The present study aimed to determine the epidemiology of sport-related injuries in amateur and professional adolescent athletes and the incidence of different risk factors on those injuries. Four hundred ninety-eight athletes aged 14 to 21 voluntarily participated in this prospective injury surveillance, conducted from 1 January 2019 to 31 December 2019. The information collected included: personal data, sports aspects, characteristics of the injuries, and lifestyle. Forty point four percent of the participants suffered an injury in 2019 (39% of them in a previously injured area). The average injury rate was 2.64 per 1000 h. Soccer presented the highest rate (7.21). The most common injuries were: lumbar muscle strains (12.24%), ankle sprains (11.98%), and bone fractures (9.31%). Ankles (36.12%), knees (19.32%), and shoulders (6.47%) concentrated the highest number of injuries. Fifty-nine point twenty-eight percent of the injuries occurred during practices, and 40.72% during competition or peri-competition. Higher injury rates were associated (in this order) with the following factors: (a) Greater number of hours of practice per week. (b) Not performing warm-ups. (c) Using inadequate sports facilities. (d) Being aged 14–17. (e) Not performing physical preparation. (f) Inappropriate training load. (g) Not performing injury-preventive activities. (h) Performing sports technique without the supervision of one sports coach. (i) Inadequate sports equipment. In conclusion, since most injury risk factors are modifiable, it is imperative to implement strategies to reduce amateur and professional adolescent athletes’ injury rates.

This study aimed to estimate the effect of the coronavirus disease 2019 (COVID-19) quarantine on low back pain (LBP) intensity, prevalence, and associated risk factors among adults in Riyadh (Saudi Arabia). A total of 463 adults (259 males and 204 females) aged between 18 and 64 years and residing in Riyadh (Saudi Arabia) participated in this cross-sectional study. A self-administered structured questionnaire composed of 20 questions regarding demographic characteristics, work- and academic-related aspects, physical activity (PA), daily habits and tasks, and pain-related aspects was used. The LBP point prevalence before the quarantine was 38.8%, and 43.8% after the quarantine. The LBP intensity significantly increased during the quarantine. The low back was also the most common musculoskeletal pain area. Furthermore, during the quarantine, a significantly higher LBP intensity was reported by those individuals who (a) were aged between 35 and 49 years old, (b) had a body mass index equal to or exceeding 30, (c) underwent higher levels of stress, (d) did not comply with the ergonomic recommendations, (e) were sitting for long periods, (f) did not practice enough physical activity (PA), and (g) underwent teleworking or distance learning. No significant differences were found between genders. The COVID-19 quarantine resulted in a significant increase in LBP intensity, point prevalence, and most associated risk factors.

Objective: The present study aimed to verify the effects of running-specific strength training alone, endurance training alone, and concurrent training on recreational endurance athletes’ performance and selected anthropometric parameters. Method: Thirty male recreational endurance runners were randomly assigned using a blocking technique to either a running-specific strength training group (RSSTG), an endurance training group (ETG), or a concurrent training group (CTG). RSSTG performed three strength-training sessions per week orientated to running, ETG underwent three endurance sessions per week, and CTG underwent a 3-day-per-week concurrent training program performed on non-consecutive days, alternating the strength and endurance training sessions applied to RSSTG and ETG. The training protocol lasted 12 weeks and was designed using the ATR (Accumulation, Transmutation, Realization) block periodization system. The following assessments were conducted before and after the training protocol: body mass (BM), body mass index (BMI), body fat percentage (BFP), lean mass (LM), countermovement jump (CMJ), 1RM (one-repetition maximum) squat, running economy at 12 and 14 km/h (RE12 and RE14), maximum oxygen consumption (VO₂max), and anaerobic threshold (AnT). Results: RSSTG significantly improved the results in CMJ, 1RM squat, RE12, and RE14. ETG significantly improved in RE12, RE14, VO₂max, and AnT. Finally, CTG, obtained significant improvements in BFP, LM, CMJ, 1RM squat, RE12, RE14, VO₂max, and AnT. RSSTG obtained improvements significantly higher than ETG in CMJ, 1RM squat, and RE14. ETG results were significantly better than those attained by RSSTG in AnT. Moreover, CTG marks were significantly higher than those obtained by ETG in CMJ and RE14. Conclusion: Performing a 12-week concurrent training program integrated into the ATR periodization system effectively improves body composition and performance variables that can be obtained with exclusive running-specific strength and endurance training in recreational runners aged 30 to 40. Running-specific strength training enhances maximum and explosive strength and RE, whereas exclusive endurance training improves VO₂max, AnT, and RE. Performing concurrent training on non-consecutive days effectively prevents the strength and endurance adaptations attained with single-mode exercise from being attenuated. The ATR periodization system is useful in improving recreational endurance athletes’ performance parameters, especially when performing concurrent training programs.

