INTRODUCTION Many subjective factors can affect energy cost (V’O2max, [7]; maximal strength and flexibility, [3]) and mechanical work (stride frequency, [6]) of walking. To our knowledge, no studies have been conducted to investigate if the level of daily physical activity (PAL) can affect external mechanical work (WEXT) and net energy cost (NetEC) of treadmill walking. The aim of the study was to analyse the relation between NetEC and WEXT with PAL. 2. MATERIALS AND METHODS 20 healthy adults were recruited in the study and were classified as inactive (INACT) and active (ACT) according to the amount of daily moderate and vigorous physical activity (MVPA). Main characteristics are summarized in Table 1. NetEC (obtained from GrossEC– Standing metabolic rate) was analysed with indirect calorimetry (K4b2, Cosmed, Italy) and simultaneously, a kinematic analysis was performed with an optoelectronic system (SMART-E, BTS, Italy) to calculate WEXT during 3 bouts of treadmill walking of 10 min each at 0.97/1.25/1.53 m/s. To assess PAL, subjects wore an activity monitor (Actiheart, CamNtech, UK) for a whole week, inferring time spent in sedentary (SED, <1.5 METs), or moderate to vigorous (MVPA, >3 METs) physical activity. Statistical Analysis: One-way ANOVA was performed to evaluate differences between ACT and INACT. A repeated measure ANOVA (2x3) was used to determine differences between velocities. An ANCOVA analysis was made to find out associations between NetEC and WEXT with PAL. The correlation analysis was performed to investigate relationships between variables. Significance was set at p<0.05. 3. RESULTS When compared with INACT, ACT had a significantly higher amount of MVPA (P<0,0001). No group differences were observed for SED behaviour (Table 2).NetEC increased significantly at all velocities, except for speed from 0.97 to 1.25 m/s. On the contrary, WEXT decreased significantly when velocities grow up, excluding speed from 1.25 to 1.53 m/s (Fig.1-2).No significant associations were found between MVPA or SED with neither NetEC nor WEXT. Significant correlations between NetEC or WEXT calculated at the different speeds were found (r>0.583; p<0.01; Table 3).DISCUSSION Our data indicate that ACT and INACT adults differ for MVPA but not for SED patterns. For both groups it is extremely important to reduce SED behaviour regardless of performed activities in order to prevent cardiovascular diseases [1]. It is well established that a U-shaped relationship between NetEC and walking speed exists [4]. Our values are substantially in agreement with literature [5;8], even if the U-shaped trend is not visible, probably due to the different number of tested speeds (we have only 3 speeds vs. 4-6 of literature). In addition, different treadmills, metabolic charts and ways to calculate resting metabolic rate may partially explain the variability in the trends. Reference [2] showed that WEXT reaches a minimum at a speed near the preferred walking speed: before and after this threshold, WEXT increases. The absence of significance between 1.25 and 1.53 m/s indicates that our minimum value may be positioned around these speeds. Probably, adding a higher velocity, closer to the preferred walking speed of our subjects, an increase in the values will appear. The absence of associations may be explained by a small sample size and speeds eliciting a V’O2 corresponding to very light/ light activity intensities [1]. Significant correlations between NetEC or WEXT at the three different speeds suggest that subjects motor patterns during walking persist even with increasing speeds. In conclusion, neither SED nor MVPA seem to influence NetEC and WEXT of light intensity treadmill walking in a healthy adult population. 5. REFERENCES [1] American College of Sports Medicine, 2011. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exerc, Jul, 43(7), 1334-59. [2] Cavagna G.A.,Thys H., Zamboni A., 1976. The sources of external work in level walking and running. J Physiol, Nov, 262(3), 639-57. [3] Hunter G.R., McCarthy J.P., Bryan D.R., Zuckerman P.A., Bamman M.M., Byrne N.M., 2008. Increased strength and decreased flexibility are related to reduced oxygen cost of walking. Eur J Appl Physiol, Nov, 104(5), 895-901. [4] Margaria R., 1976. Biomechanics and energetics of muscular exercise. Clarendon Press, Oxford, United Kingdom. p.72. [5] Mian O.S., Thom J.M., Ardigò L.P., Narici M.V., Minetti A.E., 2006. Metabolic cost, mechanical work, and efficiency during walking in young and older men. Acta Physiol (Oxf), Feb, 186(2), 127-39. [6] Saibene F., Minetti A.E., 2003. Biomechanical and physiological aspects of legged locomotion in humans. Eur J Appl Physiol, Jan, 88(4-5), 297-316. [7] Sawyer B.J., Blessinger J.R., Irving B.A., Weltman A., Patrie J.T., Gaesser G.A., 2010. Walking and running economy: inverse association with peak oxygen uptake. Med Sci Sports Exerc, Nov, 42(11), 2122-7. [8] Weyand P.G., Smith B.R., Puyau M.R., Butte N.F., 2010. The mass-specific energy cost of human walking is set by stature. J Exp Biol, Dec 1, 213(Pt 23), 3972-9.

Annoni, I., Galvani, C., Mapelli, A., Sidequersky, F., Ripamonti, G., Sforza, C., Can physical activity level affect externalmechanical work or energy cost of treadmillwalking of healthy adults?, Abstract de <<XII International Symposiumon 3D Analysis of Human MovementTechnology & Treatment>>, (Bologna, 18-20 July 2012 ), Alberto Leardini, Rita Stagni, Bologna 2012: 210-212 [http://hdl.handle.net/10807/27884]

Can physical activity level affect external mechanical work or energy cost of treadmill walking of healthy adults?

