Sex difference in IRONMAN age group triathletes.

BACKGROUND: The sex difference in athletic performance has been thoroughly investigated in single sport disciplines such as swimming, cycling, and running. In contrast, only small samples of long-distance triathlons, such as the IRONMAN® triathlon, have been investigated so far. AIM: The aim of the study was to examine potential sex differences in the three split disciplines by age groups in 5-year intervals in a very large data set of IRONMAN® age group triathletes. METHODS: Data from 687,696 (553,608 men and 134,088 women) IRONMAN® age group triathletes (in 5-year intervals from 18-24 to 75+ years) finishing successfully between 2002 and 2022 an official IRONMAN® race worldwide were analyzed. The differences in performance between women and men were determined for each split discipline and for the overall race distance. RESULTS: Most finishers were in the age group 40-44 years. The fastest women were in the age group 25-29 years, and the fastest men were in the age group 30-34 years. For all split disciplines and overall race time, men were always faster than women in all groups. The performance difference between the sexes was more pronounced in cycling compared to swimming and running. From the age group 35-39 years until 60-64 years, the sex differences were nearly identical in swimming and running. For both women and men, the smallest sex difference was least significant in age group 18-24 years for all split disciplines and increased in a U-shaped manner until age group 70-74 years. For age groups 75 years and older, the sex difference decreased in swimming and cycling but increased in running. Considering the different characteristics of the race courses, the smallest performance gaps between men and women were found in river swimming, flat surface cycling and rolling running courses. CONCLUSIONS: The sex difference in the IRONMAN® triathlon was least significant in age group 18-24 years for all split disciplines and increased in a U-shaped manner until age group 70-74 years. For 75 years and older, the sex difference decreased in swimming and cycling but increased in running.

Case Report: Differences in self-selected pacing in 20, 40, and 60 ironman-distance triathlons: a case study.

Background: Triathletes are pushing their limits in multi-stage Ironman-distance triathlons. In the present case study, we investigated the pacing during 20, 40, and 60 Ironman-distance triathlons in 20, 40, and 60 days, respectively, of one professional IRONMAN® triathlete. Case study: Event 1 (20 Ironman-distance triathlons in 20 days), Event 2 (40 Ironman-distance triathlons in 40 days), and Event 3 (60 Ironman-distance triathlons in 60 days) were analyzed by discipline (swimming, cycling, running, and overall event time), by Deca intervals (10 days of consecutive Ironman-distance triathlons) and additional data (sleep duration, body mass, heart rate in cycling and running). To test differences between Events and Deca intervals within the same discipline, T-tests (2 groups) or one-way ANOVAs (3 or more groups) were used. Results: Swimming splits were fastest in Event 1, (ii) cycling and running splits were fastest in both Event 2 and 3, (iii) overall speed was fastest in Event 3, (iv) sleep duration increased during Event 2 but decreased in Event 3, (v) body mass decreased in Event 2, but increased in Event 3 and (vi) heart rate during cycling was similar in both Event 2 and 3. In contrast, heart rate during running was greater in Event 3. Conclusion: In a professional IRONMAN® triathlete finishing 20, 40, and 60 Ironman-distance triathlons in 20, 40, and 60 days, respectively, split performances and both anthropometrical and physiological changes such as body mass and heart rate differed depending upon the duration of the events.

Crocus Sativus Linnaeus (Saffron) intake does not affect physiological and perceptual responses during a repeated sprint test in healthy active young males.

The study aimed to investigate the effects of acute ingestion of saffron (SAF) on physiological (i.e., heart rate and blood lactate) and perceptual (i.e., ratings of perceived exertion [RPE] and feeling scale) measures in response to a repeated-sprint ability test (RSS) in healthy young males (N = 22; mean ± SD: age, 21.7 ± 1.24 yrs.). All participants completed two experimental trials with a one-week washout period using a double-blind, placebo-controlled, crossover design. In each session, the participants were randomly chosen to receive either a capsule of saffron (300 mg) (SAF session) or a capsule of lactose (PLB session) two hours before performing the RSS.No significant differences (p > 0.05) were found for heart rate, RPE, and feeling scale between the SAF or PLB sessions at pre- and post-RSS. There were no significant changes (p > 0.05) in peak time, total time, fatigue index, and blood lactate in either the SAF or PLB sessions. Acute SAF ingestion did not significantly improve RSS performance nor physiological and perceptual measures in active young males. Future trials should address the topic by using shortened/prolonged higher doses of SAF on biological, physical, physiological, and perceptual responses to acute and chronic exercise.

