Human and Environmental Physiology Research Unit, School of Human Kinetics, University of Ottawa, Ottawa, Ontario, Canada.
Am J Physiol Regul Integr Comp Physiol. 2010 Aug;299(2):R387-94. doi: 10.1152/ajpregu.00546.2009. Epub 2010 May 26.
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.
本研究旨在探讨使用核心温度和皮肤温度的变化来估计体加权平均体温(DeltaT(b))时,个人和环境参数是否可以解释估计误差。在 40°C、30%相对湿度(RH)(n = 9 EG,5 VG)、30°C、30%RH(n = 9 EG,5 VG)、30°C、60%RH(n = 9 EG,5 VG)和 24°C、30%RH(n = 9 EG,5 VG)下,通过全身量热法直接测量 36 名参与者(24 名男性,12 名女性)的实验组(EG)和 20 名参与者(9 名男性,11 名女性)的整个实验过程中的 DeltaT(b),实验时间为 90 分钟。双室测温模型的核心由直肠温度表示,外壳由 12 点平均皮肤温度(DeltaT(sk))表示。在运动 30、60 和 90 分钟后,分别计算 DeltaT(b)的测量值与使用核心/外壳权重为 0.66/0.34、0.79/0.21 和 0.90/0.10 的 DeltaT(b)的测温模型之间的估计误差(X(0))。使用逐步线性回归评估 X(0)与 EG 中个体代谢产热(M - W)、体表面积(BSA)、体脂肪百分比(%fat)和体表面积与质量比(BSA/BM)个体差异以及环境条件(牛津指数)之间的关系。在所有时间点和所有测试的核心/外壳权重下,M - W、BSA 和牛津指数均与 X(0)的剩余方差独立显著相关,但 %fat 和 BSA/BM 则不然。随后的回归模型用于预测 VG 中每个个体的测温估计误差(X(0_pred))。然后将估计的 X(0_pred)值添加到使用双室测温模型估计的 DeltaT(b)中,得到 VG 中个体的调整估计值(DeltaT(b)(adj))。当将 DeltaT(b)(adj)与 VG 中从量热法得出的 DeltaT(b)进行比较时,表现最好的模型使用核心/外壳权重为 0.66/0.34,分别描述了 30、60 和 90 分钟后从量热法得出的 DeltaT(b)观察到的变异的 74%、84%和 82%。