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.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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.

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.

Enhancing cardiometabolic health: unveiling the synergistic effects of high-intensity interval training with spirulina supplementation on selected adipokines, insulin resistance, and anthropometric indices in obese males.

This study investigated the combined effects of 12 weeks of high-intensity interval training (HIIT) and spirulina supplementation on adipokine levels, insulin resistance, anthropometric indices, and cardiorespiratory fitness in 44 obese males (aged 25-40 years). The participants were randomly assigned to one of four groups: control (CG), supplement (SG), training (TG), or training plus supplement (TSG). The intervention involved daily administration of either spirulina or a placebo and HIIT three times a week for the training groups. Anthropometric indices, HOMA-IR, VO2peak, and circulating adipokines (asprosin and lipocalin2, omentin-1, irisin, and spexin) were measured before and after the 12-week intervention. Post-intervention analysis indicated differences between the CG and the three interventional groups for body weight, fat-free mass (FFM), percent body fat (%BF), HOMA-IR, and adipokine levels (p < 0.05). TG and SG participants had increased VO2peak (p < 0.05). Spirulina supplementation with HIIT increased VO2peak, omentin-1, irisin, and spexin, while causing decreases in lipocalin-2 and asprosin levels and improvements in body composition (weight, %fat), BMI, and HOMA-IR. Notably, the combination of spirulina and HIIT produced more significant changes in circulating adipokines and cardiometabolic health in obese males compared to either supplementation or HIIT alone (p < 0.05). These findings highlight the synergistic benefits of combining spirulina supplementation with HIIT, showcasing their potential in improving various health parameters and addressing obesity-related concerns in a comprehensive manner.

A single session of a beach volleyball exergame did not improve state anxiety level in healthy adult women.

This study evaluated the acute effect of the exergame Kinect Sports® beach volleyball on state anxiety level in adult women. Thirty healthy adult women (age: 21 [4] years, body mass: 54.70 [19.50] kg, height: 1.61 ± 0.05 m, and body mass index: 21.87 [5.76] kg/m2, data are expressed as median [interquartile range] and as the mean ± standard deviation) were assigned to play an exergame of beach volleyball in singleplayer mode session (intervention session) for ~ 30 min using the Xbox 360 Kinect® or remained seated (control session). State anxiety was evaluated before and after the intervention and control sessions through the State-Trait Anxiety Inventory. State anxiety obtained in both sessions (exergame and control) was classified as intermediate before (median: 36.00 [IQR: 4.75] and mean = 38.73 ± 7.23, respectively) and after (mean: 34.86 ± 6.81 and mean: 37.66 ± 8.44, respectively). Friedman test found no time significant effect on state anxiety of the sessions (χ2 [3] = 6.45, p-value = 0.092, Kendall's W = 0.07 "trivial"). In conclusion, the present study showed that there were no significant differences in the state anxiety level after an acute session of the exergame beach volleyball.

KEY POINTS: • Exergame beach volleyball presented high enjoyment and a moderate to strong future engagement possibility. • A session of the volleyball exergame did not improve affectivity and state anxiety level compared with control condition. • A session of the volleyball exergame elicited moderate physical exercise intensity.

Origin and age group of the fastest amateur triathletes competing in 'Ironman Hawaii' between 2003 and 2019.

Little is known about the prevalent nationalities among the best-placed athletes participating in "Ironman Hawaii." Moreover, the age at which athletes achieve their best performances remains unclear. The present study aimed to compare the prevalent nationalities among the athletes, their respective placement among the top five, and the performance difference between the different age groups in 'Ironman Hawaii' from 2003 to 2019. A total of 30 354 amateur triathletes were selected from the Obsessed Triathlete (OBSTRI) website. A "TOP 5" division filter was applied for further analysis, resulting in 1 851 athletes being included in this study. Among the male runners, Americans participated the most in Ironman events (39%), followed by Germans (10%). Among female runners, Americans participated the most (54%), followed by Australian runners (8%). Male Americans also featured most among the top five (30%), followed by Germans (16%). Female Americans were the most prevalent among the top five (47%), followed by Australian Americans (10%). There were no significant performance differences (p â€‹> â€‹0.05) between the 25-29 and 40-44 age groups for either sex. The 45-49 age group presented significantly worse performance than the 35-39 age group for both sexes (p â€‹< â€‹0.001). North Americans were the most performant and frequent participants in "Ironman Hawaii." The expected performance decline due to aging was observed after 45 years in both sexes.