Critical Analysis of Information Provided by ChatGPT on Lactate, Exercise, Fatigue, and Muscle Pain: Current Insights and Future Prospects for Enhancement.

This study aimed to critically evaluate the information provided by ChatGPT on the role of lactate in fatigue and muscle pain during physical exercise. We inserted the prompt: "What is the cause of fatigue and pain during exercise?" using ChatGPT versions 3.5 and 4o. In both versions, ChatGPT associated muscle fatigue with glycogen depletion and "lactic acid" accumulation, while pain was linked to processes such as inflammation and microtrauma. We deepened the investigation with ChatGPT 3.5, implementing user feedback to question the accuracy of the information about lactate. The response was then reformulated, involving a scientific debate about the true role of lactate in physical exercise and debunking the idea that it is the primary cause of muscle fatigue and pain. We also utilized the creation of a "well-crafted prompt", which included persona identification and thematic characterization, resulting in much more accurate information in both the ChatGPT 3.5 and 4o models, presenting a range of information from the physiological process of lactate to its true role in physical exercise. The results indicated that the accuracy of the responses provided by ChatGPT can vary depending on the data available in its database and, more importantly, on how the question is formulated. Therefore, it is indispensable that educators guide their students in the processes of managing the AI tool to mitigate risks of misinformation.

Europe has the fastest Ironman race courses and the fastest Ironman age group triathletes.

The majority of participants in Ironman triathlon races are age group athletes. We have extensive knowledge about recreational athletes' training and competition participation. Nonetheless, Ironman age group triathletes must achieve fast race times to qualify for the Ironman World Championship in Hawaii. They can, therefore, benefit from knowing where the fastest Ironman racecourses in the world are. The aim of the present study was to investigate where the fastest Ironman racecourses for age group triathletes are located in the world. Data from 677,702 Ironman age group finishers' records (544,963 from men and 132,739 from women) originating from 228 countries and participating in 444 events across 66 different Ironman race locations between 2002 and 2022 were analyzed. Data was analyzed through traditional descriptive statistics and with machine learning regression models. Four algorithms were tested (Random Forest Regressor, XG Boost Regressor, Cat Boot Regressor, and Decision Tree Regressor). The models used gender, age group, country of origin, environmental factors (average air and water temperatures), and the event location as independent variables to predict the final overall race time. Despite the majority of successful Ironman age group triathletes originating from the USA (274,553), followed by athletes from the United Kingdom (55,410) and Canada (38,264), these countries exhibited average overall race times that were significantly slower compared to the fastest countries. Most of the triathletes competed in Ironman Wisconsin (38,545), followed by Ironman Florida (38,157) and Ironman Lake Placid (34,341). The fastest overall race times were achieved in Ironman Copenhagen (11.68 ± 1.38 h), followed by Ironman Hawaii (11.72 ± 1.86 h), Ironman Barcelona (11.78 ± 1.43 h), Ironman Florianópolis (11.80 ± 1.52 h), Ironman Frankfurt (12.03 ± 1.38 h) and Ironman Kalmar (12.08 ± 1.47 h). The fastest athletes originated from Belgium (11.48 ± 1.47 h), followed by athletes from Denmark (11.59 ± 1.40 h), Switzerland (11.62 ± 1.49 h), Austria (11.68 ± 1.50), Finland (11.68 ± 1.40 h) and Germany (11.74 ± 15.1 h). Flat running and cycling courses were associated with faster overall race times. Three of the predictive models identified the 'country' and 'age group' variables as the most important predictors. Environmental characteristics showed the lowest influence regarding the other variables. The origin of the athlete was the most predictive variable whereas environmental characteristics showed the lowest influence. Flat cycling and flat running courses were associated with faster overall race times. The fastest overall race times were achieved mainly in European races such as Ironman Copenhagen, Ironman Hawaii, Ironman Barcelona, Ironman Florianópolis, Ironman Frankfurt and Ironman Kalmar. The fastest triathletes originated from European countries such as Belgium, Denmark, Switzerland, Austria, Finland, and Germany.

