Predicting metabolic rate across walking speed: one fit for all body sizes?

Does human foot anthropometry relate to plantar flexor fascicle mechanics and metabolic energy cost across various walking speeds?

Foot structures define the leverage in which the ankle muscles push off against the ground during locomotion. While prior studies have indicated that inter-individual variation in anthropometry (e.g. heel and hallux lengths) can directly affect force production of ankle plantar flexor muscles, its effect on the metabolic energy cost of locomotion has been inconclusive. Here, we tested the hypotheses that shorter heels and longer halluces are associated with slower plantar flexor (soleus) shortening velocity and greater ankle plantar flexion moment, indicating enhanced force potential as a result of the force-velocity relationship. We also hypothesized that such anthropometry profiles would reduce the metabolic energy cost of walking at faster walking speeds. Healthy young adults (N=15) walked at three speeds (1.25, 1.75 and 2.00 m s-1), and we collected in vivo muscle mechanics (via ultrasound), activation (via electromyography) and whole-body metabolic energy cost of transport (via indirect calorimetry). Contrary to our hypotheses, shorter heels and longer halluces were not associated with slower soleus shortening velocity or greater plantar flexion moment. Additionally, longer heels were associated with reduced metabolic cost of transport, but only at the fastest speed (2.00 m s-1, R2=0.305, P=0.033). We also found that individuals with longer heels required less increase in plantar flexor (soleus and gastrocnemius) muscle activation to walk at faster speeds, potentially explaining the reduced metabolic cost.

Accuracy of Metabolic Cost Predictive Equations During Military Load Carriage

ABSTRACT

Vine, CA, Coakley, SL, Blacker, SD, Doherty, J, Hale, B, Walker, EF, Rue, CA, Lee, BJ, Flood, TR, Knapik, JJ, Jackson, S, Greeves, JP, and Myers, SD. Accuracy of metabolic cost predictive equations during military load carriage. J Strength Cond Res 36(5): 1297-1303, 2022-To quantify the accuracy of 5 equations to predict the metabolic cost of load carriage under ecologically valid military speed and load combinations. Thirty-nine male serving infantry soldiers completed thirteen 20-minute bouts of overground load carriage comprising 2 speeds (2.5 and 4.8 km·h-1) and 6 carried equipment load combinations (25, 30, 40, 50, 60, and 70 kg), with 22 also completing a bout at 5.5 km·h-1 carrying 40 kg. For each speed-load combination, the metabolic cost was measured using the Douglas bag technique and compared with the metabolic cost predicted from 5 equations; Givoni and Goldman, 1971 (GG), Pandolf et al. 1997 (PAN), Santee et al. 2001 (SAN), American College of Sports Medicine 2013 (ACSM), and the Minimum-Mechanics Model (MMM) by Ludlow and Weyand, 2017. Comparisons between measured and predicted metabolic cost were made using repeated-measures analysis of variance and limits of agreement. All predictive equations, except for PAN, underpredicted the metabolic cost for all speed-load combinations (p < 0.001). The PAN equation accurately predicted metabolic cost for 40 and 50 kg at 4.8 km·h-1 (p > 0.05), underpredicted metabolic cost for all 2.5 km·h-1 speed-load combinations as well as 25 and 30 kg at 4.8 km·h-1, and overpredicted metabolic cost for 60 and 70 kg at 4.8 km·h-1 (p < 0.001). Most equations (GG, SAN, ACSM, and MMM) underpredicted metabolic cost while one (PAN) accurately predicted at moderate loads and speeds, but overpredicted or underpredicted at other speed-load combinations. Our findings indicate that caution should be applied when using these predictive equations to model military load carriage tasks.

Energy Expenditure of Level Overground Walking in Young Adults: Comparison With Prediction Equations

BACKGROUND

The purpose of this study was to investigate the accuracy of the published prediction equations for determining level overground walking energy cost in young adults.

METHODS

In total, 148 healthy young adults volunteered to participate in this study. Resting metabolic rate and energy expenditure variables at speeds of 4, 5, and 6 km/h were measured by indirect calorimetry, walking energy expenditure was estimated by 3 published equations.

RESULTS

The gross and net metabolic rate per mile of level overground walking increased with increased speed (all P < .01). Females were less economical than males. The present findings revealed that the American College of Sports Medicine and Pandolf et al equations significantly underestimated the energy cost of overground walking at all speeds (all P < .01) in young adults. The percentage mean bias for American College of Sports Medicine, Pandolf et al, and Weyand et al was 12.4%, 16.8%, 1.4% (4 km/h); 21.6%, 15.8%, 7.1% (5 km/h); and 27.6%, 12%, 6.6% (6 km/h). Bland-Altman plots and prediction error analysis showed that the Weyand et al was the most accurate in 3 existing equations.

