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Hintergrund
Kommunale Bewegungsförderung kann zur Vermeidung lebensstilbedingter Erkrankungen beitragen, ist aber keine kommunale Pflichtaufgabe, weshalb es in der Regel keine klaren Zuständigkeiten dafür gibt. Um zu verstehen, wie kommunale Bewegungsförderung in Deutschland vorangebracht werden kann, ist es wichtig, potenzielle Multiplikator*innen in städtischen und ländlichen Kommunen zu identifizieren und deren Rollen zu charakterisieren.
Methodische Vorgehensweise
Es wurden 18 potenzielle Multiplikator*innen der kommunalen Gesundheits- und Bewegungsförderung auf verschiedenen Ebenen (Bundesland, Landkreis/Stadt, Gemeinde/Stadtteil) in leitfadengestützten semistrukturierten Interviews zu ihrer eigenen Rolle sowie zu ihrer Wahrnehmung der Rollen anderer Akteur*innen befragt. Die Auswertung erfolgte gemäß der inhaltlich-strukturierenden Inhaltsanalyse nach Kuckartz.
Ergebnisse
(Landes‑)Gesundheitsämter und Gesundheitskonferenzen nehmen eine beratende, vernetzende und fachlich unterstützende Rolle ein. Auf der Umsetzungsebene vor Ort müssen sich im Einzelfall Kümmer*innen finden, die in Stadt und Land unterschiedlich sein können. Die befragten Quartiermanager*innen sehen ihre primäre Rolle in der Arbeit mit den Bürger*innen, die Verwaltungsmitarbeiter*innen in der administrativen Abwicklung von Projekten.
Schlussfolgerung
Fachliche Impulse zur kommunalen Bewegungsförderung können über Landesgesundheitsämter an Akteur*innen in Landkreisen und Städten weitergegeben werden. Für die Multiplikation und Umsetzung in einzelnen Gemeinden und Stadtteilen müssen Verantwortliche vor Ort gefunden werden bzw. Strukturen aufgebaut werden.
To evaluate the effects of Ramadan observance on dietary intake, body mass and body composition of adolescent athletes (design: systematic review and meta-analysis; data sources: PubMed and Web of Science; eligibility criteria for selecting studies: single-group, pre-post, with or without control-group studies, conducted in athletes aged <19 years, training at least 3 times/week, and published in any language before 12 February 2020). Studies assessing body mass and/or body composition and/or dietary intake were deemed eligible. The methodological quality was assessed using ‘QualSyst’. Of the twelve selected articles evaluating body mass and/or body composition, one was of strong quality and eleven were rated as moderate. Ten articles evaluated dietary intake; four were rated as strong and the remaining moderate in quality. Continuation of training during Ramadan did not change body mass from before to the first week (trivial effect size (ES) = −0.011, p = 0.899) or from before to the fourth week of Ramadan (trivial ES = 0.069, p = 0.277). Additionally, Ramadan observance did not change body fat content from before to the first week (trivial ES = −0.005, p = 0.947) and from before to the fourth week of Ramadan (trivial ES = -0.057, p = 0.947). Lean body mass remained unchanged from before to the fourth week of Ramadan (trivial ES = −0.025, p = 0.876). Dietary data showed the intake of energy (small ES = -0.272, p = 0.182), fat (trivial ES = 0.044, p = 0.842), protein (trivial ES = 0.069, p = 0.720), carbohydrate (trivial ES = 0.075, p = 0.606) and water (trivial ES = −0.115, p = 0.624) remained essentially unchanged during as compared to before Ramadan. Continued training of adolescent athletes at least three times/week during Ramadan observance has no effect on body mass, body composition or dietary intake.
Virtual online training has emerged as one of the top 20 worldwide fitness trends for 2021 and continues to develop rapidly. Although this allows the cycling community to engage in virtual training and competition, critical evaluation of virtual training platforms is limited. Here, we discuss the strengths, weaknesses, opportunities and threats associated with virtual training technology and cycling in an attempt to enhance awareness of such aspects. Strengths include immersive worlds, innovative drafting mechanics, and versatility. Weaknesses include questionable data accuracy, inadequate strength and reliability of power-speed algorithms. Opportunities exist for expanding strategic partnerships with major cycling races, brands, and sponsors and improving user experience with the addition of video capture and “e-coaching.” Threats are present in the form of cheating during competition, and a lack of uptake and acceptance by a broader community.