Does wet-cupping therapy improve repeated sprint ability, perceived wellness, and rating of perceived exertion in young active males?

Wet-cupping therapy (WCT) is one of the oldest known medical techniques, used as a traditional and complementary therapy with a wide application all around the world for general health. Research on the effects of WCT on sports performance are sparse and inconsistent. Thus, we aimed to explore the effects of WCT on repeated sprint ability, wellness, and exertion in young active males. Forty-nine active adult males (age: [28 â€‹± â€‹5] years; body height [177 â€‹± â€‹8] cm; body mass: [79 â€‹± â€‹7] kg; body mass index: [25.4 â€‹± â€‹1.8] kg/m2) were selected for the study. The participants performed a running-based sprint test on two separate occasions (Control and Post-WCT). WCT was performed 24 â€‹h before the testing session. They completed the Hooper questionnaire to assess their well-being ( i.e. , sleep, stress, fatigue, and soreness) before each session. The rating of perceived exertion (RPE) was collected after each testing session. A higher maximum power (p â€‹< â€‹0.05, effect size [ES] â€‹= â€‹0.6), mean power (p â€‹< â€‹0.01, ES â€‹= â€‹0.5) and minimum power (p â€‹< â€‹0.01, ES â€‹= â€‹0.6) were recorded post-WCT as compared to Control session along with a better perceived sleep (p â€‹< â€‹0.01, ES â€‹= â€‹0.85). Perceived stress (p â€‹< â€‹0.01, ES â€‹= â€‹0.6) and RPE (p â€‹< â€‹0.001; ES â€‹= â€‹1.1) were lower during the post-WCT compared to the Control session. The present findings demonstrated that WCT moderately enhanced repeated sprint ability and had positive effects on perceived sleep, stress, and exertion. WCT may be an effective ergogenic aid to improve repeated sprint ability and general well-being in young adult males. Future large-scale multicentric clinical studies are paramount to confirm the results of our study.

Cycling Intensity Effect on Running Plus Cycling Performance among Triathletes.

Running performance is crucial for triathlon performance. However, the prior bout of cycling may affect the running split time. This study compared the triathletes' cycling plus running (C+R) time, when cycling was performed at three different intensities and running was maximal. A total of 38 athletes (21 males and 17 females) were included. Body composition, maximal oxygen uptake, and functional threshold power (FTP) was evaluated. The participants visited the laboratory three times to cycle 20 km at 80%, 85%, or 90% FTP (in randomized order) and run 5 km as fast as possible. Males ran faster after cycling at 80% FTP than after cycling at 90% FTP (mean difference=35.1 s; CI% 2.2, 68.1 s; p=0.035). The C+R time was faster when cycling at 90% FTP than at 80% FTP (mean difference=57.7 s; CI% 26.1, 89.3 s; p<0.001). For females, no significant difference was observed in the running time after cycling at 80%, 85%, or 90% FTP. The C+R time was faster when cycling at 90% FTP than at 80% FTP (mean difference=80.9 s; CI% 29.7, 132.1 s; p=0.002). In conclusion, to optimize triathlon performance, male and female athletes should cycle at a minimum of 90% FTP.

Predicting and comparing the long-term impact of lifestyle interventions on individuals with eating disorders in active population: a machine learning evaluation.

