Available evidence suggests that young adults and seniors use different strategies to adjust for increasing body sway during quiet standing. Altered antagonist muscle co-activation and different ankle muscle coordination patterns may account for this finding. Consequently, we aimed at addressing whether aging leads to changes in neuromuscular coordination patterns as well as co-activation during quiet stance. We additionally investigated whether a bout of high intensity interval training additionally alters these patterns. Twenty healthy seniors (age: 70 ± 4 y) and twenty young adults (age: 27 ± 3 y) were enrolled in the present study. In between the testing procedures, four consecutive high-intensity intervals of 4 min duration at a target exercise intensity of 90 to 95% HRmax were completed on a treadmill. The total center of pressure (COP) path length displacement served as standing balance performance outcome. In order to assess ankle muscle coordination patterns, amplitude ratios (AR) were calculated for each muscle (e.g. tibialis anterior (TA) [%] = (TA × 100)/(gastrocnemius medialis (GM) + soleus (SOL) + peroneus longus (PL) + TA). The co-activation was calculated for the SOL and TA muscles computing the co-activation index (CAI = 2 × TA/TA + SOL). Seniors showed an inverted ankle muscle coordination pattern during single limb stance with eyes open (SLEO), compared to young adults (rest: GM, S: 15 ± 8% vs Y: 24 ± 9%; p = 0.03; SOL, S: 27 ± 14% vs Y: 37 ± 18%; p = 0.009; TA, S: 31 ± 13% vs Y: 13 ± 7%; p = 0.003). These patterns did not change after a high-intensity training session. A moderate correlation between amplitude ratios of the TA-contribution and postural sway was observed for seniors during SLEO (r = 0.61). Ankle co-activation was twofold elevated in seniors compared to young adults during SLEO (p < 0.001). These findings were also not affected by high intensity training. Increased ankle co-activation in the anterior-posterior plane and inverted ankle muscle coordination pattern merely occurred during single-leg stance. Seniors with decreased postural control showed higher TA contributions during SLEO. These neuromuscular changes are not affected by acute intermittent high intensity aerobic exercise.

Objective: Prolonged office sitting time adversely affects neuromuscular and cardiovascular health parameters. As a consequence, the present study investigated the effects of prompting the use of height-adjustable working desk (HAWD) on occupational sitting and standing time, neuromuscular outcomes and concentration in office workers. Methods: A single-blinded randomized controlled trial (RCT) with parallel group design was conducted. Thirty-eight office workers were supplied with HAWDs and randomly assigned (Strata: physical activity (PA), BMI, gender, workload) to a prompt (INT) or non-prompt (CON) group. INT received three daily screen-based prompts within 12 weeks. CON was only instructed once concerning the benefits of using HAWDs prior to the start of the study. Sitting and standing times were objectively assessed as primary outcomes for one entire working week using the ActiGraph wGT3X-BT at baseline (pre), after 6 (mid) and 12 weeks (post). Concentration (d2-test), postural sway during upright stance (under single, dual and triple task) and lower limb strength endurance (heel-rise) were collected as secondary outcomes. Results: With large but not statistically significant within group effects from pre to post, INT increased weekly standing time at work by 9% (p = 0.22, d = 0.8) representing an increase from 7.2 h (4.8) to 9.7 (6.6) h (p = 0.07). Concentration and neuromuscular performance did not change from pre to post testing (0.23 < p < 0.95; 0.001 < η_p² < 0.05). Conclusion: Low-frequent and low cost screen-based point of choice prompts (3 per day within 12 weeks) already result in notable increases of occupational standing time of approx. daily 30 min. These stimuli, however, did not relevantly affect neuromuscular outcomes.