CONCLUSIONS

The Weyand et al equation appears to be the most suitable for the prediction of overground walking energy expenditure in young adults.

Associations of inter-segmental coordination and treadmill walking economy in youth with cerebral palsy

This study investigated associations of thigh-shank coordination deficit severity and metabolic demands of walking in youth with cerebral palsy (CP) and their typically developing (TD) peers. Youth (ages 8-18 years) with hemiplegic and diplegic CP [Gross Motor Classification System (GMFCS) I-III] and their age (within 12 months) and sex-matched peers performed a modified six-minute-walk-test on a treadmill. Kinematics (Motion Analysis, USA, 240 Hz) and mass-specific gross metabolic rate (GMR; COSMED, Italy) were analyzed for minute two of treadmill walking. Thigh-shank coordination was determined using continuous relative phase (CRP) analysis. GMR was normalized using participant specific Froude numbers (i.e. GMR_Eq). Maximum and minimum CRP deficit angles (CRP_Max,CRP_Min) were analysed in SPSS (IBM, USA) using paired samples t-tests with Bonferroni correction (p = 0.0125). Associations of knee extension angle deficit (KED_Max) and coordination outcomes with GMR_Eq (log) were assessed using multiple linear regression. Twenty-eight matched pairs were included, demonstrating significantly larger CRP_Max for youth with CP [GMFCS I mean pair difference (98.75%CI) 8.2 (-0.1,16.5), P = 0.013; GMFCS II/III 26.1 (2.3,50.0), P = 0.008]. Joint kinematics and coordination outcomes were significantly associated with GMR_Eq (P < 0.001), primarily due to CRP_Max (P < 0.001), leading to a 1.7 (95%CI; 1.1, 2.4)% increase in GMR_Eq for every degree increase in CRP_Max. These findings indicate an association of thigh-shank coordination deficit severity and increasing metabolic demands of walking in youth with CP. CRP may be a clinically useful predictor of metabolic demands of walking in CP. Future work will evaluate the sensitivity of CRP to coordination and walking economy changes with surgical and non-surgical management.

Factors Affecting Performance on an Army Urban Operation Casualty Evacuation for Male and Female Soldiers

INTRODUCTION

This study was conducted to determine what physical and physiological characteristics contribute to the performance of an urban operation casualty evacuation (UO) and its predictive test, FORCE combat (FC) and describe the metabolic demand of the UO in female soldiers.

METHODS

Seventeen military members (9 M and 8 F) completed a loaded walking maximal aerobic test, the UO and FC. Heart rate reserve (HRR) and completion time were used as efficiency/performance measures. Oxygen consumption (VO2) was directly measured for UO on five female participants with a portable indirect calorimetry system, and analyzed using descriptive statistics. Stepwise multiple regression analysis was used to determine the contribution of the non-modifiable (age, sex, height) and modifiable characteristics (lean body mass to dead mass ratio (LBM:DM), VO2max corrected for load (L.VO2max), peak force (PF) measured on an isometric mid-thigh pull (IMTP) and medicine ball chest throw distance (Dist) on to the performance of each exercise.

RESULTS

LBM:DM and PF were the only factors included in the stepwise regression model for UO, predicting 70% of UO performance (p < 0.01). For FC, L.VO2max only was included in the stepwise regression model predicting 54% of FC performance (p < 0.01). Sex, age and height were not included in the regression model. The average metabolic cost of UO was 21.4 mL of O2*kg-1*min-1 in female soldiers while wearing PPE.

CONCLUSION

This study showed that modifiable factors such as body composition, PF on IMTP and L.VO2max are key contributors to performance on UO and FC performance.

Individualized Accelerometer Activity Cut-Points for the Measurement of Relative Physical Activity Intensity Levels

Purpose: The aim of this study was to compare the widely used accelerometer activity cut-points derived from the absolute moderate intensity recommendation (3‒6 METs), with relative intensity cut-points according to maximal cardiorespiratory fitness (46%‒63% V˙O2max ) and to individual lactate thresholds (LT1 and LT2) in postmenopausal women. Method: Thirty postmenopausal women performed several exercise tests with measures of heart rate, blood lactate, accelerometer activity counts and oxygen consumption. Individual regressions were developed to derive the accelerometer activity counts at absolute and relative moderate intensity recommendations and at individual LTs. Results: The activity counts calculated at the lower moderate intensity boundary were lower for the absolute 3 METs threshold (2026 ± 808 ct·min^-1) compared to relative 46 % V˙O2max intensity threshold (p < .01, ES: 1.95) and LT1 (p < .01, ES: 2.27), which corresponded to 4.6 ± 0.7 METs. The activity counts at the upper moderate intensity boundary were higher for LT2 (7249 ± 2499 ct·min^-1) compared to the absolute 6 METs threshold (p < .01, ES: 0.72) and relative 63% V˙O2max intensity threshold (p < .01, ES: 0.55). The interindividual variability in activity counts at relative intensity thresholds was high (CV = 30-34%), and was largely explained by cardiorespiratory fitness level (R² = ~ 50%). Conclusion: Individually tailored (relative to V˙O2max or submaximal LTs) rather than fixed accelerometer intensity cut-points derived from the classic absolute moderate physical activity intensity (3-6 METs) would result in a more accurate measurement of an individual´s activity levels and reduce the risk of overestimating or underestimating physical activity.

