Search

Evelyn Eichenberger,1 Beat Knechtle,1,2 Christoph Alexander Rüst,1 Thomas Rosemann,1 Romuald Lepers31Institute of General Practice and Health Services Research, University of Zurich, Zurich, Switzerland; 2Gesundheitszentrum St Gallen, St Gallen, Switzerland; 3INSERM U1093, Faculty of Sport Sciences, University of Burgundy, Dijon, FranceBackground: The aims of the study were to examine the (a) participation, (b) difference in running times between the sexes, and (c) age-related decline in the running times of ultramarathoner women and men competing in the Swiss Alpine Marathon from 1998 to 2011.Methods: The ultramarathoners competing in the Swiss Alpine Marathon were analyzed in terms of participation, difference in running times between the sexes, age of the fastest runners, and age-related decline in the fastest running times. The race covers a distance of 78 km, with a total altitude change of approximately 2260 m. A total of 12,194 men and 1781 women finished the race between 1998 and 2011.Results: Women's participation increased from approximately 10% in 1998 to approximately 16% in 2011 (r2 = 0.57; P = 0.001), but participation remained unchanged in men (r2 = 0.17; P > 0.05). Over the years, the top ten women showed no change in running times (r2 = 0.02; P > 0.05), whereas the top ten men's running times increased (r2 = 0.46; P < 0.01). The age for peak running times increased over time both for the top ten women (r2 = 0.58; P < 0.01) and for the top ten men (r2 = 0.40; P = 0.01).Conclusion: Among the top women, participation increased, the age for peak running times increased, and the running times remained unchanged. Among the men, however, the participation remained steady, and both the peak running-time age and the running times increased.Keywords: ultra-endurance, aging, sex difference, running

Background: Recent studies have shown that personal best marathon time is a strong predictor of race time in male ultramarathoners. We aimed to determine variables predictive of marathon race time in recreational male marathoners by using the same characteristics of anthropometry and training as used for ultramarathoners.Methods: Anthropometric and training characteristics of 126 recreational male marathoners were bivariately and multivariately related to marathon race times.Results: After multivariate regression, running speed of the training units (β=-0.52, P

Beat Knechtle,1,2 Christoph Alexander Rüst,2 Thomas Rosemann,2 Romuald Lepers31Gesundheitszentrum St Gallen, St Gallen, Switzerland; 2Institute of General Practice and Health Services Research, University of Zurich, Zurich, Switzerland; 3INSERM U1093, Faculty of Sport Sciences, University of Burgundy, Dijon, FranceBackground: To date, the age-related decline and gender differences in performance have been investigated for both Olympic and Ironman distance triathlons, but not for the intermediate distance (ie, the half-Ironman distance triathlon covering 1.9 km swimming, 90 km cycling and 21.1 km running, Ironman 70.3®). We determined the age-related differences in performance and the gender differences for female and male half-Ironman triathletes of 6303 finishers (1115 women and 5188 men) at the Ironman 70.3 Switzerland in Rapperswil, Switzerland, from 2007 to 2010.Methods: Analyses of variance were used to examine performance trends and differences between the genders.Results: Gender differences in total event time were affected by age (F = 4.2; P < 0.001). Women achieved their best performance between 25 and 39 years whereas men attained their fastest race times between 18 and 39 years. The gender difference for ages 18–24 years was significantly (P < 0.01) greater compared to older age groups (25–29 years and 40–44 years), and the gender difference for age groups 45–49 years and 50–54 years was significantly (P < 0.01) greater than for those between the ages of 35–39 years.Conclusion: The present data suggest that the fastest race time in a half-Ironman triathlon was achieved between the age of 25 and 39 years for women and between 18 and 39 years for men. Further studies considering the influences on endurance performance are required to better understand the age and gender interactions in half-Ironman triathlon performances, and these studies may provide valuable information to delineate the difference in performance between female and male half-Ironman triathletes.Keywords: cycling, endurance, female, male, running, swimming

