New formula may improve ability to predict drinking water needs

Washington, July 9 (ANI): A study has worked out a new formula to predict drinking water needs, which if successful, could accurately forecast 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.

It substantially improves a water needs equation that the US Army developed in 1982.

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 Dr. Samuel N. Cheuvront, one of the researchers involved in the study.

Dr. Cheuvront 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.

The harder an individual exercises, the more oxygen he or she consumes and the more heat the body produces.

Sweat is the body's coolant, but it only cools when it evaporates from the skin.

When it is muggy out, the air is moist, slowing the sweat evaporation rate and reducing its cooling power.

Sweat rate and water needs are difficult to predict because water needs are so variable. Inactive individuals lose between one and three liters of body water a day.

More activity and warmer climates can double or even triple ordinary losses. Sweat rates also vary depending on body size, exercise intensity, clothing, air temperature, humidity, wind, and even the individual's own genes.

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," Dr. Cheuvront said. (ANI)