The rating of perceived exertion (RPE) is a subjective load marker and may assist in individualizing training prescription, particularly by adjusting running intensity. Unfortunately, RPE has shortcomings (e.g., underreporting) and cannot be monitored continuously and automatically throughout a training sessions. In this pilot study, we aimed to predict two classes of RPE (≤15 “Somewhat hard to hard” on Borg’s 6–20 scale vs. RPE >15 in runners by analyzing data recorded by a commercially-available smartwatch with machine learning algorithms. Twelve trained and untrained runners performed long-continuous runs at a constant self-selected pace to volitional exhaustion. Untrained runners reported their RPE each kilometer, whereas trained runners reported every five kilometers. The kinetics of heart rate, step cadence, and running velocity were recorded continuously ( 1 Hz ) with a commercially-available smartwatch (Polar V800). We trained different machine learning algorithms to estimate the two classes of RPE based on the time series sensor data derived from the smartwatch. Predictions were analyzed in different settings: accuracy overall and per runner type; i.e., accuracy for trained and untrained runners independently. We achieved top accuracies of 84.8 % for the whole dataset, 81.8 % for the trained runners, and 86.1 % for the untrained runners. We predict two classes of RPE with high accuracy using machine learning and smartwatch data. This approach might aid in individualizing training prescriptions.
High-Intensity Interval Training Performed by Young Athletes: A Systematic Review and Meta-Analysis
(2018)
Background: High-intensity interval training (HIIT) is as a time-efficient alternative to moderate- or low-intensity continuous exercise for improving variables related to endurance and anaerobic performance in young and adolescent athletes.
Objectives: To assess original research about enhancement of endurance and anaerobic exercise performance in young and adolescent athletes performing HIIT.
Method: Relevant articles published in peer-reviewed journals were retrieved from the electronic databases PubMed and SPORTDiscus in December 2017. Inclusion criteria were: (i) controlled trials (HIIT vs. alternative training protocol) with pre-post design; (ii) healthy young athletes (≤18 years); (iii) assessing variables related to endurance and exercise performance. Hedges' g effect size (ES), and associated 95% confidence intervals were calculated for comparison of any outcome between experimental (HIIT) and alternative training protocol.
Results: Twenty four studies, involving 577 athletes (mean age: 15.5 ± 2.2 years), were included in this review. HIIT exerted no or small positive mean ES on peak oxygen uptake (VO2peak), running performance, repeated sprint ability, jumping performance and submaximal heart rate. Although the mean ES for changes in VO2peak with HIIT is small (mean g = 0.10±0.28), the average increase in VO2peak from pre to post HIIT-interventions were 7.2 ± 6.9% vs. 4.3 ± 6.9% with any other alternative intervention. HIIT largely and positively affected running speed and oxygen consumption at various lactate- or ventilatory-based thresholds, as well as for sprint running performance. Calculations showed negative mean ES for change-of-direction ability (large), and peak blood lactate concentrations (small). Mean duration per training session for HIIT was shorter than for control interventions (28 ± 15 min vs. 38 ± 24 min).
Conclusion: The present findings suggest that young athletes performing HIIT may improve certain important variables related to aerobic, as well as anaerobic, performance. With HIIT, most variables related to endurance improved to a higher extent, compared to alternative training protocols. However, based on ES, HIIT did not show clear superiority to the alternative training protocols. Nevertheless, young athletes may benefit from HIIT as it requires less time per training session leaving more time for training sport specific skills.
This paper provides the evidence of a sweet spot on the boot/foot as well as the method for detecting it with a wearable pressure sensitive device. This study confirmed the hypothesized existence of sweet and dead spots on a soccer boot or foot when kicking a ball. For a stationary curved kick, kicking the ball at the sweet spot maximized the probability of scoring a goal (58–86%), whereas having the impact point at the dead zone minimized the probability (11–22%). The sweet spot was found based on hypothesized favorable parameter ranges (center of pressure in x/y-directions and/or peak impact force) and the dead zone based on hypothesized unfavorable parameter ranges. The sweet spot was rather concentrated, independent of which parameter combination was used (two- or three-parameter combination), whereas the dead zone, located 21 mm from the sweet spot, was more widespread.
There is a debate on the optimal way of monitoring training loads in elite endurance athletes especially during altitude training camps. In this case report, including nine members of the German national middle distance running team, we describe a practical approach to monitor the psychobiological stress markers during 21 days of altitude training (~2100 m above sea‐level) to estimate the training load and to control muscle damage, fatigue, and/or chronic overreaching. Daily examination included: oxygen saturation of hemoglobin, resting heart rate, body mass, body and sleep perception, capillary blood concentration of creatine kinase. Every other day, venous serum concentration of blood urea nitrogen, venous blood concentration of hemoglobin, hematocrit, red and white blood cell were measured. If two or more of the above‐mentioned stress markers were beyond or beneath the athlete's normal individual range, the training load of the subsequent training session was reduced. Running speed at 3 mmol L\(^{−1}\) blood lactate (V\(_{3}\)) improved and no athlete showed any signs of underperformance, chronic muscle damage, decrease body and sleep perception as well as activated inflammatory process during the 21 days. The dense screening of biomarkers in the present case study may stimulate further research to identify candidate markers for load monitoring in elite middle‐ and long‐distance runners during a training camp at altitude.