Obesity is the excessive accumulation of adipose tissue in the body that leads to health risks. The study aimed to classify obesity levels using a tree-based machine-learning approach considering physical activity and nutritional habits. Methods: The current study employed an observational design, collecting data from a public dataset via a web-based survey to assess eating habits and physical activity levels. The data included gender, age, height, weight, family history of being overweight, dietary patterns, physical activity frequency, and more. Data preprocessing involved addressing class imbalance using Synthetic Minority Over-sampling TEchnique-Nominal Continuous (SMOTE-NC) and feature selection using Recursive Feature Elimination (RFE). Three classification algorithms (logistic regression (LR), random forest (RF), and Extreme Gradient Boosting (XGBoost)) were used for obesity level prediction, and Bayesian optimization was employed for hyperparameter tuning. The performance of different models was evaluated using metrics such as accuracy, recall, precision, F1-score, area under the curve (AUC), and precision–recall curve. The LR model showed the best performance across most metrics, followed by RF and XGBoost. Feature selection improved the performance of LR and RF models, while XGBoost’s performance was mixed. The study contributes to the understanding of obesity classification using machine-learning techniques based on physical activity and nutritional habits. The LR model demonstrated the most robust performance, and feature selection was shown to enhance model efficiency. The findings underscore the importance of considering both physical activity and nutritional habits in addressing the obesity epidemic.

Significant back pain prevalence and intensity are reported in female pedagogues. Due to the COVID-19 pandemic, they have been exposed to remote working conditions, higher psychological demands, and stress. Our objective was to evaluate the back pain prevalence, intensity, and related risk factors in female teachers from Slovak regions in the context of remote learning during the COVID-19 pandemic. An electronic questionnaire was applied for data collection. A total of 782 adult female teachers (age 43.11 ± 0.36, BMI 34.94 ± 5.94) from primary, secondary, and tertiary schools from Slovak regions were included in the survey. Of these, 74% reported cervical pain, 67% lower back pain, and 60% pain in more than one vertebral region. The highest pain intensities were reported in the following cohorts (pain scale 1–5, 1 = no pain, and 5 = extreme pain): pedagogues from the Presov region (3.74), those working in the special education sector (3.83), those who gave five online classes a week (3.58), those who performed no physical activity (PA, 3.86), pedagogues who did not work in compliance with ergonomic recommendations (3.59), those with moderate or severe stress (3.66), and those who were sitting all or most of the time (3.62). The main risk factors identified were: no PA performed, no compliance with ergonomic recommendations, and stress.

Sleep is essential for a range of physiological and mental functions in professional athletes. There is proof that athletes may experience lower quality and quantity of sleep. While adequate sleep has been shown to have restorative effects on the immune system and endocrine system, facilitate nervous system recovery and the metabolic cost of wakefulness, and play a significant role in learning, memory, and synaptic plasticity, which can affect sports recovery, injury risk reduction, and performance. Sports performance may suffer significantly from a lack of sleep, especially under maximal and long-term exercise. Due to the potential harm, these factors may do to an athlete's endocrine, metabolic, and nutritional health, sports performance is impacted by reduced sleep quality or quantity. There are several neurotransmitters associated with the sleep–wake cycle that have been discovered. They comprise cholinergic hormone, orexin, melanin, galanin, serotonin, gamma-aminobutyric acid, histamine, and serotonin. Therefore, dietary modifications that affect the neurotransmitters in the brain also may affect sleep; particularly for athletes who require more physical and psychological recovery owing to the tremendous physiological and psychological demands placed on them during training and performance. This review explores the variables that influence the quantity and quality of sleep-in populations of athletes and assesses their possible effects. In addition, several recommendations for improving sleep are presented. Even though there has been much research on variables that impact sleep, future studies may highlight the significance of these aspects for athletes.