Metabolic Costs of Standing and Walking in Healthy Military-Age Adults: A Meta-regression

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). 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) was 1.44 + 1.94S + 0.24S. The economical speed for level walking was 1.39 m·s (~ 3.1 mph). The LCDA walking equation was more precise across all walking speeds (bias ± SD, 0.01 ± 0.33 W·kg) 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 in healthy, military-age adults. The LCDA walking equation avoids the errors estimated by other equations at lower and higher walking speeds.

Objectively measured absolute and relative physical activity intensity levels in postmenopausal women

OBJECTIVES

To investigate how objectively measured physical activity (PA) levels differ according to absolute moderate intensity recommendation (3-6 METs) and relative to individual lactate thresholds (LT1 and LT2), and to verify if high-fit women record higher PA levels compared to women with lower aerobic fitness.

METHODS

Seventy-five postmenopausal women performed an incremental exercise test and several constant-velocity tests wearing an accelerometer to identify the activity counts (ct min^-1) corresponding to LT1 and LT2. Individual linear regression determined activity counts cut-points for each intensity: (1) sedentary (<200 ct min^-1), (2) light (from 200 ct min^-1 to ct min^-1 at LT1), (3) moderate (ct min^-1 between LT1 and LT2) and (4) vigorous (ct min^-1> LT2). Participants then wore an accelerometer during a week to measure the time spent at each PA intensity level.

RESULTS

According to absolute intensity categorisation, high-fit postmenopausal women recorded twice as much time at moderate-to-vigorous PA (MVPA) (P < 0.01) than low-fit women. However, when PA intensity was calculated relative to individual lactate thresholds, MVPA was significantly reduced by half (P < 0.01) and the data revealed no differences (P = 0.62) between groups (∼20 min day^-1 at MVPA).

CONCLUSIONS

Accelerometer cut-points derived from absolute moderate-intensity recommendations overestimated MVPA. Similar time at MVPA was recorded by high- and low-fit postmenopausal women when the cut-points were tailored to individual lactate thresholds. A more accurate estimation of PA behaviour could be provided with the use of individually tailored accelerometer cut-points.

Walking economy is predictably determined by speed, grade, and gravitational load

The metabolic energy that human walking requires can vary by more than 10-fold, depending on the speed, surface gradient, and load carried. Although the mechanical factors determining economy are generally considered to be numerous and complex, we tested a minimum mechanics hypothesis that only three variables are needed for broad, accurate prediction: speed, surface grade, and total gravitational load. We first measured steady-state rates of oxygen uptake in 20 healthy adult subjects during unloaded treadmill trials from 0.4 to 1.6 m/s on six gradients: −6, −3, 0, 3, 6, and 9°. Next, we tested a second set of 20 subjects under three torso-loading conditions (no-load, +18, and +31% body weight) at speeds from 0.6 to 1.4 m/s on the same six gradients. Metabolic rates spanned a 14-fold range from supine rest to the greatest single-trial walking mean (3.1 ± 0.1 to 43.3 ± 0.5 ml O2·kg-body−1·min−1, respectively). As theorized, the walking portion (V̇o2-walk =  V̇o2-gross – V̇o2-supine-rest) of the body’s gross metabolic rate increased in direct proportion to load and largely in accordance with support force requirements across both speed and grade. Consequently, a single minimum-mechanics equation was derived from the data of 10 unloaded-condition subjects to predict the pooled mass-specific economy (V̇o2-gross, ml O2·kg-body + load−1·min−1) of all the remaining loaded and unloaded trials combined ( n = 1,412 trials from 90 speed/grade/load conditions). The accuracy of prediction achieved ( r2 = 0.99, SEE = 1.06 ml O2·kg−1·min−1) leads us to conclude that human walking economy is predictably determined by the minimum mechanical requirements present across a broad range of conditions.