Maximal Oxygen Uptake, Muscular Oxidative Capacity, and Ventilatory Threshold in Amateur Triathletes: Eight-Month Training Follow-Up.

Purpose: Endurance sports performance is influenced by several factors, including maximal oxygen uptake (⩒O2max), the percentage of ⩒O2max that can be sustained in endurance events, running economy, and body composition. Traditionally, ⩒O2max can be measured as an absolute value, adjusted for body mass, reflecting the athlete's central capacity (maximal cardiac output), or adjusted for lean mass (LM), reflecting the athlete's peripheral capacity (muscular oxidative capacity). The present study aims to evaluate absolute, total body mass, and lower limb LM-adjusted ⩒O2max, ventilatory thresholds (VT), respiratory compensation points (RCP), and body composition during two training periods separated by 8 months. Patients and Methods: Thirteen competitive amateur triathletes [seven men (40.7±13.7 years old, 76.3±8.3kg, and 173.9±4.8cm) and six women (43.5±6.9 years old, 55.0±2.7kg, 164.9±5.2cm)] were evaluated for body composition with dual-energy X-ray absorptiometry and ⩒O2max, VT, RPC, and maximal aerobic speed (MAS) with a cardiorespiratory maximal treadmill test. Results: The absolute ⩒O2max (p = 0.003, d = 1.05), body mass-adjusted ⩒O2max (p < 0.001, d = 1.2859), and MAS (p = 0.047, d = 0.6139) values differed significantly across evaluation periods. Lower limb LM-adjusted ⩒O2max (p = 0.083, d = -0.0418), %⩒O2max at VT (p = 0.541, d = -0.1746), speed at VT (p = 0.337, d = -0.2774), % ⩒O2max at RCP (p = 0.776, d = 0.0806), and speed at RCP (p = 0.436, d = 0.2234) showed no difference. Conclusion: The sensitivities of ⩒O2max adjusted for body mass and ⩒O2max adjusted for LM to detect changes in physical training state differ. Furthermore, decreases in physical fitness level, as evaluated by ⩒O2max values, are not accompanied by changes in VT.

Effects of swimming in cold water on lipolysis indicators via fibroblast growth factor-21 in male Wistar rats.

This study aimed to investigate the effects of swimming in cold water on the release of FGF21 from various tissues and its impact on fat metabolism. Twenty Wistar rats were randomly divided into three groups: untrained (C), trained in thermo-neutral water (TN, 30 °C) and trained in cold water (TC, 15 °C). The training groups swam intervals (2-3 min) until exhaustion, 1 min rest, three days a week for six weeks, with 3-6% bodyweight load. The mRNA expression of variables was determined in white fat tissue (WAT), and FGF21 protein was also measured in the liver, brown fat tissue (BAT), serum, and muscle. The experimental protocols resulted in lower body weight gain, associated with reduced WAT volume; the most remarkable improvement was observed in the TC group. Swimming significantly increased FGF21 protein levels in WAT, BAT, and muscle tissues compared to the C group; substantial increases were in the TC group. Changes in FGF21 were highly correlated with the activation of genes involved in fat metabolisms, such as CPT1, CD36, and HSL, and with glycerol in WAT. The findings indicate a positive correlation between swimming in cold water and the activation of genes involved in fat metabolism, possibly through FGF21 production, which was highly correlated with fat-burning genes.

Cycling is the most important predictive split discipline in professional Ironman® 70.3 triathletes.

Introduction: Our study examined 16,611 records of professional triathletes from 163 Ironman® 70.3 races across 97 countries (2004-2020). The aim was to identify the most predictive discipline-swim, bike, or run-for overall race time. Methods: We used correlation matrices to compare the dependent variable "finish time" with independent variables "swim time," "bike time," and "run time." This analysis was conducted separately for male and female athletes. Additionally, univariate and multiple linear regression models assessed the strength of these associations. Results: The results indicated that "bike time" had the strongest correlation with finish time (0.85), followed by "run time" (0.75 for females, 0.82 for males) and "swim time" (0.46 for females, 0.63 for males). Regression models confirmed "bike time" as the strongest predictor of overall race time (R² = 0.8), with "run time" and "swim time" being less predictive. Discussion: The study concludes that in Ironman 70.3 races, "bike time" is the most significant predictor of overall race performance for both sexes, suggesting a focus on cycling in training and competition strategies. It also highlights a smaller performance gap between genders in swimming than in cycling or running.