Army Lab Study 'Improves' Water Needs Equation
When soldiers leave base for a three-day mission, how much water should they bring?
The new study substantially improves a water needs equation that the U.S. Army developed in 1982. That equation, known as the Shairo equation, overestimates water needs.
The study produced formulations that are 58-65 percent more accurate than the Shapiro equation, at least in the laboratory. If the new formula works in the field, as expected, it could accurately predict water needs not only for soldiers but also for civilians who work or exercise outdoors.
The study, "Expanded prediction equations of human sweat loss and water needs," appears in the online edition of the Journal of Applied Physiology. The researchers are Richard R. Gonzalez, Samuel N. Cheuvront, Scott J. Montain, Daniel A. Goodman, Laurie A. Blanchard, Larry G. Berglund and Michael N. Sawka. The researchers are with the U.S. Army Research Institute of Environmental Medicine, except for Dr. Gonzalez, who is an adjunct professor at New Mexico State University. The American Physiological Society published the study.
The Army spends substantial resources transporting water to troops in the field, including Afghanistan and Iraq. Water transport accounts for about one-third of in-theatre costs, according to Cheuvront. He points out that an improved sweating prediction equation would not only help keep troops healthy and cut the cost of operations but would also facilitate better civilian water planning when desired.
In this study, the researchers collected data on 80 men and 21 women who exercised in the laboratory under varying conditions of work intensity and duration, environmental conditions such as temperature and humidity, and types of clothing. They measured the sweat losses for each volunteer and compared that to the sweat loss predicted by the equation. Once they were able to compare the prediction versus the real sweat rate, they derived specific algorithms statistically so that the predictions would more accurately reflect the observed sweat rates.
The study produced two equations. The researchers then cross validated the new equations, using new data from 21 men and 9 women. One of the equations increased the prediction accuracy by 58 percent and one increased accuracy by 65 percent. Either of these equations would provide predictions accurate enough to be used in the field, Cheuvront said.
The researchers hope to develop either a table or an online application program in which an individual could enter variables such as height and weight, how hard and long they would be active and what the environmental conditions would be (temperature, humidity, sunlight and wind). The device would then calculate their sweat loss.
One variable the equation does not take into account is fitness levels, which do influence sweat rates. That may be the next area to work into the equation, Cheuvront said.