Energy Expenditure Associated With Froude Number And Traditional Speed Measures In Children And Adolescents.

Abstract

Energy expenditure or metabolic cost of walking is related to speed of locomotion. Leg length normalized speed measures may improve the ability to predict the metabolic cost of walking across the developmental age range. Metrics that improve the strength of the relationship between subject size, walking speed and its metabolic cost may enhance the ability to provide universal recommendations of walking behavior that may serve to improve health. PURPOSE: The purpose of this study was to compare the predictive value of speed in standard units (STD, m/s) to leg length (LL) normalized speed values: the Froude number (Fr) and Dimensionless Speed (DLS) on the metabolic cost of walking in persons 6-20 years of age. We hypothesize that Fr and DLS will improve the prediction of metabolic cost of bipedal transport in children and adolescents. METHODS: : 120 children and adolescents (50% female, 13.1 ± 4.2 years, height 155.6 ± 16.6 cm, mass 56.3 ± 22.3 kg, LL 74.1 ± 9.0 cm) participated in this study. O2 consumption was measured by a K4 portable metabolic system (COSMED). Individuals completed an incremental treadmill protocol 0.22-2.23 m/s, in 0.22m/s increments. The square root of the metabolic data (ml*kg-1*min-1) were compared with all ambulatory speed measures: STD, Fr and DLS. The Akaike information criterion (AIC) was used to compare the linear and quadratic regression models of each gait measure and square root of metabolic cost of walking, best models were selected based on AIC weights. RESULTS: : AIC values indicated that quadratic model provided a better fit for all models of speed and the metabolic cost of walking. AIC weights indicated that DLS (AIC = -489.59) was 315 and 2.45 * 106 times better than Fr (AIC = -478.08) and STD (AIC = -460.16), predicting the metabolic cost of locomotion. CONCLUSIONS: The DLS method of scaling gait speed to leg length offers significant improvements in the ability to predict metabolic cost of locomotion in children and adolescents ages 6-20. Improving the ability to predict metabolic cost from gait parameters may enhance the ability to provide public health recommendations based on objectively measured gait parameters. Funded by Eunice Kennedy Shriver National Institute of Child Health and Human Development: 1R21HD073807-01A1