Energy expenditure during level XXXX walking: seeking a simple and accurate predictive solution.

@entity1 @entity3612 @entity353
UNASSIGNED: Accurate prediction of the metabolic energy walking requires can inform numerous health, bodily status and fitness outcomes. Here, we adopted a two-step approach to identifying a concise, generalized equation for predicting level @entity1 walking metabolism. Using literature-aggregated values, we compared: 1) the predictive accuracy of three literature equations: ACSM, Pandolf, and @entity353 ( @entity353 ) equations, and 2) the goodness-of-fit possible from one- vs. two-component descriptions of walking metabolism. Literature metabolic rate values (n=127; speed range=0.4-1.9 m   s(-1)) were aggregated from 25 subject populations (n=5-42) whose means spanned a 1.8-fold range of heights and a 4.2-fold range of weights. Population-specific resting metabolic rates (VO2-rest) were determined using standardized equations. Our first finding was that the ACSM and Pandolf equations under-predicted nearly all 127 literature-aggregated values. Consequently, their standard errors of estimate (SEE) were nearly four times greater than those of the @entity353 equation (4.51 and 4.39 vs. 1.13 mls O2   kg(-1)   min(-1), respectively). For our second comparison, empirical best-fit relationships for walking metabolism were derived from the data set in one- and two-component forms for three VO2-speed model types: linear (   V(1.0)), exponential (   V(2.0)), and exponential/height (   V(2.0)/Ht). We found that the proportion of variance (R(2)) accounted for, when averaged across the three model types, was substantially lower for one- vs. two-component versions (0.63  0.1 vs. 0.90  0.03) and the predictive errors were nearly twice as great (SEE=2.22 vs. 1.21 mls O2   kg(-1)   min(-1)). Our final analysis identified the following concise, generalized equation for predicting level @entity1 walking metabolism: VO2-total=VO2-rest+3.85+5.97   V(2)/Ht (units: V, m   s(-1); Ht, m; and VO2, mls @entity3612   kg(-1)   min(-1)).