Objective: This study aims to evaluate and predict the long-term effectiveness of five lifestyle interventions for individuals with eating disorders using machine learning techniques. Methods: This study, conducted at Dr. Irandoust's Health Center at Qazvin from August 2021 to August 2023, aimed to evaluate the effects of five lifestyle interventions on individuals with eating disorders, initially diagnosed using The Eating Disorder Diagnostic Scale (EDDS). The interventions were: (1) Counseling, exercise, and dietary regime, (2) Aerobic exercises with dietary regime, (3) Walking and dietary regime, (4) Exercise with a flexible diet, and (5) Exercises through online programs and applications. Out of 955 enrolled participants, 706 completed the study, which measured Body Fat Percentage (BFP), Waist-Hip Ratio (WHR), Fasting Blood Sugar (FBS), Low-Density Lipoprotein (LDL) Cholesterol, Total Cholesterol (CHO), Weight, and Triglycerides (TG) at baseline, during, and at the end of the intervention. Random Forest and Gradient Boosting Regressors, following feature engineering, were used to analyze the data, focusing on the interventions' long-term effectiveness on health outcomes related to eating disorders. Results: Feature engineering with Random Forest and Gradient Boosting Regressors, respectively, reached an accuracy of 85 and 89%, then 89 and 90% after dataset balancing. The interventions were ranked based on predicted effectiveness: counseling with exercise and dietary regime, aerobic exercises with dietary regime, walking with dietary regime, exercise with a flexible diet, and exercises through online programs. Conclusion: The results show that Machine Learning (ML) models effectively predicted the long-term effectiveness of lifestyle interventions. The current study suggests a significant potential for tailored health strategies. This emphasizes the most effective interventions for individuals with eating disorders. According to the results, it can also be suggested to expand demographics and geographic locations of participants, longer study duration, exploring advanced machine learning techniques, and including psychological and social adherence factors. Ultimately, these results can guide healthcare providers and policymakers in creating targeted lifestyle intervention strategies, emphasizing personalized health plans, and leveraging machine learning for predictive healthcare solutions.

Using machine learning to determine the nationalities of the fastest 100-mile ultra-marathoners and identify top racing events.

The present study intended to determine the nationality of the fastest 100-mile ultra-marathoners and the country/events where the fastest 100-mile races are held. A machine learning model based on the XG Boost algorithm was built to predict the running speed from the athlete's age (Age group), gender (Gender), country of origin (Athlete country) and where the race occurred (Event country). Model explainability tools were then used to investigate how each independent variable influenced the predicted running speed. A total of 172,110 race records from 65,392 unique runners from 68 different countries participating in races held in 44 different countries were used for analyses. The model rates Event country (0.53) as the most important predictor (based on data entropy reduction), followed by Athlete country (0.21), Age group (0.14), and Gender (0.13). In terms of participation, the United States leads by far, followed by Great Britain, Canada, South Africa, and Japan, in both athlete and event counts. The fastest 100-mile races are held in Romania, Israel, Switzerland, Finland, Russia, the Netherlands, France, Denmark, Czechia, and Taiwan. The fastest athletes come mostly from Eastern European countries (Lithuania, Latvia, Ukraine, Finland, Russia, Hungary, Slovakia) and also Israel. In contrast, the slowest athletes come from Asian countries like China, Thailand, Vietnam, Indonesia, Malaysia, and Brunei. The difference among male and female predictions is relatively small at about 0.25 km/h. The fastest age group is 25-29 years, but the average speeds of groups 20-24 and 30-34 years are close. Participation, however, peaks for the age group 40-44 years. The model predicts the event location (country of event) as the most important predictor for a fast 100-mile race time. The fastest race courses were occurred in Romania, Israel, Switzerland, Finland, Russia, the Netherlands, France, Denmark, Czechia, and Taiwan. Athletes and coaches can use these findings for their race preparation to find the most appropriate racecourse for a fast 100-mile race time.

Comparison of bone mineral density between female amateur triathletes and nonathletes: A cross-sectional study.

PURPOSE: Physical inactivity is considered an important risk factor for osteoporosis, however, some athletes performing extremely high training volumes can also develop bone mass loss. Moreover, the effect of total body mass or body surface area on bone mineral density remains controversial. Therefore, the aim of this study was to compare the absolute bone mineral density and bone mineral density adjusted to body surface area between amateur triathletes and nonactive women. METHODS: Forty-two healthy women (23 amateur triathletes and 19 nonactive individuals) were evaluated for body composition using a dual-energy X-ray absorptiometry system. RESULTS: Compared to nonactive women, amateur triathletes exhibited lower body mass index (p < 0.001), lower bone mineral density (p < 0.001), and body surface area (p < 0.001). However, bone mineral density adjusted by body surface area in the triathletes was higher than in the nonactive women (p = 0.03). CONCLUSION: These findings showed that amateur triathles presented lower absolute bone mineral density, but higher bone mineral density adjusted to body surface area. Future studies are recommended to identify if the higher bone mineral density adjusted to body surface area are associated with a lower bone fragility.

