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Metabolic Costs of Standing and Walking in Healthy Military-Age Adults

A Meta-regression

LOONEY, DAVID P.1; POTTER, ADAM W.1; PRYOR, J. LUKE2; BREMNER, PATRICIA E.3; CHALMERS, CHRISTOPHER R.1,4; MCCLUNG, HOLLY L.1; WELLES, ALEXANDER P.1; SANTEE, WILLIAM R.1,4

Medicine & Science in Sports & Exercise: February 2019 - Volume 51 - Issue 2 - p 346–351
doi: 10.1249/MSS.0000000000001779
APPLIED SCIENCES

Introduction The Load Carriage Decision Aid (LCDA) is a U.S. Army planning tool that predicts physiological responses of soldiers during different dismounted troop scenarios. We aimed to develop an equation that calculates standing and walking metabolic rates in healthy military-age adults for the LCDA using a meta-regression.

Methods We searched for studies that measured the energetic cost of standing and treadmill walking in healthy men and women via indirect calorimetry. We used mixed effects meta-regression to determine an optimal equation to calculate standing and walking metabolic rates as a function of walking speed (S, m·s−1). The optimal equation was used to determine the economical speed at which the metabolic cost per distance walked is minimized. The estimation precision of the new LCDA walking equation was compared with that of seven reference predictive equations.

Results The meta-regression included 48 studies. The optimal equation for calculating normal standing and walking metabolic rates (W·kg−1) was 1.44 + 1.94S 0.43 + 0.24S 4. The economical speed for level walking was 1.39 m·s−1 (~ 3.1 mph). The LCDA walking equation was more precise across all walking speeds (bias ± SD, 0.01 ± 0.33 W·kg−1) than the reference predictive equations.

Conclusion Practitioners can use the new LCDA walking equation to calculate energy expenditure during standing and walking at speeds <2 m·s−1 in healthy, military-age adults. The LCDA walking equation avoids the errors estimated by other equations at lower and higher walking speeds.

1U.S. Army Research Institute of Environmental Medicine (USARIEM), Natick, MA;

2Department of Kinesiology, California State University, Fresno, CA;

3Alvin O. Ramsley Technical Library, U.S. Army Natick Soldier Research, Development and Engineering Center, Natick, MA; and

4Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN

Address for correspondence: David P. Looney, Ph.D., U.S. Army Research Institute of Environmental Medicine (USARIEM), 10 General Greene Avenue, Natick, MA 01760; E-mail: david.p.looney4.civ@mail.mil.

Submitted for publication August 2018.

Accepted for publication August 2018.

© 2019 American College of Sports Medicine