Background: Sedentary behaviour (SB) has been identified as an important mortality risk factor. Health organizations have recognised SB as a public health challenge with major health, social, and economic consequences. Researchers have alerted the need to develop specific strategies, to monitor, prevent, and reduce SB. However, there is no systematic analysis of the SB changes in European Union adults. We aimed to examine SB changes between 2002 and 2017 in the European Union (EU) adult population. Methods: SB prevalence (>4h30mins of sitting time/day) of 96,004 adults as a whole sample and country-by-country was analysed in 2002, 2005, 2013, and 2017 of the Sport and Physical Activity EU Special Eurobarometers’ data. The SB question of a modified version of the International Physical Activity Questionnaire was considered. SB prevalence between countries and within years was analysed with a χ2 test, and SB between genders was analysed with the Z-Score test for two population proportions. Results: An association between the SB prevalence and the years was found (p < 0.001), with increases for the whole sample (2002: 49.3%, 48.5–50.0 95% confidence interval (CI); 2017: 54.5%, 53.9–55.0 95% CI) and men (2002: 51.2%, 50.0–52.4 95% CI; 2017: 55.8%, 55.0–56.7 95% CI) and women (2002: 47.6%, 46.6–48.7 95% CI; 2017: 53.4%, 52.6–54.1 95% CI) separately. The adjusted standardised residuals showed an increase in the observed prevalence versus the expected during 2013 and 2017 for the whole sample and women and during 2017 for men. For all years, differences were observed in the SB prevalence between countries for the whole sample, and men and women separately (p < 0.001). Besides, the SB prevalence was always higher in men versus women in the overall EU sample (p < 0.001). Conclusions: SB prevalence increased between 2002 and 2017 for the EU as a whole and for both sexes separately. Additionally, differences in SB prevalence were observed for all years between EU countries in the whole sample and both sexes separately. Lastly, SB was consistently higher in men than women. These findings reveal a limited impact of current policies and interventions to tackle SB at the EU population level.

Set configuration refers to the repetitions performed with regard to the maximum possible number of repetitions, a factor affecting RPE that has not been previously studied. This study analyzed the effect of set configuration and muscle mass on RPE. Eight students ( M age = 23.7 yr. ± 1.7) completed four sessions corresponding to types of exercise with different amount of muscle mass (bench press and parallel squat) and two set configurations: a session with five sets of repetitions to failure and a cluster session. The cluster session involved the same intensity, volume, and rest than the failure session, guaranteeing the same work-to-rest ratio. RPE was higher in Failure vs Cluster sessions and higher in parallel squat vs bench press. This suggests that set configuration influences RPE. Similarly, RPE can be affected by the muscle mass of the exercise performed.

Purpose: To analyze performance during the execution of a maximum number of repetitions (MNR) in a cluster-set configuration.Method: Nine judokas performed 2 sessions of parallel squats with a load corresponding to 4-repetition maximum (4RM) with a traditional-training (TT) and cluster-training (CT) set configuration. The TT consisted of 3 sets of repetitions leading to failure and 3 min of rest between sets. In the CT the MNR was performed with a rest interval between repetitions (45.44 ± 11.89 s). The work-to-rest ratio was similar for CT and TT.Results: MNR in CT was 45.5 ± 32 repetitions and was 9.33 ± 1.87 times the volume in TT. There was a tendency for the average mean propulsive velocity (MPV) to be higher in CT (0.39 ± 0.04 vs 0.36 ± 0.04 m/s for CT and TT, respectively, P = .054, standardized mean difference [d] = 0.57). The average MPV was higher in CT for a similar number of repetitions (0.44 ± 0.08 vs 0.36 ± 0.04 m/s for CT and TT, respectively, P = .006, d = 1.33). The number of repetitions in TT was correlated with absolute 4RM load (r = –.719, P = .031) but not in CT (r = –.273, P = .477).Conclusions: A cluster-set configuration allows for a higher number of repetitions and improved sustainability of mechanical performance. CT, unlike TT, was not affected by absolute load, suggesting an improvement of training volume with high absolute loads.

This study compared the functional and neural effects of two strength training programmes differing in set configuration. Thirteen participants performed 10 sessions, over a period of 5 weeks, of unilateral leg extensions with different set configurations but with identical work-to-rest ratios for each limb: a traditional configuration (4 sets of 8 repetitions, 10RM load, 3-min pause between sets) and an inter-repetition rest configuration (32 repetitions, 10RM load, 17.4 s of rest between each repetition). Mean propulsive velocity of the traditional sessions was lower than for inter-repetition rest sessions (0.48 ± 0.06 vs. 0.54 ± 0.06 m · s⁻¹; P < 0.001), while perceived exertion was higher (8.3 ± 0.9 and 6.56 ± 1.6 for traditional training and IRT; P = 0.002). One repetition maximum (RM), work with 10RM load, maximum mean propulsive power, maximum voluntary contraction and time to failure with 50% of maximum isometric force improved similarly in both legs (time effect, P < 0.001; effect size range, 0.451–1.190). Time and set configuration did not show significant main effects or interactions for cortical adaptations (motor-evoked potentials, short-interval intracortical inhibition, intracortical facilitation). There were no significant correlations between changes in cortical and peripheral neural adaptations and strength improvement. In conclusion, inter-repetition rest configuration was as effective as traditional training in improving muscle performance.

Background: The World Health Organization (WHO) considers physical inactivity (PIA) as a critical noncommunicable factor for disease and mortality, affecting more women than men. In 2013, the WHO set a 10% reduction of the PIA prevalence, with the goal to be reached by 2025. Changes in the 2013–2017 period of physical inactivity prevalence in the 28 European Union (EU) countries were evaluated to track the progress in achieving WHO 2025 target. Methods: In 2013 and 2017 EU Special Eurobarometers, the physical activity levels reported by the International Physical Activity Questionnaire of 53,607 adults were analyzed. Data were considered as a whole sample and country-by-country. A χ2 test was used to analyze the physical inactivity prevalence (%) between countries, analyzing women and men together and separately. Additionally, PIA prevalence was analyzed between years (2013–2017) for the overall EU sample and within-country using a Z-Score for two population proportions. Results: The PIA prevalence increased between 2013 and 2017 for the overall EU sample (p < 0.001), and for women (p = 0.04) and men (p < 0.001) separately. Data showed a higher PIA prevalence in women versus men during both years (p < 0.001). When separately considering changes in PIA by gender, only Belgium’s women and Luxembourg’s men showed a reduction in PIA prevalence. Increases in PIA prevalence over time were observed in women from Austria, Croatia, Germany, Lithuania, Malta, Portugal, Romania, and Slovakia and in men from Bulgaria, Croatia, Czechia, Germany, Italy, Lithuania, Portugal, Romania, Slovakia, and Spain. Conclusions: PIA prevalence showed an overall increase across the EU and for both women and men between 2013 and 2017, with higher rates of PIA reported for women versus men during both years. PIA prevalence was reduced in only Belgium’s women and Luxembourg’s men. Our data indicate a limited gender-sensible approach while tacking PIA prevalence with no progress reaching global voluntary reductions of PIA for 2025.