Gait variability can be considered an indirect measure of gait stability, in particular regarding temporal or spatial variability assessment. Physical activity, such as walking, is advised for the elderly and can be improved by gait stability. The aim of this study was to investigate the associations between gait stability and physical activity in women of different age ranges. Forty-two healthy women of different age ranges (18-40 yrs. and 65-75 yrs.) were recruited in the study. To assess physical activity, the subjects wore a multi-sensor activity monitor for a whole week, inferring the time spent in moderate to vigorous physical activity (MVPA). MVPA were analysed in bouts of at least 10 subsequent minutes (MVPAbouts) and in overall minutes (MVPAtot). A kinematic analysis was performed with an optoelectronic system to calculate gait variability - expressed as standard deviation (SD) and coefficient of variability (CV) of step width, stride length, stance and swing time (during treadmill walking at different speeds). Elderly women, with high walking speed (5 km/h), and moderate step width variability (CV = 8–27%), met the recommended levels of physical activity (MVPAtot and MVPAbouts). Furthermore, gait variability, adjusted for age and number of falls, was significantly and negatively associated with MVPAtot only at 3.5 km/h, and with MVPAbouts only at 4 km/h. In a population of healthy elderly women, gait variability was significantly and negatively associated with the level of physical activity. Healthy elderly women, with moderate gait variability (step width variability), and high preferred walking speed, seem to be able to meet the recommended levels of physical activity.

Background: Exercise has beneficial effects on older adults, but controversy surrounds the purported “compensatory effects” that training may have on total daily physical activity and energy expenditure in the elderly. We wanted to determine whether 8 weeks of high-intensity interval training (HIIT) induced such effects on physical activity and energy expenditure in healthy, active older adult men. Methods: Twenty-four healthy elderly male volunteers were randomized to two groups. The experimental group performed HIIT (7 × 2 min cycling repetitions, 3 d/w); the control group performed continuous moderate-intensity training (20–30 min cycling, 3 d/w). Physical activity and energy expenditure were measured with a multisensor activity monitor SenseWear Armband Mini. Results: During HIIT, significant changes were observed in moderate and vigorous physical activity, average daily metabolic equivalents (METs), physical activity level, and activity energy expenditure (p < 0.05) but not in total energy expenditure. Sleep and sedentary time, and levels of light physical activity remained constant during the training period. Conclusions: The findings suggest that HIIT induced no compensatory effect: HIIT does not adversely affect lifestyle, as it does not reduce daily energy expenditure and/or increase sedentary time.

Irisin is an exercise-induced cytokine mainly secreted by myocytes. Circulating level of irisin can increase in response to acute exercise, promoting pleiotropic effects on health. Generally, irisin is evaluated in blood, however, its collection is invasive. Saliva sample would not have any risk associated with blood collection and would represent a less invasive method for irisin detection. Until now, there are only a few studies that have analyzed irisin levels in saliva. In the present research, five healthy male adults performed an incremental exercise until exhaustion on cycle ergometer. Serum and saliva samples were collected before exercise and 15min, 24h and 48h after reaching the exhaustion. Irisin was detected by ELISA assay. Serum and salivary irisin levels increased from baseline to 24h post exercise and reverted to basal levels after 48h of rest. A significant rise of both serum and salivary irisin level at 24h (p≤0.05) compared to baseline levels was found. Furthermore, a significant correlation between irisin percentage change in serum and saliva from baseline to 24h post exercise was detected (r=0.92, p<0.05). Despite the relatively limited sample, this research suggests that collecting saliva samples might represent a valid and less invasive method to detect irisin level changes induced by exercise.

Athletic performance is influenced by many factors such as the environment, diet, training and endurance or speed in physical effort and by genetic predisposition. Just a few studies have analyzed the impact of genotypes on physical performance in rugby. The aim of this study was to verify the modulation of genetic influence on rugby-specific physical performance. Twenty-seven elite rugby union players were involved in the study during the in-season phase. Molecular genotyping was performed for: angiotensin-converting enzyme (ACE rs4646994), alfa-actinin-3 (ACTN3 rs1815739) and monocarboxylate transporter 1 (MCT1 rs1049434) and their variants. Lean mass index (from skinfolds), lower-limb explosive power (countermovement jump), agility (505), speed (20 m), maximal aerobic power (Yo-yo intermittent recovery test level 1) and repeated sprint ability (12 × 20 m) were evaluated. In our rugby union players ACE and ACTN3 variants did not show any influence on athletic performance. MCT1 analysis showed that TT-variant players had the highest peak vertical power (p = 0.037) while the ones with the AA genotype were the fastest in both agility and sprint tests (p = 0.006 and p = 0.012, respectively). Considering the T-dominant model, the AA genotype remains the fastest in both tests (agility: p = 0.013, speed: p = 0.017). Only the MCT1 rs1049434 A allele seems to be advantageous for elite rugby union players, particularly when power and speed are required.