Estimation of Energy Expenditure with Two Different Footwear’s in Normal Healthy Females (original) (raw)
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Impact of Alternative Footwear on Human Energy Expenditure
Medicine & Science in Sports & Exercise, 2017
Purpose: Use of alternative footwear options such as flip-flop style sandals and minimalist athletic shoes are becoming increasingly popular footwear choices. The purpose of the investigation was to analyze the energy expenditure and oxygen consumption requirements of walking at preferred pace while wearing flip-flops, slipon style shoes, and minimalist athletic shoes. Methods: Eighteen healthy male adults participated in this study. In addition to an initial familiarization session, participants were tested in three different footwear conditions [thong-style flip-flops (FF), Croc® slip on shoes (CROC), and Vibram Fivefingers® minimalist shoes (MIN)]. Then after a brief warm-up, participants walked a one-mile distance at their preferred pace. Immediately following completion of the one-mile walk, participants stood quietly on the treadmill for an additional period to assess excess post-exercise oxygen consumption (EPOC). Results: A repeatedmeasures ANOVA that the following variables did not show evidence of a significant differently value between conditions: preferred pace (p = 0.392), average oxygen consumption (p = 0.804), energy expenditure per mile (p = 0.306), or EPOC (p = 0.088). There was shown to be a significantly higher RER during exercise in CROC compared to MIN (p = 0.031) with no significant differences observed when comparing CROC to FF (p = 0.106) or FF to MIN (p = 0.827). Conclusion: Based on the results of the current study, it appears that the alternative footwear selected for evaluation do not lead to a substantial alteration of walking pace or
Comparison of Energy Expenditure during Walking between Female Athletes and Non-Athletes
Asian Social Science, 2013
This study aimed to determine, if there is a difference in energy expenditure during walking among athletes and non-athletes at two different speeds of walking. Ninety five healthy female students (47 athletes and 48 non-athletes) with a mean age of 22.4 (±1.6) years purposively participated in this study. Medical and sport participation history of the subjects was acquired through a questionnaire. Two experimental tests including anthropometric measurements,V O , and walking tests on treadmill at speeds of 3.00 and 3.5 mph were conducted. Results showed no difference in weight, height, body mass index, and leg length between both groups. The non-athletes expended a greater amount of energy than athletes (3.78±.1 and 2.95±.6 kcal.min-1 , respectively) at both speeds of 3.00mph and 3.5mph (4.89±1 and 3.94±.7 kcal.min-1). Based on energy requirements for walking at similar weights and speeds by ACSM's guideline, the female athletes walked at a slow, moderate and brisk pace. Most of the female non-athletes walked at a moderate, brisk and very brisk pace. This study revealed that regular exercise could improve walking efficiency, and the energy expenditure of walking would play an important role in the information processing for total energy requirement that progressively affects weight management and health.
Field evaluation of energy expenditure from continuous and intermittent walking in women
Medicine and Science in Sports and Exercise, 2001
Rationale: Recent physical activity recommendations suggest that comparable amounts of prescribed physical activity, done as a single continuous bout or as a set of intermittent bouts, will produce equal amounts of energy expenditure (EE) during the prescribed activity as well as throughout the day. Hypotheses: In a field setting, we tested two hypotheses: (1) continuous and intermittent walking conditions will result in significantly greater total daily EE than a control condition, and (2) continuous and intermittent walking conditions will result in similar total daily Methods:. Thirty women (mean age [yr] ϭ 43.7 Ϯ 5.8; mean body mass index [kg⅐m-2 ]ϭ 24.7 Ϯ 4.0) participated in a repeated-measures design so that each woman participated in three walking conditions on successive days of the week: a single 30-min brisk walk (continuous); three 10-min brisk walks (intermittent); and no activity (control). Throughout the study protocol, women wore a TRITRAC-R3D accelerometer programmed to estimate EE in 2-min intervals. Results: Mean total EE estimates (kcal) for the three walking conditions were as follows: continuous: 2181 Ϯ 308; intermittent: 2121 Ϯ 305; and control: 1948 Ϯ 270. A repeated-measures analysis of variance omnibus test indicated that EE differed significantly by experimental condition [F(2,58) ϭ 40.2, P Ͻ 0.001]. To test the first hypothesis, contrasts were examined revealing that EE in the continuous and intermittent conditions was significantly greater than EE in the control condition [F(1,29) ϭ 58.2, P Ͻ 0.001]. To test the second hypothesis, contrasts revealed that EE in the continuous condition was significantly greater than EE in the intermittent condition [F(1,29) ϭ 7.0, P ϭ 0.013]. Conclusion: For the purposes of total EE, selecting a continuous mode of walking may offer additional benefit over an intermittent mode, given the same total prescribed duration.
