Józef Piłsudski University of Physical Education in Warsaw

BackgroundNon-communicable diseases are a growing public health challenge, shaped not only by biological predispositions but also by geo-demographic, socioeconomic, psychological, and lifestyle factors. A comprehensive understanding of these determinants is essential for developing targeted public health strategies. This study aimed to examine the multifactorial determinants of individual health status by analyzing geo-demographic, socio-economic, behavioral, psychological, and lifestyle variables.MethodsData were collected from 4,010 participants (age: 37.2 ± 15.4 years; 59.5% female) across 10 Mediterranean and neighboring countries using the multinational MEDIET4ALL e-survey. Health status was categorized as healthy, at-risk, or with diseases. Multinomial logistic regression, Quade’s Rank ANCOVA and series of multiple regression models were conducted.ResultsCollectively, around 25% of respondents declared to be at-risk of or with known disease. BMI emerged as the strongest negative predictor of health status (β = −0.145), with both obesity and underweight significantly increasing the odds of being at risk (OR = 1.8 and 5.2, respectively) and having diseases (OR = 2.2 and 11.9, respectively). Other significant negative predictors included psychological distress (notably anxiety, β = −0.091), insomnia (β = −0.084), alcohol consumption (β = −0.053), and prolonged sitting time (β = −0.037). Conversely, life satisfaction was the strongest significant protective factor (β = 0.066), followed by higher education, better sleep quality, and adherence to the Mediterranean Diet and lifestyle (β = 0.034 to 0.050). Socio-economic disparities, including employment status (β = −0.045) and living environment (β = −0.031), also significantly influenced health outcomes with rural environment and employed individual showing lower odd ratios of being at-risk and/or having diseases (p < 0.001). Furthermore, individuals residing in Mediterranean regions, females, married or cohabiting individuals, and non-smokers exhibited significantly lower odds of being at-risk or having diseases (p < 0.05). While gender remained a significant predictor in the final refined comprehensive regression model (β = −0.049), marital status lost significance, suggesting that its protective effect may be mediated by psychological well-being and health-related behaviors.ConclusionThese findings highlight the complex interplay of lifestyle, mental health, and socio-environmental factors in determining health outcomes, while emphasizing the urgent need for multi-level public health interventions, including policies promoting physical activity, healthy eating, mental well-being, and equitable healthcare access. Future research should employ longitudinal designs to establish causal relationships and guides preventive strategies.

Evidence on the comparative effectiveness of random, learner-adaptive, and self-controlled practice schedules among skilled athletes remains limited. Their effects on motor learning and performance in applied table tennis settings require further investigation. The present study examined the motor performance and learning effects of random, learner-adaptive, and self-controlled practice schedules on table tennis stroke accuracy in highly skilled players. Forty-eight highly skilled table tennis players were assigned to one of four groups: random practice, learner-adaptive practice, self-controlled practice, and a no-practice control group. The self-controlled group regulated task difficulty and serving parameters during practice, whereas these variables were externally controlled in the random and learner-adaptive practice groups. During the acquisition phase, participants completed a total of 630 practice trials distributed across seven practice sessions. Performance was assessed during acquisition, immediate retention, delayed retention, and transfer tests using linear mixed-effects models. The results demonstrated significant improvements in performance across acquisition sessions for all practice groups. During the final acquisition session, the self-controlled group demonstrated lower performance compared with the random and learner-adaptive groups. During immediate retention, all practice groups outperformed the control group; however, no statistically significant differences were observed between the three practice groups. Similarly, no differences were found between the practice groups during delayed retention. During the transfer test, the random practice group demonstrated significantly superior performance relative to the self-controlled group, whereas the learner-adaptive group outperformed the control group. No statistically significant differences were observed between the random and learner-adaptive practice groups during transfer performance. These findings suggest that random practice remains an effective practice schedule for promoting transfer performance in highly skilled table tennis players, whereas the specific rule-based Win-Shift/Lose-Stay learner-adaptive procedure used in this study did not provide additional learning benefits beyond random practice. Given the additional monitoring and adjustment required to implement this adaptive procedure, random practice may represent a simpler and equally effective option in practice. Moreover, the additional choices available in the self-controlled condition may have contributed to increased task difficulty, which could have limited transfer performance.

Introduction. Although physical activity provides numerous health benefits, increased intra-abdominal pressure (IAP), generated during physical exertion, may also have negative consequences. The aim of the study was to assess the relationship between the type of undertaken training and the extent of rectus abdominis diastasis. Material and methods. The study included 88 healthy and physically active women aged 18–30 years. The participants completed an author-designed questionnaire. The following were assessed: rectus abdominis diastasis (curl-up test), level of physical activity (IPAQ-SF), joint hypermobility (Beighton scale), and WHR (measured using a measuring tape). Due to the intensity of undertaken training, the participants were assigned to one of four groups. Results. Rectus abdominis diastasis (RAD) was diagnosed in 39% of the participants. A significant relationship was demonstrated between RAD and the intensity and frequency of undertaken training (p < 0.001), as well as the overall level of physical activity (p = 0.001). A significant correlation was found between RAD and BMI (p = 0.036), waist circumference (p = 0.041), and joint hypermobility (p = 0.009). Conclusions. The results of this pilot study indicate the need for individual assessment of joint hypermobility in women undertaking high-intensity training and require further prospective studies.

Movement quality and postural control are crucial for performance and injury prevention in team-sport athletes. Although FMS and YBT are commonly used, their ability to predict injury risk is limited when used alone. Therefore, integrating functional assessment with body composition and biochemical markers may provide a more comprehensive evaluation of athletes’ functional status. The study aimed to investigate the relationships among functional performance, body composition, and chosen biochemical markers in young men's team-sport athletes. The study involved 48 young Polish male professional team-sport athletes (football, futsal, handball, volleyball, rugby), divided into lower-limb (Group 1, n = 34) and upper-limb dominance groups (Group 2, n = 14). Body composition, functional performance (FMS, Y Balance Test), training characteristics, and blood biomarkers of stress, muscle damage, and inflammation were assessed. Selected anthropometric, functional, and biochemical parameters were compared between groups. Significant differences were observed mainly in body composition, with Group 2 demonstrating higher BMI, fat mass percentage, fat-free mass, and total body water (p ≤ 0.05; Hedges’ g = 0.64–0.89). Training experience was significantly longer in Group 1, while no differences were found in age or height. Functional performance assessed using FMS and YBT did not differ significantly between groups. Similarly, no significant differences were observed in biochemical markers, including cortisol, CK, CRP, IL-6, TNF-α, and TGF-β. The ANCOVA analysis showed that body weight had a significant effect on cortisol (F = 6.22, p = 0.02) and CRP levels (F = 58.45, p < 0.001), whereas training experience significantly affected CK activity (F = 4.63, p = 0.04). Despite differences in body composition between the groups, functional movement quality, dynamic balance, and biochemical markers were comparable. However, body weight and training experience significantly influenced selected biochemical indicators, suggesting their role in shaping physiological responses to training.