The relative influence of physical fitness, acclimatization state, anthropometric measures and gender on individual reactions to heat stress

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Abstract
An experiment was set up to quantify the relative influence of fitness, acclimatization, gender and anthropometric measures on physiological responses to heat stress. For this purpose, 12 male and 12 female subjects were exposed to a neutral [ambient temperature (T a) 21°C, relative humidity (r.h. 50%)], a warm, humid (T a 34°C, r.h. 80%) and a hot, dry (T a 45°C, r.h. 20%) climate at rest and at two exercise intensities [25%, and 45% maximal O2 intake (VO2max)], seated seminude in a net chair behind a cycle ergometer. Their physiological responses were recorded and the data submitted to a multiple regression analysis. It was shown that for the variance in heat storage, the percentage of body fat and the surface to mass ratio had relatively the largest influence of all the individual parameters, followed by VO2max and the sweat rate versus increase in core temperature (total r 2=92%). For the skin temperature variation, the relative influence of individual parameters (sweat gain, VO2max) was small. For body core temperatures, individual parameters had a large influence. The largest effect was due to the percentage of fat and the surface to mass ratio, followed by the sweating setpoint and, finally, VO2max (total r 2 = 54%−70%). For the variance in heart rate the VO2max was the most relevant parameter, followed by the setpoint of the sweat rate:rectal temperature relationship (total r 2=88%). Blood pressure and skin blood flow predictions were also shown to improve by the addition of individual characteristics to the model. Body surface area, VO2max and the sweating setpoint were shown to have a large influence but the proportion of the variance explained by these variables was too small (r 2 < 70%) to use them as strain predictors, however. For all the predicted variables, it was shown that gender lost its influence, once VO2max or anthropometric data were introduced into the prediction equation.