Expanded prediction equations of human sweat loss and water needs

Author:

Gonzalez R. R.,Cheuvront S. N.,Montain S. J.,Goodman D. A.,Blanchard L. A.,Berglund L. G.,Sawka M. N.

Abstract

The Institute of Medicine expressed a need for improved sweating rate (ṁsw) prediction models that calculate hourly and daily water needs based on metabolic rate, clothing, and environment. More than 25 years ago, the original Shapiro prediction equation (OSE) was formulated as ṁsw (g·m−2·h−1) = 27.9· Ereq·( Emax)−0.455, where Ereq is required evaporative heat loss and Emax is maximum evaporative power of the environment; OSE was developed for a limited set of environments, exposures times, and clothing systems. Recent evidence shows that OSE often overpredicts fluid needs. Our study developed a corrected OSE and a new ṁsw prediction equation by using independent data sets from a wide range of environmental conditions, metabolic rates (rest to ≤450 W/m2), and variable exercise durations. Whole body sweat losses were carefully measured in 101 volunteers (80 males and 21 females; >500 observations) by using a variety of metabolic rates over a range of environmental conditions (ambient temperature, 15–46°C; water vapor pressure, 0.27–4.45 kPa; wind speed, 0.4–2.5 m/s), clothing, and equipment combinations and durations (2–8 h). Data are expressed as grams per square meter per hour and were analyzed using fuzzy piecewise regression. OSE overpredicted sweating rates ( P < 0.003) compared with observed ṁsw. Both the correction equation (OSEC), ṁsw = 147·exp (0.0012·OSE), and a new piecewise (PW) equation, ṁsw = 147 + 1.527· Ereq − 0.87· Emax were derived, compared with OSE, and then cross-validated against independent data (21 males and 9 females; >200 observations). OSEC and PW were more accurate predictors of sweating rate (58 and 65% more accurate, P < 0.01) and produced minimal error (standard error estimate < 100 g·m−2·h−1) for conditions both within and outside the original OSE domain of validity. The new equations provide for more accurate sweat predictions over a broader range of conditions with applications to public health, military, occupational, and sports medicine settings.

Publisher

American Physiological Society

Subject

Physiology (medical),Physiology

Reference31 articles.

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