The aims of this study were: to compare energy expenditure (EE) estimated from the existing GT3X accelerometer equations and EE measured with indirect calorimetry; to define new equations for EE estimation with the GT3X in youth, adults and older people; and to define GT3X vector magnitude (VM) cut points allowing to classify PA intensity in the aforementioned age-groups. The study comprised 31 youth, 31 adults and 35 older people. Participants wore the GT3X (setup: 1-s epoch) over their right hip during 6 conditions of 10-min duration each: resting, treadmill walking/running at 3,?5,?7, and 9?km???h?1, and repeated sit-stands (30?times???min?1). The GT3X proved to be a good tool to predict EE in youth and adults (able to discriminate between the aforementioned conditions), but not in the elderly. We defined the following equations: for all age-groups combined, EE (METs)=2.7406+0.00056???VM activity counts (counts???min?1)?0.008542???age (years)?0.01380??? body mass (kg); for youth, METs=1.546618+0.000658???VM activity counts (counts???min?1); for adults, METs=2.8323+0.00054???VM activity counts (counts???min?1)?0.059123???body mass (kg)+1.4410???gender (women=1, men=2); and for the elderly, METs=2.5878+0.00047???VM activity counts (counts???min?1)?0.6453???gender (women=1, men=2). Activity counts derived from the VM yielded a more accurate EE estimation than those derived from the Y-axis. The GT3X represents a step forward in triaxial technology estimating EE. However, age-specific equations must be used to ensure the correct use of this device.

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Menopausal women may benefit from physical exercise, which attenuates the effects of the physiological and psychological changes associated with the menopause and prevents pathologic changes.

The main purpose of this study was to assess the inter-monitor reliability of the tri-axial GT3X Actigraph accelerometer over a range of physical activities (PA). This device collects motion data on each of the vertical (Y), horizontal right-left (X), and horizontal front-back (Z) axes and also calculates the vector summed value √X(2)+Y(2)+Z(2) known as 'vector magnitude' (VM). 8 GT3X accelerometers were worn at the same time by the same participant. Accelerometers were placed back-to-front, all facing forward and in sets of 4 securely taped together, attached to a belt and allocating each block above either left or right hip at waist level. Inter-monitor reliability was assessed during 6 conditions: rest, walking (4 and 6 km·h(-1)), running (8 and 10 km·h(-1)) and repeated sit-to-stand (40 times·min(-1)). The intra-class correlation coefficients were high for X, Y and Z axes (i.e., all ≥ 0.925) and for VM (≥ 0.946). In conclusion, we found good inter-instrument reliability of the GT3X accelerometer across all planes, yet our results also suggest that the X and Z axes do not provide further benefits over the 'traditional' Y-axis to assess the movement in typical PA.

Judo competition is characterized structurally by weight category, which raises the importance of physiological control training in judo. The aim of the present review was to examine scientific papers on the physiological profile of the judokas, maintenance or loss of weight, framing issues, such as anthropometric parameters (body fat percentage), heart rate responses to training and combat, maximal oxygen uptake, hematological, biological and hormones indicators. The values shown in this review should be used as a reference for the evaluation of physical fitness and the effectiveness of training programs. Hence, this information is expected to contribute to the development of optimal training interventions aiming to achieve maximum athletic performance and to maintain the health of judokas.

The aim of the present study was to determine statistical differences in a set of badminton competition matches in five different modalities with regard to competition level (Group Phase vs. Eliminatory Phase). Data from 453 sets (125 in men’s singles; 108 sets in women’s singles; 77 sets in men’s doubles; 73 in women’s doubles and 70 in mixed doubles) from the RIO 2016 Olympics Games were recorded and classified in two groups of variables to analyze variables related to match (5) and set (15). A descriptive analysis and univariate test (Mann–Whitney U) for non-parametric data were conducted. The results show in men’s and women’s singles all the variables related to match were higher in the Elimination Phase than in the Group Phase ( p < 0.01). In Sets 1 and 3, the longest set duration, rally and average rally were found in the Elimination Phase than Group Stage ( p < 0.05). In women’s singles, these differences were also recorded in Set 2. For doubles, the results are more stable among groups. Men’s doubles had a longer duration of the match and set (sets 1 and set 2) ( p < 0.01), and also scored highest for average rally strokes (sets 1 3) ( p < 0.05) and shuttles used in the Elimination Phase vs. the Group Phase along the match ( p < 0.01). In women’s doubles, more shuttles were used in a match in the Elimination than in the Group Phase. Moreover, the same results are established for Set 2, including for average rally. Mixed doubles saw no match going to three sets. However, the greatest differences showed a longer rally and average rally being registered in the Elimination than in the Group Phase. In conclusion, the timing factors of the badminton singles and doubles games were different in the Elimination and Group Phases. This information may help players and coaches prepare and administer different types of workouts or, more specifically, competition schedules adapted to the characteristics of modern badminton.

We studied the single and combined influence of the ACE I/D and the ACTN3 R577X polymorphisms on muscle phenotypes (thigh muscles' cross-sectional area assessed with magnetic resonance imaging) and strength (maximal handgrip, 30-s chair stand test), functional ability during activities of daily living (Barthel index) and bone mineral density (proximal femur) in Caucasian (Spanish) community-dwelling old people [n = 81, 59 women; mean age 82.8 ± 4.8 years (range 71-93 years)]. We found no significantly differences in the aforementioned phenotypes across ACE and ACTN3 genotypes (all P > 0.05), except for handgrip in the ACE I/D recessive model (DD 19.5 ± 6.7 kg, ID 24.0 ± 9.1 kg, II 22.1 ± 7.9; P = 0.047), yet statistical significance disappeared after correction for multiple comparisons. Likewise, the analyses of the combined effects between genotypes did not yield any significant difference (all P > 0.05) between the two 'extreme' genotypes [theoretically 'power or muscularity oriented' [(ACTN3 RR + RX & ACE DD) versus 'non-power' (ACTN3 XX & ACE II + ID)]. The aforementioned analyses were adjusted by sex, age and physical activity levels as covariates. Logistic regression analysis revealed no significant association of single or combined effect of ACE and ACTN3 genotypes or genotype combination group (ACE + ACTN3) with sarcopenia (i.e. being in the lowest 25th sex-specific percentile for a combined score of the muscle and functional phenotypes we measured). Though ACE I/D and ACTN3 R577X polymorphisms are candidates to modulate exercise-related phenotypes in adults, our data suggest that they do not exert a major influence in the muscle phenotypes of old people. More studies with larger sample sizes are needed.