Analysis of the fastest backstroke age group swimmers competing in the World Masters Championships 1986-2024.

Backstroke has been thoroughly investigated in the context of sports science. However, we have no knowledge about the nationalities of the fastest age group backstroke swimmers. Therefore, the present study intended to investigate the nationalities of the fastest backstroke swimmers. For all World Masters Championships held between 1986 and 2024, the year of competition, the first and last name, the age, and the age group, and both the stroke and the distance were recorded for each swimmer. Descriptive data were presented using mean, standard deviation, maximum and minimum values, and confidence intervals. The top ten race times for each swimming distance and sex were identified for descriptive purposes. Nationalities were then grouped into six categories: the top five nationalities with the most appearances in the backstroke swimming top ten times by distance each year and one group consisting of all other nationalities. The Kruskal-Wallis test compared nationality differences, followed by Bonferroni-adjusted pairwise comparisons to identify specific distinctions. Between 1986 and 2024, most age group backstroke swimmers (39.6%) competed in the 50 m event (11,964, 6206 women, and 5,758 men), followed by the 100 m event (32.3%, n = 9764, 5157 women, and 4607 men), and the 200 m event (28.1%, n = 8483, 4511 women, and 3,972 men). Germany had the highest number of top ten female swimmers in the 50 m backstroke distance. Brazil had the highest number of top ten male swimmers in the same distance. The USA had the highest number of female and male swimmers among the top ten in the 100 m and 200 m backstroke distances. Germany and Great Britain were the only countries with swimmers in the top ten for all female backstroke distances. Brazil, the USA, Italy, and Germany were the countries that had swimmers in the top ten for all male backstroke distances. In summary, the fastest backstroke age group swimmers originated from Germany, Brazil, USA, Great Britain, and Italy, where differences between the sexes and race distances exist.

Developing normative values and predictive models for the 6-minute walk test across diverse adolescent developmental stages.

The six-minute walking test (6MWT) is commonly used to measure functional capacity in field settings, primarily through the distance covered. This study aims to establish reference curves for the six-minute walking distance (6MWD) and peak heart rate (PHR) and develop a predictive equation for cardiovascular capacity in Tunisian children and adolescents. A total of 1501 participants (706 boys and 795 girls), aged 10-18 years, were recruited from schools in Tunisia. The Lambda (L), Mu (M), and Sigma (S) methods (LMS method) were employed to develop smoothed percentile curves for 6MWD and PHR. Multivariate linear regression was utilized to formulate a prediction equation for 6MWD. Smoothed percentiles (3rd, 10th, 25th, 50th, 75th, 90th, and 97th) for 6MWD and PHR were presented with age. All variables showed a strong positive correlation (p < 0.001) with a six-minute walking distance (r ranged from 0.227 to 0.558 for girls and from 0.309 to 0.610 for boys), except resting heart rate, which showed a strong negative correlation (girls: r = -0.136; boys: r = -0.201; p < 0.001). Additionally, PHR showed a weak correlation (p > 0.05). The prediction equations, based on age as the primary variable, were established for both genders. For boys: 6MWD = 66.181 + 38.142 × Age (years) (R2 = 0.372; Standard Error of Estimate (SEE) = 122.13), and for girls: 6MWD = 105.535 + 28.390 × Age (years) (R2 = 0.312; SEE = 103.66). The study provides normative values and predictive equations for 6MWD and PHR in Tunisian children and adolescents. These findings offer essential tools for identifying, monitoring, and interpreting cardiovascular functional deficits in clinical and research settings.

Developing and testing a framework for coding general practitioners' free-text diagnoses in electronic medical records - a reliability study for generating training data in natural language processing.