David Eisner, Marco Zoller, Thomas Rosemann, Carola A Huber, Nina Badertscher, Ryan TandjungInstitute for General Practice and Health Services Research, University of Zurich, Zurich, SwitzerlandBackground and objectives: Prevention is a challenging area of primary care. In Switzerland, little is known about attitudes to and performance of screening and prevention services in general practice. To implement prevention services in primary care it is important to know about not only potential facilitators but also barriers. Primary care encompasses the activities of general practitioners, including those with particular interest and/or specializations (eg, pediatrics, gynecology). The aim of this study was to review all studies with a focus on prevention services which have been conducted in Switzerland and to reveal barriers and facilitators for physicians to participate in any preventive measures.Methods: The Cochrane Library, PubMed, EMBASE and BIOSIS were searched from January 1990 through December 2010. Studies focussing on preventive activities in primary care settings were selected and reviewed. The methodological quality of the identified studies was classified according to the guidelines in the Consolidated Standards of Reporting Trials (CONSORT) statement.Results: We identified 49 studies including 45 descriptive studies and four randomised controlled trials (RCTs). Twelve studies addressed the prevention of epidemics, eleven out of them vaccinations. Further studies focused on lifestyle changes, physical activity counselling, smoking cessation, cardiovascular prevention and cancer screening. Perceived lack of knowledge/training and lack of time were the most commonly stated barriers. Motivation, feasibility and efficiency were the most frequently reported supporting factors for preventive activities. The methodological quality was weak, only one out of four RCTs met the applied quality criteria.Conclusion: Most studies focussing on screening and prevention activities in primary care addressed vaccination, lifestyle modification or cardiovascular disease prevention. Identified barriers and facilitators indicate a need for primary-care-adapted education and training which are easy to handle, time-saving and reflect the specific needs of general practitioners. If new prevention programs are to be implemented in general practices, RCTs of high methodological quality are needed to assess their impact.Keywords: disease prevention, primary care, Switzerland, epidemic, screening, education, descriptive study

Ryan Tandjung, Thomas Rosemann, Nina BadertscherInstitute of General Practice and Health Services Research, University of Zurich, SwitzerlandIntroduction: Discontinuity of care at the interface between inpatient and outpatient management can lead to increased morbidity and mortality. Appropriate communication and flow of information is indispensable to ensure continuity of care. Consequently, the aim of this study was to assess general practitioners’ (GPs) experiences of cooperation with a university hospital, as well as their needs and obvious barriers regarding an optimized information flow.Methods: A qualitative study was performed. In March 2011, 300 GPs from the Zurich Canton were invited to participate in two focus group meetings. Based on a review of the literature, an interview guide was created addressing two main issues. In the first part, experiences and barriers regarding cooperation with the university were explored. In the second part, needs and suggestions to improve cooperation were addressed.Results: Fifteen GPs participated in two focus groups. GPs complained that they have often not been adequately informed about ongoing treatments or appointments for their patients. GPs feel responsible for the continuity of care and wish to be more involved, especially in long-term treatment decisions or at the end of life. By not involving them, they stated, important information concerning patients’ medical history and social setting was not taken into account. Improvements are also required at discharge: GPs often do not receive important information about treatments in the hospital and further requirements within a reasonable time.Conclusion: Exchange of information between the hospital and the GP at admission and discharge is essential. However, at present, involvement during hospitalization of the patient is lacking. This includes the exchange of information after an unexpected clinical procedure and input from GPs when difficult clinical decisions are made, such as at the beginning or termination of long-term therapies.Keywords: referral, general practitioners, hospital, cooperation, handover, communication

