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J Appl Physiol (1985). 2012 Apr;112(8):1300-10. doi: 10.1152/japplphysiol.01056.2011. Epub 2012 Jan 12.

Sweat rate prediction equations for outdoor exercise with transient solar radiation.

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Biology Department, New Mexico State University, Las Cruces, New Mexico, USA.


We investigated the validity of employing a fuzzy piecewise prediction equation (PW) [Gonzalez et al. J Appl Physiol 107: 379-388, 2009] defined by sweat rate (m(sw), g·m(-2)·h(-1)) = 147 + 1.527·(E(req)) - 0.87·(E(max)), which integrates evaporation required (E(req)) and the maximum evaporative capacity of the environment (E(max)). Heat exchange and physiological responses were determined throughout the trials. Environmental conditions were ambient temperature (T(a)) = 16-26°C, relative humidity (RH) = 51-55%, and wind speed (V) = 0.5-1.5 m/s. Volunteers wore military fatigues [clothing evaporative potential (i(m)/clo) = 0.33] and carried loads (15-31 kg) while marching 14-37 km over variable terrains either at night (N = 77, trials 1-5) or night with increasing daylight (N = 33, trials 6 and 7). PW was modified (Pw,sol) for transient solar radiation (R(sol), W) determined from measured solar loads and verified in trials 6 and 7. PW provided a valid m(sw) prediction during night trials (1-5) matching previous laboratory values and verified by bootstrap correlation (r(bs) of 0.81, SE ± 0.014, SEE = ± 69.2 g·m(-2)·h(-1)). For trials 6 and 7, E(req) and E(max) components included R(sol) applying a modified equation Pw,sol, in which m(sw) = 147 + 1.527·(E(req,sol)) - 0.87·(E(max)). Linear prediction of m(sw) = 0.72·Pw,sol + 135 (N = 33) was validated (R(2) = 0.92; SEE = ±33.8 g·m(-2)·h(-1)) with PW β-coefficients unaltered during field marches between 16°C and 26°C T(a) for m(sw) ≤ 700 g·m(-2)·h(-1). PW was additionally derived for cool laboratory/night conditions (T(a) < 20°C) in which E(req) is low but E(max) is high, as: PW,cool (g·m(-2)·h(-1)) = 350 + 1.527·E(req) - 0.87·E(max). These sweat prediction equations allow valid tools for civilian, sports, and military medicine communities to predict water needs during a variety of heat stress/exercise conditions.

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