BT was compared to the rate of calorie burning, as measured in the USDA BHNRC room calorimeter. A mathematical formula was developed relating the body temperature to the calories burned. These two measurements, BT and calories burned, were closely related during both rest and during exercise periods. This study suggest that this technique, predicting calories burned from measurements of body temperature may be useful in field studies or circumstances where direct measurements of calories burned are impractical.
Technical Abstract: Measuring metabolic energy expenditure in humans may provide a means of monitoring and reducing obesity, estimating nutritional requirements, reducing obesity, maintaining energy balance during athletics, and modeling human thermoregulatory responses. However, measuring metabolic rate (M) is challenging as the equipment required (gas exchange analyzers, face masks, and/or sealed chambers) can limit the type and intensity of activity during measurement. The use of a previously validated rational thermoregulatory model may provide a means to accurately estimate M from measures of core body temperature (CT). Fifteen test volunteers (age = 23 ± 3 yr, ht =21.73 ± 0.07 m, mass = 68.6 ± 8.7 kg, body fat = 16.7 ± 7.3 %; mean ± SD) participated in up to three Human metabolic energy expenditure is critical to many scientific disciplines but can only be measured using expensive and/or restrictive equipment. The aim of this work is to determine whether the SCENARIO thermoregulatory model can be adapted to estimate metabolic rate (M) from core body temperature (TC). To validate this method of M estimation, data were collected from fifteen test volunteers (age = 23 ± 3yr, height = 1.73 ± 0.07m, mass = 68.6 ± 8.7kg, body fat = 16.7 ± 7.3%; mean ± SD) who wore long sleeved nylon jackets and pants (Itot,clo = 1.22, Im = 0.41) during treadmill exercise tasks (32 trials; 7.8 ± 0.5km in 1h; air temp. = 22°C, 50% RH, wind speed = 0.35ms-1). Core body temperatures were recorded by ingested thermometer pill and M data were measured via whole room indirect calorimetry. Metabolic rate was estimated for 5min epochs in a two-step process. First, for a given epoch, a range of M values were input to the SCENARIO model and a corresponding range of TC values were output. Second, the output TC range value with the lowest absolute error relative to the observed TC for the given epoch was identified and its corresponding M range input was selected as the estimated M for that epoch. This process was then repeated for each subsequent remaining epoch. Root mean square error (RMSE), mean absolute error (MAE), and bias between observed and estimated M were 186W, 130 ± 174W, and 33 ± 183W, respectively. The RMSE for total energy expenditure by exercise period was 0.30 MJ. These results indicate that the SCENARIO model is useful for estimating M from TC when measurement is otherwise impractical.