Cardiovascular (CV) diseases including heart failure are the leading causes of morbidity, with age being the primary risk factor. The combination of age-related organic functional impairment and reduced physical fitness can drastically impact an individual’s healthspan. One’s lifespan can potentially be prolonged by the preservation or improvement of physical fitness. However, it remains unclear as to which biomarkers are most suitable for distinguishing between healthy aging and the impaired organ function associated with heart failure. Therefore, a comprehensive assessment of the components of physical fitness and CV function will be performed to identify the most important factors contributing to aging in relation to both health and disease. This cross-sectional investigation will consist of two parts: COmPLETE-Health (C-Health) and COmPLETE-Heart (C-Heart). C-Health will examine the aging trajectories of physical fitness components and CV properties in a healthy population sample aged between 20 and 100 years (n = 490). Separately, C-Heart will assess the same markers in patients at different stages of chronic heart failure (n = 80). The primary outcome to determine the difference between C-Health and C-Heart will be cardiorespiratory fitness as measured by cardiopulmonary exercise testing on a bicycle ergometer. Secondary outcomes will include walking speed, balance, isometric strength, peak power, and handgrip strength. Physical activity as a behavioural component will be assessed objectively via accelerometry. Further, CV assessments will include pulse wave velocity; retinal, arterial, and venous diameters; brachial and retinal arterial endothelial function; carotid intima-media thickness; and systolic and diastolic function. The health distances for C-Health and C-Heart will be calculated using the methodology based on statistical (Mahalanobis) distance applied to measurements of quantitative biomarkers. This research seeks to identify physical fitness and CV biomarkers that best resemble underlying CV risk with age. Further, it will examine which physical fitness markers are impaired most in heart failure. The presented integrative approach could define new recommendations for diagnostic guidance in aging. Ultimately, this study is expected to offer a better understanding of which functional characteristics should be specifically targeted in primary and secondary prevention to achieve an optimal healthspan.

Background: Stroke is a major cause of disability and stroke incidence increases with age. Stroke frequently results in permanent limitations of mobility, and, consequently, the need for the help of others in activities of daily living. In order to optimize rehabilitative efforts and their functional outcomes, detailed knowledge of the functional recovery process, regarding mobility, is needed. Objectives of the MOBITEC-Stroke study are: 1.) To characterize mobility, including lower extremity physical function (LEPF) and life space (the geospatial extent of all of a person’s movements), and changes in mobility within the first year after stroke. 2.) To identify and characterize subgroups with different mobility trajectories. 3.) To evaluate whether changes in LEPF are associated with changes in life-space. 4.) To evaluate participants’ reasons for going outdoors, transportation use, and assistance needed for outdoor movement. Methods: Patients with incident first stroke who live in their own homes (target N = 59, based on sample size calculation) will be included in this cohort study. At 3, 6, 9, and 12 months after stroke a battery of mobility tests will be performed at the study centre, including laboratory-based tests of balance and strength, and quantitative gait analysis. Life-space assessment (including 1-week GPS measurements) will be performed in participants’ real life. Semantic information on visited locations (reasons for going outdoors, transportation use, assistance needed) will be collected by using interactive digital maps. Linear mixed effects models will be used to model the trajectories of mobility measures for the total sample and for predefined subgroups. As an exploratory analysis, growth mixture models (GMMs) will be used to identify relevant subgroups with different trajectories. Linear mixed effect models will be used to test whether changes in LEPF parameters are associated with changes in life-space. Participants’ motivation for going outdoors, transportation use, and assistance needed for outdoor mobility will be analysed descriptively. Discussion: A comprehensive and detailed knowledge of recovery patterns will enable the planning of targeted and adaptively tailored rehabilitation measures. Information about patients’ reasons for outdoor mobility will provide the opportunity to define individualized and patient-oriented rehabilitation goals. Trial registration: ISRCTN85999967 (on 13 August 2020; retrospectively).

Objective: To (1) establish extensive physiological profiles of highly trained CrossFit® athletes using gold-standard tests and (2) investigate which physiological markers best correlate with CrossFit Open performance. Methods: This study encompassed 60 participants (30 men and 30 women), all within the top 5% of the CrossFit Open, including 7 CrossFit semifinalists and 3 CrossFit Games finalists. Isokinetic dynamometers were employed to measure maximum isometric and isokinetic leg and trunk strength. Countermovement-jump height and maximum isometric midthigh-pull strength were assessed on a force plate. Peak oxygen uptake (VO₂peak) was measured by a cardiopulmonary exercise test, and critical power and W′ were evaluated during a 3-minute all-out test, both on a cycle ergometer. Results: Male and female athletes’ median (interquartile range) VO₂peak was 4.64 (4.43, 4.80) and 3.21 (3.10, 3.29) L·min⁻¹, critical power 314.5 (285.9, 343.6) and 221.3 (200.9, 238.9) W, and midthigh pull 3158 (2690, 3462) and 2035 (1728, 2347) N. Linear-regression analysis showed strong evidence for associations between different anthropometric variables and CrossFit Open performance in men and women, whereas for markers of cardiorespiratory fitness such as VO₂peak, this was only true for women but not men. Conventional laboratory evaluations of strength, however, manifested minimal evidence for associations with CrossFit Open performance across both sexes. Conclusions: This study provides the first detailed insights into the physiology of high-performing CrossFit athletes and informs training optimization. Furthermore, the results emphasize the advantage of athletes with shorter limbs and suggest potential modifications to CrossFit Open workout designs to level the playing field for athletes across different anthropometric characteristics.