Christoph Alexander Rüst1, Beat Knechtle1,2, Patrizia Knechtle2, Ursula Barandun1, Romuald Lepers3, Thomas Rosemann11Institute of General Practice and Health Services Research, University of Zurich, Zurich, Switzerland; 2Gesundheitszentrum St Gallen, St Gallen, Switzerland; 3INSERM U887, University of Burgundy, Faculty of Sport Sciences, Dijon, FranceAbstract: The aim of this study was to investigate predictor variables of anthropometry, training, and previous experience in order to predict a half marathon race time for future novice recreational male half marathoners. Eighty-four male finishers in the ‘Half Marathon Basel’ completed the race distance within (mean and standard deviation, SD) 103.9 (16.5) min, running at a speed of 12.7 (1.9) km/h. After multivariate analysis of the anthropometric characteristics, body mass index (r = 0.56), suprailiacal (r = 0.36) and medial calf skin fold (r = 0.53) were related to race time. For the variables of training and previous experience, speed in running of the training sessions (r = –0.54) were associated with race time. After multivariate analysis of both the significant anthropometric and training variables, body mass index (P = 0.0150) and speed in running during training (P = 0.0045) were related to race time. Race time in a half marathon might be partially predicted by the following equation (r2 = 0.44): Race time (min) = 72.91 + 3.045 * (body mass index, kg/m2) –3.884 * (speed in running during training, km/h) for recreational male runners. To conclude, variables of both anthropometry and training were related to half marathon race time in recreational male half marathoners and cannot be reduced to one single predictor variable.Keywords: anthropometry, body fat, skin-folds, training, endurance

Romuald Lepers1, Beat Knechtle2,3, Patrizia Knechtle2, Thomas Rosemann2 1INSERM U887, Faculty of Sport Sciences, University of Burgundy, Dijon, France; 2Institute of General Practice and Health Services Research, University of Zurich, Switzerland; 3Gesundheitszentrum St Gallen, St Gallen, Switzerland Abstract: Despite increased interest in ultra-endurance events, little research has examined ultra-triathlon performance. The aims of this study were: (i) to compare swimming, cycling, running, and overall performances in three ultra-distance triathlons, double Ironman distance triathlon (2IMT) (7.6 km swimming, 360 km cycling, and 84.4 km running), triple Ironman distance triathlon (3IMT) (11.4 km, 540 km, and 126.6 km), and deca Ironman distance triathlon (10IMT) (38 km, 1800 km, and 420 km) and (ii) to examine the relationships between the 2IMT, 3IMT, and 10IMT performances to create predicted equations of the 10IMT performances. Race results from 1985 through 2009 were examined to identify triathletes who performed the three considered ultra-distances. In total, 73 triathletes (68 men and 5 women) were identified. The contribution of swimming to overall ultra-triathlon performance was lower than for cycling and running. Running performance was more important to overall performance for 2IMT and 3IMT compared with 10IMT. The 2IMT and 3IMT performances were significantly correlated with 10IMT performances for swimming and cycling, but not for running. 10IMT total time performance might be predicted by the following equation: 10IMT race time (minutes) = 5885 + 3.69 × 3IMT race time (minutes). This analysis of human performance during ultra-distance triathlons represents a unique data set in the field of ultra-endurance events. Additional studies are required to determine the physiological and psychological factors associated with ultra-triathlon performance. Keywords: triathlon, swimming, cycling, running, ultra-endurance

Christoph Alexander Rüst1, Beat Knechtle1,2, Patrizia Knechtle2, Thomas Rosemann1, Romuald Lepers31Institute of General Practice and Health Services Research, University of Zurich, Zurich, Switzerland; 2Gesundheitszentrum St Gallen, St Gallen, Switzerland; 3INSERM U887, University of Burgundy, Faculty of Sport Sciences, Dijon, FranceBackground: The purpose of this study was to define predictor variables for recreational male Ironman triathletes, using age and basic measurements of anthropometry, training, and previous performance to establish an equation for the prediction of an Ironman race time for future recreational male Ironman triathletes.Methods: Age and anthropometry, training, and previous experience variables were related to Ironman race time using bivariate and multivariate analysis.Results: A total of 184 recreational male triathletes, of mean age 40.9 ± 8.4 years, height 1.80 ± 0.06 m, and weight 76.3 ± 8.4 kg completed the Ironman within 691 ± 83 minutes. They spent 13.9 ± 5.0 hours per week in training, covering 6.3 ± 3.1 km of swimming, 194.4 ± 76.6 km of cycling, and 45.0 ± 15.9 km of running. In total, 149 triathletes had completed at least one marathon, and 150 athletes had finished at least one Olympic distance triathlon. They had a personal best time of 130.4 ± 44.2 minutes in an Olympic distance triathlon and of 193.9 ± 31.9 minutes in marathon running. In total, 126 finishers had completed both an Olympic distance triathlon and a marathon. After multivariate analysis, both a personal best time in a marathon (P < 0.0001) and in an Olympic distance triathlon (P < 0.0001) were the best variables related to Ironman race time. Ironman race time (minutes) might be partially predicted by the following equation: (r2 = 0.65, standard error of estimate = 56.8) = 152.1 + 1.332 × (personal best time in a marathon, minutes) + 1.964 × (personal best time in an Olympic distance triathlon, minutes).Conclusion: These results suggest that, in contrast with anthropometric and training characteristics, both the personal best time in an Olympic distance triathlon and in a marathon predict Ironman race time in recreational male Ironman triathletes.Keywords: body fat, swimming, cycling, running, triathlon