Annoni, Isabella;Galvani, Christel;Ripamonti, Giorgio;
2012

Abstract

INTRODUCTION Many subjective factors can affect energy cost (V’O2max, [7]; maximal strength and flexibility, [3]) and mechanical work (stride frequency, [6]) of walking. To our knowledge, no studies have been conducted to investigate if the level of daily physical activity (PAL) can affect external mechanical work (WEXT) and net energy cost (NetEC) of treadmill walking. The aim of the study was to analyse the relation between NetEC and WEXT with PAL. 2. MATERIALS AND METHODS 20 healthy adults were recruited in the study and were classified as inactive (INACT) and active (ACT) according to the amount of daily moderate and vigorous physical activity (MVPA). Main characteristics are summarized in Table 1. NetEC (obtained from GrossEC– Standing metabolic rate) was analysed with indirect calorimetry (K4b2, Cosmed, Italy) and simultaneously, a kinematic analysis was performed with an optoelectronic system (SMART-E, BTS, Italy) to calculate WEXT during 3 bouts of treadmill walking of 10 min each at 0.97/1.25/1.53 m/s. To assess PAL, subjects wore an activity monitor (Actiheart, CamNtech, UK) for a whole week, inferring time spent in sedentary (SED, <1.5 METs), or moderate to vigorous (MVPA, >3 METs) physical activity. Statistical Analysis: One-way ANOVA was performed to evaluate differences between ACT and INACT. A repeated measure ANOVA (2x3) was used to determine differences between velocities. An ANCOVA analysis was made to find out associations between NetEC and WEXT with PAL. The correlation analysis was performed to investigate relationships between variables. Significance was set at p<0.05. 3. RESULTS When compared with INACT, ACT had a significantly higher amount of MVPA (P<0,0001). No group differences were observed for SED behaviour (Table 2).NetEC increased significantly at all velocities, except for speed from 0.97 to 1.25 m/s. On the contrary, WEXT decreased significantly when velocities grow up, excluding speed from 1.25 to 1.53 m/s (Fig.1-2).No significant associations were found between MVPA or SED with neither NetEC nor WEXT. Significant correlations between NetEC or WEXT calculated at the different speeds were found (r>0.583; p<0.01; Table 3).DISCUSSION Our data indicate that ACT and INACT adults differ for MVPA but not for SED patterns. For both groups it is extremely important to reduce SED behaviour regardless of performed activities in order to prevent cardiovascular diseases [1]. It is well established that a U-shaped relationship between NetEC and walking speed exists [4]. Our values are substantially in agreement with literature [5;8], even if the U-shaped trend is not visible, probably due to the different number of tested speeds (we have only 3 speeds vs. 4-6 of literature). In addition, different treadmills, metabolic charts and ways to calculate resting metabolic rate may partially explain the variability in the trends. Reference [2] showed that WEXT reaches a minimum at a speed near the preferred walking speed: before and after this threshold, WEXT increases. The absence of significance between 1.25 and 1.53 m/s indicates that our minimum value may be positioned around these speeds. Probably, adding a higher velocity, closer to the preferred walking speed of our subjects, an increase in the values will appear. The absence of associations may be explained by a small sample size and speeds eliciting a V’O2 corresponding to very light/ light activity intensities [1]. Significant correlations between NetEC or WEXT at the three different speeds suggest that subjects motor patterns during walking persist even with increasing speeds. In conclusion, neither SED nor MVPA seem to influence NetEC and WEXT of light intensity treadmill walking in a healthy adult population. 5. REFERENCES [1] American College of Sports Medicine, 2011. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exerc, Jul, 43(7), 1334-59. [2] Cavagna G.A.,Thys H., Zamboni A., 1976. The sources of external work in level walking and running. J Physiol, Nov, 262(3), 639-57. [3] Hunter G.R., McCarthy J.P., Bryan D.R., Zuckerman P.A., Bamman M.M., Byrne N.M., 2008. Increased strength and decreased flexibility are related to reduced oxygen cost of walking. Eur J Appl Physiol, Nov, 104(5), 895-901. [4] Margaria R., 1976. Biomechanics and energetics of muscular exercise. Clarendon Press, Oxford, United Kingdom. p.72. [5] Mian O.S., Thom J.M., Ardigò L.P., Narici M.V., Minetti A.E., 2006. Metabolic cost, mechanical work, and efficiency during walking in young and older men. Acta Physiol (Oxf), Feb, 186(2), 127-39. [6] Saibene F., Minetti A.E., 2003. Biomechanical and physiological aspects of legged locomotion in humans. Eur J Appl Physiol, Jan, 88(4-5), 297-316. [7] Sawyer B.J., Blessinger J.R., Irving B.A., Weltman A., Patrie J.T., Gaesser G.A., 2010. Walking and running economy: inverse association with peak oxygen uptake. Med Sci Sports Exerc, Nov, 42(11), 2122-7. [8] Weyand P.G., Smith B.R., Puyau M.R., Butte N.F., 2010. The mass-specific energy cost of human walking is set by stature. J Exp Biol, Dec 1, 213(Pt 23), 3972-9.
2012
Inglese
Book of Abstracts
XII International Symposium on 3D Analysis of Human Movement Technology & Treatment
Bologna
18-lug-2012
20-lug-2012
N/A
Annoni, I., Galvani, C., Mapelli, A., Sidequersky, F., Ripamonti, G., Sforza, C., Can physical activity level affect externalmechanical work or energy cost of treadmillwalking of healthy adults?, Abstract de <<XII International Symposiumon 3D Analysis of Human MovementTechnology & Treatment>>, (Bologna, 18-20 July 2012 ), Alberto Leardini, Rita Stagni, Bologna 2012: 210-212 [http://hdl.handle.net/10807/27884]
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