The purpose of this study was threefold: 1) to assess the eggbeater kick and throwing performance using a number of water polo specific tests, 2) to explore the relation between the eggbeater kick and throwing performance, and 3) to investigate the relation between the eggbeater kick in the water and strength tests performed in a controlled laboratory setting in elite water polo players. Fifteen male water polo players of the German National Team completed dynamic and isometric strength tests for muscle groups (adductor, abductor, abdominal, pectoralis) frequently used during water polo. After these laboratory strength tests, six water polo specific in-water tests were conducted. The eggbeater kick assessed leg endurance and agility, maximal throwing velocity and jump height. A 400 m test and a sprint test examined aerobic and anaerobic performance. The strongest correlation was found between jump height and arm length (p < 0.001, r = 0.89). The laboratory diagnostics of important muscles showed positive correlations with the results of the in-water tests (p < 0.05, r = 0.52-0.70). Muscular strength of the adductor, abdominal and pectoralis muscles was positively related to in-water endurance agility as assessed by the eggbeater kick (p < 0.05; r = 0.53-0.66). Findings from the current study emphasize the need to assess indices of water polo performance both in and out of the water as well as the relation among these parameters to best assess the complex profile of water polo players.
The purpose of this study was to determine whether an individually designed incremental exercise protocol results in greater rates of oxygen uptake VO\(_{2max}\) than standardized testing. Fourteen well-trained, male runners performed five incremental protocols in randomized order to measure their VO\(_{2max}\): i) an incremental test (INC\(_{S+I}\)) with pre-defined increases in speed (2 min at 8.64 km.h\(^{-1}\), then a rise of 1.44 km.h\(^{-1}\) every 30 s up to 14.4 km.h\(^{-1}\)) and thereafter inclination (0.5.every 30 s); ii) an incremental test (INC\(_{I}\)) at constant speed (14.4 km.h\(^{-1}\)) and increasing inclination (2 degrees every 2 min from the initial 0 degrees); iii) an incremental test (INC\(_{S}\)) at constant inclination (0 degrees) and increasing speed (0.5 km.h\(^{-1}\) every 30 s from the initial 12.0 km.h\(^{-1}\)); iv) a graded exercise protocol (GXP) at a 1 degrees incline with increasing speed (initially 8.64 km.h\(^{-1}\) + 1.44 km.h\(^{-1}\) every 5 min); v) an individual exercise protocol (INDXP) in which the runner chose the inclination and speed. VO\(_{2max}\) was lowest (-4.2%) during the GXP (p = 0.01; d = 0.06 - 0.61) compared to all other tests. The highest rating of perceived exertion, heart rate, ventilation and end-exercise blood lactate concentration were similar between the different protocols (p < 0.05). The time to exhaustion ranged from 7 min 18 sec (INC\(_{S}\)) to 25 min 30 sec (GXP) (p = 0.01). The VO\(_{2max}\) attained by employing an individual treadmill protocol does not differ from the values derived from various standardized incremental protocols.
The aim was to examine certain aspects of circulatory, metabolic, hormonal, thermoregulatory, cognitive, and perceptual responses while sitting following a brief session of high-intensity interval exercise. Twelve students (five men; age, 22 ± 2 years) performed two trials involving either simply sitting for 180 min (SIT) or sitting for this same period with a 6-min session of high-intensity exercise after 60 min (SIT+HIIT). At T\(_0\) (after 30 min of resting), T\(_1\) (after a 20-min breakfast), T\(_2\) (after sitting for 1 h), T\(_3\) (immediately after the HIIT), T\(_4\), T\(_5\), T\(_6\), and T\(_7\) (30, 60, 90, and 120 min after the HIIT), circulatory, metabolic, hormonal, thermoregulatory, cognitive, and perceptual responses were assessed. The blood lactate concentration (at T\(_3\)–T\(_5\)), heart rate (at T\(_3\)–T\(_6\)), oxygen uptake (at T\(_3\)–T\(_7\)), respiratory exchange ratio, and sensations of heat (T\(_3\)–T\(_5\)), sweating (T\(_3\), T\(_4\)) and odor (T\(_3\)), as well as perception of vigor (T\(_3\)–T\(_6\)), were higher and the respiratory exchange ratio (T\(_4\)–T\(_7\)) and mean body and skin temperatures (T\(_3\)) lower in the SIT+HIIT than the SIT trial. Levels of blood glucose and salivary cortisol, cerebral oxygenation, and feelings of anxiety/depression, fatigue or hostility, as well as the variables of cognitive function assessed by the Stroop test did not differ between SIT and SIT+HIIT. In conclusion, interruption of prolonged sitting with a 6-min session of HIIT induced more pronounced circulatory and metabolic responses and improved certain aspects of perception, without affecting selected hormonal, thermoregulatory or cognitive functions.