OBJECTIVE: This study aimed at comparing the depression and anxiety levels, and health self-perception during the coronavirus disease 2019 pandemic among subjects who practice aerobic, strength, and mixed (aerobic and strength) exercises and nonsports participants. MATERIALS AND METHODS: We included 304 Brazilians of both sexes in this cross-sectional study. All participants were recruited through online advertisement and completed a self-administered questionnaire regarding the personal information, level of restriction adopted, physical activity, and mood state screening (Patient Health Questionnaire-9 and General Anxiety Disorder-7). We divided the participants into four groups: strength sports group (CrossFit or strength training), aerobic/endurance sports groups (running, cycling, triathlon, or swimming), mixed sports groups (individuals who practice endurance and strength sports), and nonsports group. RESULTS: The Kruskal-Wallis test showed a significant effect of the group on the depression and anxiety levels. Meanwhile, the post-hoc comparisons showed a significantly lower depression level in the mixed and aerobic sports groups than in the strength sports and nonsports groups, and a significantly lower anxiety level in the mixed and aerobic sports groups than in the nonsports group. Furthermore, participants in the mixed, strength, and aerobic sports groups presented a better level of health self-assessment than the nonsports group, and those in the mixed sports group had a better level of health self-assessment than the strength or aerobic sports groups. CONCLUSIONS: Individuals practicing aerobic exercises present lower depression and anxiety levels than those practicing strength training and are inactive. However, individuals who practice strength exercises and aerobics have the best levels of health perception. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Competitive athletes must undergo fitness testing to monitor athlete progress and to create appropriate, progressive training programs. However, fitness testing adds to training stress; therefore, impacts of testing on wellness and recovery must be considered in test selection. This study investigated the effects of two incremental field tests [VAMEVAL test (T-VAM) and 20-m maximum shuttle test (20-m MST)] on wellness, total quality of recovery (TQR) and physical enjoyment (PE) in competitive soccer players. SUBJECTS AND METHODS: Twenty-two soccer players (20.9±1.5 years) completed two T-VAM and two 20-m MST in a randomized order on separate days with a 1-week interval between tests. TQR and wellness indices (sleep, fatigue, stress and muscle soreness) measures were collected before and 24 hours after each test. Heart rate (HR) was continuously monitored during each test. Rating of perceived exertion (RPE) and PE were assessed after each test. RESULTS: T-VAM resulted in higher PE, TQR and wellness scores than 20-m MST (p<0.05). T-VAM and 20-m MST resulted in similar HR and maximal aerobic speed. For T-VAM, TQR was correlated (p<0.01) with RPE and wellness indices. For 20-m MST, TQR was correlated (p<0.01) with wellness indices. HRmax and RPE were not correlated with wellness indices, TQR or PE. CONCLUSIONS: Overall, T-VAM and 20-m MST produced similar aerobic fitness testing results, but athletes responded more favorably to T-VAM. Coaches can use T-VAM for evaluating aerobic fitness while maximizing well-being and physical enjoyment among soccer players. [ABSTRACT FROM AUTHOR]