Validation of a method for estimating energy expenditure during walking in middle-aged adults
European Journal of Applied Physiology, 2017
The aim of this study was to test the validity of a method using an inertial measurement unit for estimating activityrelated energy expenditure (AEE) during walking in middle-aged adults. Methods Twenty healthy middle-aged participants completed different treadmill walking trials with an inertial measurement unit adhered to their lower back. Gas exchange was monitored with indirect calorimetry. Mechanical data were used to estimate AEE from an algorithm developed by Bouten et al. (Med Sci Sport Exer 26(12):1516-1523, 1994). Three methods for removing the gravitational component were proposed and tested: mean subtraction method (MSM), high-pass filter method (HPM) and free acceleration method (FAM). Results The three methods did not differ significantly from the indirect calorimetry [bias = − 0.08 kcal min −1 ; p = 0.47 (MSM), bias = − 0.08 kcal min −1 ; p = 0.48 (HPM) and bias = − 0.15 kcal min −1 ; p = 0.23 (FAM)]. Mean root mean square errors were 0.43, 0.42 and 0.51 kcal min −1 for MSM, HPM and FAM, respectively. Conclusion This study proposed an accurate method for estimating AEE in middle-aged adults for a large range of walking intensities, from slow to brisk walking, based on Bouten's algorithm.
Effects of Walking in High Heeled Shoes on Oxygen Consumption and Energy Expenditure in Young Women
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Odebiyi DO, Ajiboye EO, Jaja SI. Effects of Walking in High Heeled Shoes on Oxygen Consumption and Energy Expenditure in Young Women. JEPonline 2011;14(6):20-28. O xygen consumption and energy expenditure have been studied in various aspects of life. However, studies involving the determination of oxygen consumption and energy expenditure during walking in high heeled shoes of various heights have not been fully studied. This study was designed to determine oxygen consumption and energy expenditure while walking barefooted and in shoes of different heel heights. The subjects consisted of 20 female student s (age 22 to 26 yrs) from the College of Medicine at the University of Lagos. The cardiovascular parameters, oxygen consumption, and energy expenditure were determined while walking barefooted and in 2, 4 , and 6-inch high heeled shoes. Paired t-test showed that there was a significant difference (P<0.05) in the cardiovascular and metabolic parameters of the subjects between walking barefooted and in shoes with heel heights of 2, 4 and 6 inches, respectively. The effects of walking on the parameters increased with the increase in heel heights. However, there was no significant difference (P>0.05) within the groups. Walking in high heeled shoes required more effort and overloaded the activity of the respiratory muscles than when walking barefooted. It appears that the higher the heel heights, the greater the effort required for walking. When it is necessary to be in high heeled shoes, the low heeled shoes are recommended.
Journal of Physical Activity and Health, 2011
Background:The purposes of this study were to determine the accuracy and reliability of step counts and energy expenditure as estimated by a pedometer during treadmill walking and to clarify the relationship between step counts and current physical activity recommendations.Methods:One hundred males (n = 50) and females (n = 50) walked at stride frequencies (SF) of 80, 90, 100, 110, and 120 steps/min, during which time step counts and energy expenditure were estimated with a Walk4Life Elite pedometer.Results:The pedometer accurately measured step counts at SFs of 100, 110, and 120 steps/min, but not 80 and 90 steps/min. Compared with energy expenditure as measured by a metabolic cart, the pedometer significantly underestimated energy expenditure at 80 steps/min and significantly overestimated measured energy expenditure at 90, 100, 110, and 120 steps/ min.Conclusions:The pedometers’ inability to accurately estimate energy expenditure cannot be attributed to stride length entered into...
Energy expenditure estimates of the Caltrac accelerometer for running, race walking, and stepping
British Journal of Sports Medicine, 1997
Objective-To examine the accuracy of the Caltrac accelerometer for estimating energy expenditure (EE) during three exercise modes. Methods-A subset of 31 women (mean (SEM) age 22.6 (5) years) was selected from a training study comparing various physiological parameters during race walking, running, and stepping. Subjects each performed mode specific graded exercise tests to peak Vo2. Regression equations for Vo2 v heart rate (HR) were generated from each individual's test data. EE (kcal and kJ) was estimated for each Vo2 value based on the respiratory exchange ratio, and kcal v HR regression equations were generated to predict EE from each subject's HR data (EE-HR). HR in the field was monitored by telemetry, and two Caltrac monitors, one set for EE and one to give counts, were attached to a belt over opposite hips. Results-EE-HR was not significantly different across exercise modes. Caltrac overestimated EE (P<0.01) in runners (14%) and walkers (19%) but underestimated EE in steppers by about 10% (P = 0.12). Conclusions-The Caltrac is a reliable instrument but it did not accurately distinguish EE in running, race walking, or stepping in a group of young women.
