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Background: All physical activity (PA) behaviours undertaken over the day, including sleep, sedentary time, standing time, light-intensity PA (LIPA) and moderate-to-vigorous PA (MVPA) have the potential to influence cardiometabolic health. Since these behaviours are mutually exclusive, standard statistical approaches are unable to account for the impact on time spent in other behaviours., Objective: By employing a compositional data analysis (CoDA) approach, this study examined the associations of objectively measured time spent in sleep, sedentary time, standing time, LIPA and MVPA over a 24-h day on markers of cardiometabolic health in older adults., Methods: Participants (n =366; 64.6 years [5.3]; 46% female) from the Mitchelstown Cohort Rescreen Study provided measures of body composition, blood lipid and markers of glucose control. An activPAL3 Micro was used to obtain objective measures of sleep, sedentary time, standing time, LIPA and MVPA, using a 7-day continuous wear protocol. Regression analysis, using geometric means derived from CoDA (based on isometric log-ratio transformed data), was used to examine the relationship between the aforementioned behaviours and markers of cardiometabolic health., Results: Standing time and LIPA showed diverging associations with markers of body composition. Body mass index (BMI), body mass and fat mass were negatively associated with LIPA (all p <0.05) and positively associated with standing time (all p <0.05). Sedentary time was also associated with higher BMI (p <0.05). No associations between blood markers and any PA behaviours were observed, except for triglycerides, which were negatively associated with standing time (p < 0.05). Reallocating 30 min from sleep, sedentary time or standing time, to LIPA, was associated with significant decreases in BMI, body fat and fat mass., Conclusion: This is the first study to employ CoDA in older adults that has accounted for sleep, sedentary time, standing time, LIPA and MVPA in a 24-h cycle. The findings support engagement in LIPA to improve body composition in older adults. Increased standing time was associated with higher levels of adiposity, with increased LIPA associated with reduced adiposity; therefore, these findings indicate that replacing standing time with LIPA is a strategy to lower adiposity.

Background: Economy, velocity/power at maximal oxygen uptake ([Formula: see text]) and endurance-specific muscle power tests (i.e. maximal anaerobic running velocity; vMART), are now thought to be the best performance predictors in elite endurance athletes. In addition to cardiovascular function, these key performance indicators are believed to be partly dictated by the neuromuscular system. One technique to improve neuromuscular efficiency in athletes is through strength training., Objective: The aim of this systematic review was to search the body of scientific literature for original research investigating the effect of strength training on performance indicators in well-trained endurance athletes-specifically economy, [Formula: see text] and muscle power (vMART)., Methods: A search was performed using the MEDLINE, PubMed, ScienceDirect, SPORTDiscus and Web of Science search engines. Twenty-six studies met the inclusion criteria (athletes had to be trained endurance athletes with ≥6 months endurance training, training ≥6 h per week OR [Formula: see text] ≥50 mL/min/kg, the strength interventions had to be ≥5 weeks in duration, and control groups used). All studies were reviewed using the PEDro scale., Results: The results showed that strength training improved time-trial performance, economy, [Formula: see text] and vMART in competitive endurance athletes., Conclusion: The present research available supports the addition of strength training in an endurance athlete's programme for improved economy, [Formula: see text], muscle power and performance. However, it is evident that further research is needed. Future investigations should include valid strength assessments (i.e. squats, jump squats, drop jumps) through a range of velocities (maximal-strength ↔ strength-speed ↔ speed-strength ↔ reactive-strength), and administer appropriate strength programmes (exercise, load and velocity prescription) over a long-term intervention period (>6 months) for optimal transfer to performance.