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Am J Physiol Regul Integr Comp Physiol. 2010 Aug;299(2):R387-94. doi: 10.1152/ajpregu.00546.2009. Epub 2010 May 26.

Estimating changes in volume-weighted mean body temperature using thermometry with an individualized correction factor.

Author information

1
Human and Environmental Physiology Research Unit, School of Human Kinetics, University of Ottawa, Ottawa, Ontario, Canada. ojay@uottawa.ca

Abstract

This study investigated whether the estimation error of volume-weighted mean body temperature (DeltaT(b)) using changes in core and skin temperature can be accounted for using personal and environmental parameters. Whole body calorimetry was used to directly measure DeltaT(b) in an Experimental group (EG) of 36 participants (24 males, 12 females) and a Validation group (VG) of 20 (9 males, 11 females) throughout 90 min of cycle ergometry at 40 degrees C, 30% relative humidity (RH) (n = 9 EG, 5 VG); 30 degrees C, 30% RH (n = 9 EG, 5 VG); 30 degrees C, 60% RH (n = 9 EG, 5 VG); and 24 degrees C, 30% RH (n = 9 EG, 5 VG). The core of the two-compartment thermometry model was represented by rectal temperature and the shell by a 12-point mean skin temperature (DeltaT(sk)). The estimation error (X(0)) between DeltaT(b) from calorimetry and DeltaT(b) from thermometry using core/shell weightings of 0.66/0.34, 0.79/0.21, and 0.90/0.10 was calculated after 30, 60, and 90 min of exercise, respectively. The association between X(0) and the individual variation in metabolic heat production (M - W), body surface area (BSA), body fat percentage (%fat), and body surface area-to-mass ratio (BSA/BM) as well as differences in environmental conditions (Oxford index) in the EG data were assessed using stepwise linear regression. At all time points and with all core/shell weightings tested, M - W, BSA, and Oxford index independently correlated significantly with the residual variance in X(0), but %fat and BSA/BM did not. The subsequent regression models were used to predict the thermometric estimation error (X(0_pred)) for each individual in the VG. The value estimated for X(0_pred) was then added to the DeltaT(b) estimated using the two-compartment thermometry models yielding an adjusted estimation (DeltaT(b)_(adj)) for the individuals in the VG. When comparing DeltaT(b)_(adj) to the DeltaT(b) derived from calorimetry in the VG, the best performing model used a core/shell weighting of 0.66/0.34 describing 74%, 84%, and 82% of the variation observed in DeltaT(b) from calorimetry after 30, 60, and 90 min, respectively.

PMID:
20504906
DOI:
10.1152/ajpregu.00546.2009
[Indexed for MEDLINE]
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