BACKGROUND: Diagnoses entered by general practitioners into electronic medical records have great potential for research and practice, but unfortunately, diagnoses are often in uncoded format, making them of little use. Natural language processing (NLP) could assist in coding free-text diagnoses, but NLP models require local training data to unlock their potential. The aim of this study was to develop a framework of research-relevant diagnostic codes, to test the framework using free-text diagnoses from a Swiss primary care database and to generate training data for NLP modelling. METHODS: The framework of diagnostic codes was developed based on input from local stakeholders and consideration of epidemiological data. After pre-testing, the framework contained 105 diagnostic codes, which were then applied by two raters who independently coded randomly drawn lines of free text (LoFT) from diagnosis lists extracted from the electronic medical records of 3000 patients of 27 general practitioners. Coding frequency and mean occurrence rates (n and %) and inter-rater reliability (IRR) of coding were calculated using Cohen's kappa (Κ). RESULTS: The sample consisted of 26,980 LoFT and in 56.3% no code could be assigned because it was not a specific diagnosis. The most common diagnostic codes were, 'dorsopathies' (3.9%, a code covering all types of back problems, including non-specific lower back pain, scoliosis, and others) and 'other diseases of the circulatory system' (3.1%). Raters were in almost perfect agreement (Κ ≥ 0.81) for 69 of the 105 diagnostic codes, and 28 codes showed a substantial agreement (K between 0.61 and 0.80). Both high coding frequency and almost perfect agreement were found in 37 codes, including codes that are particularly difficult to identify from components of the electronic medical record, such as musculoskeletal conditions, cancer or tobacco use. CONCLUSION: The coding framework was characterised by a subset of very frequent and highly reliable diagnostic codes, which will be the most valuable targets for training NLP models for automated disease classification based on free-text diagnoses from Swiss general practice.

Changes in the attractiveness of medical careers and career determinants during the bachelor's program at Zurich medical schools.

BACKGROUND: Monitoring the career intentions of medical students during their undergraduate studies could help to address the shortage of physicians, particularly in general practice. This study aimed to investigate changes in medical students' career openness, attractiveness and determinants of medical career choice during their bachelor's studies. METHODS: The design was cross-sectional, recruiting all medical students who started a bachelor's program in one of the four different educational tracks in Zurich, Switzerland, in the fall of 2019 (first survey) and completed it in the summer of 2022 (second survey). Students' perceptions of the attractiveness and determinants of different medical career options were assessed using a structured online questionnaire. Absolute changes between the two-time points were reported in percentage points overall and by educational track. Regression analysis was used to examine the association of student characteristics and determinants of career options with the attractiveness of each option. RESULTS: We surveyed 354 medical students at the beginning and 433 at the end of the bachelor's program (participation rate: 71.1% and 86.9%, respectively). Overall, the proportion of students open to all proposed medical career options decreased (from 52.8% to 43.8%, p = 0.004). The attractiveness of outpatient gynecology or pediatrics increased (from 27.4% to 43.4%, p < 0.001), whereas the attractiveness of both general and specialized inpatient care decreased (from 47.8% to 40.3%, p = 0.05 and from 71.1% to 61.1%, p = 0.006 respectively). There was an increase in the proportion of students who perceived part-time work, autonomy and relationships with patients as important career determinants (from 47.3% to 64.7%, p < 0.001; from 63.3% to 77.8%, p < 0.001; from 80.8% to 89.3%, p = 0.002 respectively), while the importance of reputation and career opportunities decreased (from 42.6% to 26.2%, p < 0.001; from 79.2% to 63.6%, p < 0.001 respectively). The importance of part-time work and relationships with patients were positively associated with the attractiveness of general practice. CONCLUSIONS: During the bachelor's program, the attractiveness of a career in general practice tended to decrease, but the importance of part-time work, autonomy and relationships with patients as career determinants increased. Helping students understand how these determinants relate to general practice may increase their interest in the profession. TRIAL REGISTRATION: Not applicable.

Impact of aging on maximal oxygen uptake in female runners and sedentary controls.

