Predictors of Athlete’s Performance in Ultra-Endurance Mountain Races

Background: In previous studies, ultra-endurance performance has been associated with training and psychological variables. However, performance under extreme conditions is understudied, mainly due to difficulties in making field measures. Aim: The aim of this study was to analyze the role of training, hydration, nutrition, oral health status, and stress-related psychological factors in athletes’ performance in ultra-endurance mountain events. Methods: We analyzed the variables of race time and training, hydration state, nutrition, oral health status, and stress-related psychological factors in 448 ultra-endurance mountain race finishers divided into three groups according to race length (less than 45 km, 45–90 km, and greater than 90 km), using a questionnaire. Results: Higher performance in ultra-endurance mountain races was associated with better oral health status and higher accumulative altitude covered per week as well as higher positive accumulative change of altitude per week during training. In longer distance races, experience, a larger volume of training, and better hydration/nutrition prior to the competition were associated with better performance. Conclusions: Ultra-endurance mountain athletes competing in longer races (>90 km) have more experience and follow harder training schedules compared with athletes competing in shorter distances. In longer races, a larger fluid intake before the competition was the single best predictor of performance. For races between 45 and 90 km, training intensity and volume were key predictors of performance, and for races below 45 km, oral health status was a key predictor of performance. Psychological factors previously reported as ultra-endurance mountain race performance predictors were inconsistent or failed to predict the performance of athletes in the present research

Muscle damage and inflammation biomarkers after two ultraendurance mountain races of different distances: 54 km vs 111km

The aims of this study were 1) to describe the effects of a 54 km and 111 km ultra-endurance mountain race on the biomarkers of muscle damage and inflammation, 2) to compare the effects between the two races regarding the biomarkers of muscle damage and inflammation. Sixteen ultra-endurance amateur runners volunteered to participate in this study. Ten runners completed a 54 km race (Group 1; age: 27.0 ± 5.7; height: 179.5 ± 5.8 cm; and body mass: 77.3 ± 10.7 kg) and six completed a 111 km race (Group 2; age: 30.5 ± 8.0; height: 179.4 ± 5.5 cm; and body mass: 76.2 ± 9.4 kg). Blood samples were taken at five different points during the investigation, 24 h before the race, immediately post-race, and again at 24, 48, and 72 h after the race. There were increases in leukocyte (Group 1: p ≤ .001, ES = 2.8; Group 2: p = .001, ES = 3.5) and platelet concentrations (Group 1: p ≤ .001, ES = 2.3; Group 2: p = .02, ES = 1.7) post-races. Significant inter-race differences were also observed in leukocyte at 72 h (Group 1: 5.5 ± 0.9, Group 2: 4.2 ± 0.9, p = .012, ES = 1.5). Erythrocytes, hematocrit and hemoglobin concentration decreased after 54 km and 111 km races at 24, 48 and 72 h (p ≤.001, ES = 2.0–3.18). Serum uric acid concentration increased after the 54 km race (pre = 4.9 ± 1.2 – post = 7.3 ± 1.0 8 mg/dl; p ≤ .001, ES = 2.4), and also the 111 km race (pre = 5.3 ± 0.9 – post = 6.7 ± 0.8 mg/dl; p < .008, ES = 2.2). GPT, GOT and LDH had changed by the end of the races (p < .05) and differences between the groups were observed in GOT post-race (p = .008, ES = 1.7) 24 h (p = .004, ES = 1.8), 48 h (p = .007, ES = 1.6), and 72 h (p = .02, ES = 1.4) and also in LDH at 24, 48, 72 h. Serum creatinine decreased post-race in Group 1 (pre = 1.1 ± 0.1 – post = 1.4 ± 0.2 mg/dl; p = .001, ES = 1.5) and Group 2 (pre = 1.2 ± 0.1, post = 1.5 ± 0.2; p = .002, ES = 3.3) along with CK and myoglobin. In addition, values did not return to baseline levels after 72 h in Group 2 for C-reactive protein, myoglobin, and CK. Differences between the races were also observed post-race in Troponin I (Group 1 = 0.06 ± 0.05, 111 km = 0.02 ± 0.01 μg/l, p = .047, ES = 1.1) and C-reactive protein post-race (Group 2 = 2.5 ± 1.6, 111 km = 18.2 ± 6.4 mg/l, p ≤ .001, ES = 4.4) at 24 and 48 h. The athletes had increased concentrations of markers associated with damage, inflammation, muscle injury and cardiac damage after the races. Furthermore, athletes who completed the greater distance (111 km) had higher concentrations of the markers associated with muscle damage and muscle inflammation which remained changed for a period of 72 h. However, the participants of the ‘shorter race’ showed higher values associated with cardiac damage. Consequently, athletes who take part in these kinds of races should wait at least 72 h before training with high load.Actividad Física y Deport

Effectiveness of Reverse vs. Traditional Linear Training Periodization in Triathlon

The present research aimed to analyze the modification in performance, body composition, and autonomic modulation of reverse and traditional linear training periodization in amateur triathletes.We analyzed running and swimming performance, strengthmanifestation, body composition, and autonomic modulation before and after a traditional linear training periodization (four weeks of volume-based training plus four weeks of intensity-based training plus two-week tapering), a reverse linear training periodization (four weeks of intensity-based training plus four weeks of volume-based training plus two-week tapering), and a free training control physical active group (10-week free training) in 32 amateur athletes. Independently of the periodization model, the combination of two four-week mesocycles followed by a two-week taper is an e ciency strategy to avoid overreaching, obtaining an increase in parasympathetic modulation. Moreover, both types of training periodization proposed in this study do not modified body composition of amateur triathletes. Also, compared with traditional periodization, reverse periodization e ciently improves horizontal jump performance. Finally, reverse and traditional periodization were an e ective strategy to improve running biomechanical, performance, and physiological variables, as well as e cient periodization strategies to improve swimming technical ability, aerobic, and anaerobic swimming performance