NEW & NOTEWORTHY Introduced is a “minimum mechanics” model that predicts human walking economy across a broad range of conditions from only three variables: speed, surface grade, and body-plus-load mass. The derivation/validation data set includes steady-state loaded and unloaded walking trials ( n = 3,414) that span a fourfold range of walking speeds on each of six different surface gradients (−6 to +9°). The accuracy of our minimum mechanics model ( r2 = 0.99; SEE = 1.06 ml O2·kg−1·min−1) appreciably exceeds that of currently used standards.

Predicting metabolic rate during level and uphill outdoor walking using a low-cost GPS receiver

The objective of this study was to assess the accuracy of using speed and grade data obtained from a low-cost global positioning system (GPS) receiver to estimate metabolic rate (MR) during level and uphill outdoor walking. Thirty young, healthy adults performed randomized outdoor walking for 6-min periods at 2.0, 3.5, and 5.0 km/h and on three different grades: 1) level walking, 2) uphill walking on a 3.7% mean grade, and 3) uphill walking on a 10.8% mean grade. The reference MR [metabolic equivalents (METs) and oxygen uptake (V̇o2)] values were obtained using a portable metabolic system. The speed and grade were obtained using a low-cost GPS receiver (1-Hz recording). The GPS grade (Δ altitude/distance walked) was calculated using both uncorrected GPS altitude data and GPS altitude data corrected with map projection software. The accuracy of predictions using reference speed and grade (actual[SPEED/GRADE]) data was high [R(2) = 0.85, root-mean-square error (RMSE) = 0.68 MET]. The accuracy decreased when GPS speed and uncorrected grade (GPS[UNCORRECTED]) data were used, although it remained substantial (R(2) = 0.66, RMSE = 1.00 MET). The accuracy was greatly improved when the GPS speed and corrected grade (GPS[CORRECTED]) data were used (R(2) = 0.82, RMSE = 0.79 MET). Published predictive equations for walking MR were also cross-validated using actual or GPS speed and grade data when appropriate. The prediction accuracy was very close when either actual[SPEED/GRADE] values or GPS[CORRECTED] values (for level and uphill combined) or GPS speed values (for level walking only) were used. These results offer promising research and clinical applications related to the assessment of energy expenditure during free-living walking.

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

Accurate prediction of the metabolic energy that walking requires can inform numerous health, bodily status, and fitness outcomes. We adopted a two-step approach to identifying a concise, generalized equation for predicting level human walking metabolism. Using literature-aggregated values we compared 1) the predictive accuracy of three literature equations: American College of Sports Medicine (ACSM), Pandolf et al., and Height-Weight-Speed (HWS); 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 to 1.9 m/s) 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 (V̇o2 rest) were determined using standardized equations. Our first finding was that the ACSM and Pandolf et al. equations underpredicted nearly all 127 literature-aggregated values. Consequently, their standard errors of estimate (SEE) were nearly four times greater than those of the HWS equation (4.51 and 4.39 vs. 1.13 ml 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 V̇o2-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 ml O2·kg(-1)·min(-1)). Our final analysis identified the following concise, generalized equation for predicting level human walking metabolism: V̇o2 total = V̇o2 rest + 3.85 + 5.97·V(2)/Ht (where V is measured in m/s, Ht in meters, and V̇o2 in ml O2·kg(-1)·min(-1)).

Energy expenditure during common sitting and standing tasks: examining the 1.5 MET definition of sedentary behaviour

Background

Sedentary behavior is defined as any waking behavior characterized by an energy expenditure of 1.5 METS or less while in a sitting or reclining posture. This study examines this definition by assessing the energy cost (METs) of common sitting, standing and walking tasks.

Methods

Fifty one adults spent 10 min during each activity in a variety of sitting tasks (watching TV, Playing on the Wii, Playing on the PlayStation Portable (PSP) and typing) and non-sedentary tasks (standing still, walking at 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, and 1.6 mph). Activities were completed on the same day in a random order following an assessment of resting metabolic rate (RMR). A portable gas analyzer was used to measure oxygen uptake, and data were converted to units of energy expenditure (METs).

Results

Average of standardized MET values for screen-based sitting tasks were: 1.33 (SD: 0.24) METS (TV), 1.41 (SD: 0.28) (PSP), and 1.45 (SD: 0.32) (Typing). The more active, yet still seated, games on the Wii yielded an average of 2.06 (SD: 0.5) METS. Standing still yielded an average of 1.59 (SD: 0.37) METs. Walking MET values increased incrementally with speed from 2.17 to 2.99 (SD: 0.5 - 0.69) METs.

Conclusions

The suggested 1.5 MET threshold for sedentary behaviors seems reasonable however some sitting based activities may be classified as non-sedentary. The effect of this on the definition of sedentary behavior and associations with metabolic health needs further investigation.