The present study aimed to compare V̇O2max (absolute, adjusted to total body mass, and adjusted to lean mass) in recreational runners and sedentary women < and > 50 yr and verify the effect of aging and physical activity level on the three types of V̇O2 max expression. The study included 147 women:85 runners (45.7 ± 14.1 yr) and 62 sedentary controls (48.8 ± 9.8 yr). They were subjected to cardiopulmonary exercise testing for V̇O2 max measurement and a body composition test by dual-emission X-ray absorptiometry system. V̇O2max were expressed as absolute values (L/min), relative to total body mass values (mL/kg/min), and relative to lean mass values (mL/kgLM/min). The two-way analysis of variance revealed a significant interaction [F(2,131) = 4.43, p < 0.001] and effects of age group [F(2,131) = 32.79, p < 0.001] and physical activity group [F(2,131) = 55.64, p < 0.001] on V̇O2max (mL/min). V̇O2max (mL/kg/min) and V̇O2 max (mL/kgLM/min) were significantly influenced by age and physical activity levels. The multiple regression model explains 76.2 % of the dependent variable V̇O2max (mL/kg/min), age (ß = -0.335, t = -7.841, p < 0.001), and physical activity group (ß = -0.784, t = -18.351, p < 0.001). In conclusion, female runners had higher V̇O2 max values than sedentary women at all ages, even though aging has a greater impact on V̇O2 max in the runners group. In addition to cardiorespiratory fitness, women's metabolic lean mass function, as measured by V̇O2max adjusted by lean mass, is significantly influenced by aging. Finally, physical activity has a greater impact on V̇O2 max levels than aging.

Effect of self-modeling and self-controlled feedback on the performance of professional swimmers and waterpolo players.

Self-modeling (SM) and self-control (SC) feedback can be presented as two solutions for learning improvement. Therefore, the aim of the present study was to investigate the effects of SM and SC feedback on 100-m freestyle performance of professional swimmers and waterpolo players. 25 elite male swimmers and waterpolo players, were randomly assigned to four groups: swimmer group with SM, swimmer group with SM and SC feedback, waterpolo players group with SM, and waterpolo players group with SM and SC feedback. 100-m freestyle times and performance were recorded. SM and SC feedback for the participants were utilized at the acquisition stage. The device used included a Lenovo B570 laptop and an Exilim ZR200 canon camcorder. SM and SC feedback presented to the swimmers and waterpolo players led to improved speed and results, and the effect of presenting SM with SC feedback to swimmers had better results. In conclusion, the present study indicates that SC modeling of watching video is a suitable method for professional swimmers. Water polo trainers can also use SM and SC feedback to enhance their players' swimming technique.

Personality of marathon runners: a narrative review of recent findings.

Participation in marathons has dramatically increased over the last few years. Marathon running has many proven beneficial effects, especially on cardiovascular health and fitness. Most research has focused on physiologic and pathophysiologic adaptations in connection with endurance exercise. Nevertheless, marathon running also has a major impact on psychological aspects and positively influences mental health, which has only recently attracted research interest. The present narrative review aimed to review the personality traits of marathon runners with an emphasis on recent literature. Marathon runners show a distinct personality and highly characteristic personality traits needed to successfully finish such a demanding race, i.e., a strong sense of vigor, self-sufficiency, and intelligence as well as low scores in anger, fatigue, tension, and depression. Furthermore, personality differences are detectable between runners of different sexes, ages, and performance level groups. This has significant clinical implications for athletes, coaches and competition organizers, as these groups show different patterns of personality traits. Future studies should focus on changes in cognition and mood states pre-, during, and post-endurance events, as well as during training periods. Large-scale studies comparing personality differences by sex, age, and performance are also important for better clinical guidance. See also the graphical abstract(Fig. 1).

Analysis of over 1 million race records shows runners from East African countries as the fastest in 50-km ultra-marathons.

The 50-km ultra-marathon is a popular race distance, slightly longer than the classic marathon distance. However, little is known about the country of affiliation and age of the fastest 50-km ultra-marathon runners and where the fastest races are typically held. Therefore, this study aimed to investigate a large dataset of race records for the 50-km distance race to identify the country of affiliation and the age of the fastest runners as well as the locations of the fastest races. A total of 1,398,845 50-km race records (men, n = 1,026,546; women, n = 372,299) were analyzed using both descriptive statistics and advanced regression techniques. This study revealed significant trends in the performance of 50-km ultra-marathoners. The fastest 50-km runners came from African countries, while the fastest races were found to occur in Europe and the Middle East. Runners from Ethiopia, Lesotho, Malawi, and Kenya were the fastest in this race distance. The fastest 50-km racecourses, providing ideal conditions for faster race times, are in Europe (Luxembourg, Belarus, and Lithuania) and the Middle East (Qatar and Jordan). Surprisingly, the fastest ultra-marathoners in the 50-km distance were found to fall into the age group of 20-24 years, challenging the conventional belief that peak ultra-marathon performance comes in older age groups. These findings contribute to a better understanding of the performance models in 50-km ultra-marathons and can serve as valuable insights for runners, coaches, and race organizers in optimizing training strategies and racecourse selection.