Energy expenditure of walking at different intensities in Brazilian college women
Clinical Nutrition, 2008
Background: Current recommendations state that all subjects should engage in at least 30 min of moderate intensity physical activity assuming an extra energy expenditure (EE) of 836 kJ. Aims: To determine the EE of walking at different intensities, to check whether the EE of walking could be estimated by intensity codes and to determine the time necessary to expend 836 kJ while walking. Methods: Resting and walking EE in a treadmill (67/0; 93.8/0; and 93.8 m min À1 /2.5% slope) were measured by indirect calorimetry in 58 healthy college-aged women. Walking EE was compared (paired Student t-tests) with estimated EE using the physical activity ratio values from FAO/WHO/UNU and the MET codes published in the Compendium of Physical Activities. Results: Average EE increased from 12.1 (1.9) to 18.6 (2.9) kJ min À1 or 3.5 (0.5) to 5.4 (0.7) kJ min À1 multiples of measured MET. Walking EE at the two first intensities could be correctly estimated by the MET codes but according to age-dependent classification walking could only be considered moderate at the highest intensity. For the extra amount of 836 kJ these women would have to walk for at least 46 min at the highest intensity. Conclusions: EE of walking at ground level can be accurately estimated by MET codes but it is necessary to walk much longer than 30 min to reach the recommended level of EE for good health in college-aged Brazilian women.
Energy Expenditure of Walking and Running: Comparison with Prediction Equations
Medicine and Science in Sports and Exercise, 2004
Purpose: This study established the published prediction equations for the energy expenditure of walking and running compared with the measured values. To make this comparison we first determined whether differences exist in energy expenditure for 1600 m of walking versus running, and whether energy expenditure differences occur due to being on the track or treadmill. Methods: Energy was measured via indirect calorimetry in 24 subjects while walking (1.41 m·s Ϫ1 ) and running (2.82 m·s Ϫ1 ) 1600 m on the treadmill. A subgroup also performed the 1600-m run/walk on the track. The measured energy expenditures were compared with published prediction equations. Results: Running required more energy (P Ͻ 0.01) for 1600 m than walking (treadmill: running 481 Ϯ 20.0 kJ, walking 340 Ϯ 14 kJ; track: running 480 Ϯ 23 kJ, walking 334 Ϯ 14 kJ) on both the track and treadmill. Predictions using the ACSM or Léger equations for running, and the Pandolf equation for walking, were similar to the actual energy expenditures for running and walking (total error: ACSM: Ϫ20 and 14.4 kJ, respectively; Légers walking: Ϫ10.1 kJ; Pandolf walking: Ϫ10.0 kJ). An overestimation (P Ͻ 0.01) for 1600 m was found with the McArdle's table for walking and running energy expenditure and with van der Walt's prediction for walking energy expenditure, whereas the Epstein equation underestimated running energy expenditure (P Ͻ 0.01). Conclusion: Running has a greater energy cost than walking on both the track and treadmill. For running, the Léger equation and ACSM prediction model appear to be the most suitable for the prediction of running energy expenditure. The ACSM and Pandolf prediction equation also closely predict walking energy expenditure, whereas the McArdle's table or the equations by Epstein and van der Walt were not as strong predictors of energy expenditure.
Estimation of the gait energy expenditure *
2008
The aims of this study were: 1) to propose predictive equations for gait energy expenditure (GEE) of young individuals in three situations: a) when the identification of the gait velocity is possible; b) when heart rate (HR) monitoring is possible; and c) when neither the velocity identification nor the HR monitoring is possible; and 2) to validate the GEE made by the HR Polar M71® monitor. Thirty individuals (16 males, 22.7 ± 2.6 years and 14 female, 22.1 ± 2.1 years), non-athletes, physical education students were instructed to walk on the treadmill with 1% inclination, in self-selected low, moderate and high intensity velocities, during 6 minutes in each velocity. The VO2, measured by the Aerosport Metabolic Analyzer Teem 100, HR and GEE estimated by the monitor, were registered in the last 2 minutes of each load. It was concluded that the best GEE prediction is done with the use of the gait velocity and the individual’s body weight. HR for prediction of GEE should be accompanied...