Expanded Prediction Equations of Human Sweat Loss and Water Needs

Abstract

The Institute of Medicine expressed a need for improved sweating rate (m'sw) 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 m'sw (g*m-2*h-11) +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 m'sw 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 deg 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.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2009
Accession Number
ADA506525

Entities

People

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

Organizations

  • United States Army Research Institute of Environmental Medicine

Tags

DTIC Thesaurus Topics

  • Body Armor
  • Data Sets
  • Department Of Defense
  • Environment
  • Equations
  • Heat Balance
  • Heat Energy
  • Heat Loss
  • Heat Of Vaporization
  • Heat Transfer
  • Heat Transfer Coefficients
  • Latent Heat
  • Protective Clothing
  • Public Health
  • Regression Analysis
  • Vapor Pressure
  • Water Vapor

Fields of Study

  • Environmental science

Readers

  • Computational Modeling and Simulation
  • Exercise and Sports Science.