Ultra-Cycling- Past, Present, Future: A Narrative Review.

BACKGROUND: Ultra-endurance events are gaining popularity in multiple exercise disciplines, including cycling. With increasing numbers of ultra-cycling events, aspects influencing participation and performance are of interest to the cycling community. MAIN BODY: The aim of this narrative review was, therefore, to assess the types of races offered, the characteristics of the cyclists, the fluid and energy balance during the race, the body mass changes after the race, and the parameters that may enhance performance based on existing literature. A literature search was conducted in PubMed, Scopus, and Google Scholar using the search terms 'ultracycling', 'ultra cycling', 'ultra-cycling', 'ultra-endurance biking', 'ultra-bikers' and 'prolonged cycling'. The search yielded 948 results, of which 111 were relevant for this review. The studies were classified according to their research focus and the results were summarized. The results demonstrated changes in physiological parameters, immunological and oxidative processes, as well as in fluid and energy balance. While the individual race with the most published studies was the Race Across America, most races were conducted in Europe, and a trend for an increase in European participants in international races was observed. Performance seems to be affected by characteristics such as age and sex but not by anthropometric parameters such as skin fold thickness. The optimum age for the top performance was around 40 years. Most participants in ultra-cycling events were male, but the number of female athletes has been increasing over the past years. Female athletes are understudied due to their later entry and less prominent participation in ultra-cycling races. A post-race energy deficit after ultra-cycling events was observed. CONCLUSION: Future studies need to investigate the causes for the observed optimum race age around 40 years of age as well as the optimum nutritional supply to close the observed energy gap under consideration of the individual race lengths and conditions. Another research gap to be filled by future studies is the development of strategies to tackle inflammatory processes during the race that may persist in the post-race period.

Genotypic and Allelic Distribution of the CD36 rs1761667 Polymorphism in High-Level Moroccan Athletes: A Pilot Study.

Previous studies have shown that variations in the CD36 gene may affect phenotypes associated with fat metabolism as the CD36 protein facilitates the transport of fatty acids to the mitochondria for oxidation. However, no previous study has tested whether variations in the CD36 gene are associated with sports performance. We investigated the genotypic and allelic distribution of the single-nucleotide polymorphism (SNP) rs1761667 in the CD36 gene in elite Moroccan athletes (cyclists and hockey players) in comparison with healthy non-athletes of the same ethnic origin. Forty-three Moroccan elite male athletes (nineteen cyclists and twenty-four field hockey players) belonging to the national teams of their respective sports (athlete group) were compared to twenty-eight healthy, active, male university students (control group). Genotyping of the CD36 rs1761667 (G>A) SNP was performed via polymerase chain reaction (PCR) and Sanger sequencing. A chi-square (χ2) test was used to assess the Hardy-Weinberg equilibrium (HWE) and to compare allele and genotype frequencies in the "athlete" and "control" groups. The genotypic distribution of the CD36 rs1761667 polymorphism was similar in elite athletes (AA: 23.81, AG: 59.52, and GG: 16.67%) and controls (AA: 19.23, AG: 69.23, and GG: 11.54%; χ2 = 0.67, p = 0.71). However, the genotypic distribution of the CD36 rs1761667 polymorphism was different between cyclists (AA: 0.00, AG: 72.22, and GG: 27.78%) and hockey players (AA: 41.67, AG: 50.00, and GG: 8.33%; χ2 = 10.69, p = 0.004). Specifically, the frequency of the AA genotype was significantly lower in cyclists than in hockey players (p = 0.02). In terms of allele frequency, a significant difference was found between cyclists versus field hockey players (χ2 = 7.72, p = 0.005). Additionally, there was a predominance of the recessive model in cyclists over field hockey players (OR: 0.00, 95% CI: 0.00-0.35, p = 0.002). Our study shows a significant difference between cyclists and field hockey players in terms of the genotypic and allelic frequency of the SNP rs1761667 of the CD36 gene. This divergence suggests a probable association between genetic variations in the CD36 gene and the type of sport in elite Moroccan athletes.