Disordered Eating in Non-Elite Marathon Runners

The primary purpose of this study was to evaluate prevalence of disordered eating in non-elite marathon runners. Another purpose for this study was to analyze the difference in disordered eating prevalence between males and females, as well as, to evaluate the relationship of BMI categories and education levels with disordered eating.The participants for this study were recruited through running club directors throughout the states of Oklahoma, Arkansas, and Texas via email. Running club directors sent an email containing the information sheet on the study procedures and a hyperlink to the Qualtrics survey. The participants were required to fill out a two-part survey that included anthropometrics, demographics, marathon information, and the EAT-26 questionnaire.A total of 98 non-elite marathon runners participated in this study. There were 49 males and 49 females. Disordered eating risk was exhibited by 23 (23.5%) of the participants (EAT-26 ≥ 20). There was no significant difference in disordered eating risk (EAT-26 ≥ 20) between genders (p = .057) There was also no significant difference found in the EAT-26 subscales Dieting (D) (p = .221), Food Preoccupation (FP) (p = .133), and Oral Control (OC) (p = .062) between males and females. There was no significant difference found in EAT-26 total scores between the BMI categories, normal and overweight (p = .858). There was a significant relationship between the BMI categories and the subscale OC (p = .038). There was a significant negative correlation between BMI and subscale OC (r = -.228, p = .024). There was no significant difference found in EAT-26 total scores or subscales between the education levels (total p = .620; D p = .842, FP p = .227, and OC p = .600).Non-elite marathon runners are a population that could benefit from dietary education, specifically education on binge eating. Further research should explore BMI and the subscale Oral Control.Nutritional Science

Sports Medicine and Physical Fitness

Sports Medicine and Physical Fitness has been a successful Special Issue, which addressed novel topics in any subject related to sports medicine, physical fitness, and human movement. The article collection was able to positively evaluate three systematic reviews, nineteen original articles, and one brief report. These encompassed a broad range of topics ranging from accident kinematics, soccer monitoring, children’s physical evaluation, adapted physical activity, physical evaluation for people with intellectual disabilities, performance analysis in rowers, ultramarathon racers, karateka’s, rugby players, volleyball and basketball players, and cross-fit athletes, and also aspects related to biomechanics, fatigue and injury prevention in racing motorcycle riders, gymnasts, and cyclists.These scientific contributions within the field of Sports Medicine and Physical Fitness broaden the understanding of specific aspects of each analyzed discipline.It has been a pleasure for the Editorial Team to have served the International Journal Of Environmental Research and Public Health

Fitness Assessment, Athlete’s Monitoring Cycle and Training Interventions in Team Sports

Team sports training are progressively growing, and thus challenging strength and conditioning coaches and head coaches. As part of a well-prepared training strategy, it is important to establish a functional relationship among fitness assessment, load, and well-being monitoring and readiness analysis to identify the consequences of training stimulus for players. Each of these topics has already been isolated in research; however, it is important to bridge the gap between them and establish a greater and more comprehensive approach among fitness adaptations, training monitoring, and specific interventions performed. This may help us to achieve a clearer view of the big picture in terms of the consequences for players, such as, considering their exposure to successful biological adaptations or less successful cases, including illness or injuries. As it is clear that more research should be performed on the relationship among these dimensions and topics, the aim of the Special Issue on "Fitness Assessment, Athlete’s Monitoring Cycle and Training Interventions in Team Sports" was to publish high-quality original investigations, systematic reviews, and meta-analysis in the research field of team sports. We have published 22 articles that cover the topics of performance assessment and relationships between fitness measures; training load monitoring, well-being, and readiness in team sports;training interventions; complementary strategies for performance (e.g., nutrition, supplementation, psychology, injury preventions, and recovery); and determinants of illness and injuries in players

Use of bioimpedianciometer as predictor of mountain marathon performance

This study aimed to examine the relation among body composition, training experience and race time during a mountain marathon. Body composition and training pre-race experience analyses were conducted previous to a mountain marathon in 52 male athletes. A significant correlation between race time and mountain marathon with chronological age, body fat mass, percentage of body fat (BF), level of abdominal obesity, sport experience and daily training volume was revealed. In addition, BF and athlete’s chronological age were negatively associated with race performance. In contrast, the daily training volume was positively associated with mountain marathon time. A regression analysis showed that race time could be predicted (R2 = .948) by the daily training load, sports experience, age, body fat mass, BF and level of abdominal obesity. The comparison between performance groups regarding to body composition and training characteristics showed that the higher performance group was lighter with lower BF, fat mass and level of abdominal obesity, and with more days of training per week compared with the lower performance group (p < .05). Therefore, coaches and fitness trainers working with mountain marathon runners should develop exercise and nutritional strategies to reduce BF and consider increasing mean daily training volume to improve performance.Sin financiación2.098 JCR (2017) Q2, 46/94 Health Care Sciences and Services; Q3, 13/25 Medical Informatics0.619 SJR (2017) Q2, 27/190 Health Informatics, 12/64 Health Information Management, 83/1258 Information Systems, 1087/2878 Medicine (miscellaneous)No data IDR 2017UE