INTRODUCTION Many subjective factors can affect energy cost (V’O2max, ; maximal strength and flexibility, ) and mechanical work (stride frequency, ) 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 (2×3) 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 . It is well established that a U-shaped relationship between NetEC and walking speed exists . 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  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 . 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.