Federica Moro

Background and Aims: Body composition (BC) plays a key role in assessing athletes' health. However, many factors, including sex and performance rank, may influence BC and should be considered when assessing it. Moreover, BC is estimated indirectly, and body volume (BV) represents a key component of densitometric assessment. This investigation aimed to compare swimmers' BC across sexes and performance ranks, compare methods for BF estimation, and develop a model for predicting BV. Methods: This was a cross‐sectional study. Participants underwent air‐displacement plethysmography (ADP), anthropometric measurements, and bioimpedance analysis (BIA) according to standardized procedures. Sixty‐four competitive (13.6 ± 1.9 training hours per week) swimmers (17.8 ± 4.4 years, 56.3% male; 13.6 ± 1.9 training hours per week) were enrolled from the national competitive list. They were stratified by sex and classified into three groups according to performance rank (Best World Aquatic score, BWA). A two‐way ANCOVA (sex and rank), adjusted for age, was used to compare BC variables. A bootstrap model‐averaging approach was used to select a linear regression model for predicting BV. Results: Males showed higher BV, total body water (TBW), and fat‐free mass (FFM) than females. Most rank‐related differences were attenuated after adjustment for age; however, BWA showed a strong positive correlation with limb girths and FFM (Pearson rho > 0.5). BF estimated using specific cut‐offs exhibited the lowest error propagation (reduction of 6.42%). The best model was selected with a 18.81% frequency (adjusted R ² = 0.981; RMSE = 1.541), and the variables that showed an adequate bootstrap inclusion frequency (> 60%) were stature ( β = 0.342), stretched arm ( β = 0.905), hip ( β = 0.117), thigh ( β = 0.659) and calf ( β = 0.508) girths, with a mean relative conditional bias of 1.79%. Conclusion: The proposed BF estimation method showed lower error propagation in this sample, while the anthropometric model provided an accurate internal prediction of BV. These findings support the use of predicted BV for subsequent BF estimation using specific cut‐offs, although external validation of the BV prediction model is required.

Importance: Physical activity (PA) may mitigate adverse changes in body composition (BC) and body image (BI) in postmenopausal women; however, the magnitude and consistency of its effects remain unclear. Objective: To systematically review and synthesize evidence from experimental studies examining the effects of structured PA interventions on BC parameters and BI perception in postmenopausal women (PROSPERO: CRD42024539791). Evidence review: MEDLINE, Web of Science, and Scopus were searched for randomized controlled trials published in English from 2014 to 2025 reporting BC and/or BI outcomes. Risk of bias and certainty of evidence were assessed using the RoB 2.0 tool and the GRADE approach. Pooled mean differences (MDs) with 95% CIs were estimated using a random-effects model for body mass index (BMI), percentage of fat mass (%F), and waist-to-hip ratio (WHR). Findings: After duplicate removal, 2,483 records were screened, and 13 trials involving 694 postmenopausal women met the inclusion criteria. Most studies had a low risk of bias or some concerns. Despite wide variation in frequency, intensity, type, and duration of PA interventions, meta-analyses suggested significant reductions ( P < 0.001) in BMI (MD = −0.87 kg/m ² ; 95% CI: −1.20 to −0.55), %F (standardized MD: −0.53; 95% CI: −0.81 to −0.26), and WHR (MD = −0.03; 95% CI: −0.04 to 0.02). The heterogeneity was low for BMI and WHR (I ² = 0%) and moderate for %F (I ² = 57%) despite considerable within-study variability. Evidence on BI was limited and inconclusive, with only one study reporting preintervention and postintervention data. Conclusions and relevance: Structured PA appears to improve key BC parameters in postmenopausal women. Evidence regarding BI is insufficient, emphasizing the need for rigorous, long-term trials to clarify PA’s effects on BI. These findings may guide clinicians in recommending PA for postmenopausal women to improve BC, while highlighting a critical gap in evidence regarding BI.

Objectives: To examine disordered eating behaviors, orthorexic tendencies, binge-eating episodes, attitudes toward exercise, perceived hormone-related symptoms and body image perception among competitive bodybuilders across different levels of competitive experience. Methods: In this cross-sectional study, 60 competitive bodybuilders (29 men, 31 women) completed an anonymous online questionnaire. The survey evaluated demographic characteristics, coaching and training management, phase-specific symptoms (such as libido, sleep, eating behaviors, and menstrual alterations), orthorexic tendencies, exercise addiction, and body-image perception. Results: Both sexes reported reduced libido, increased hunger, and sleep disturbances, along with frequent weight monitoring and common binge-eating episodes. Moreover, females frequently reported menstrual irregularities. ORTO-15 scores indicated a potential risk of orthorexia nervosa, while EAI-3 scores suggested a risk of exercise addiction in novice females and advanced males, with differences in mood regulation and guilt across sex and experience. Males showed higher perceived and ideal muscle mass, whereas females reported higher perceived body fat and a preference for leaner physiques. Conclusions: Competitive bodybuilders of both sexes exhibit post-competition binge eating, mood- and appearance-driven exercise behaviors, and pronounced body-image concerns. Screening, education on energy availability, structured post-competition support, and health-focused coaching are recommended to prevent the progression from sport-specific practices to clinical pathology.

Background Physical ability and body composition affect players’ health. Understanding body features and using valid methods to evaluate them is crucial in football at all ages. Methods This was a cross-sectional study with a cross-validation design that aims to compare body composition in competitive women's football between adolescents and adults and to validate new methods for predicting body volume (BV) and estimating body fat (BF). Eighty players (62.5% adults, body mass (BM) = 59.98 ± 6.69, stature = 165.32 ± 6.19) from Italian Serie A participated in the study. Air-displacement plethysmography (ADP), anthropometry, and bioimpedance analysis (BIA) were assessed according to reference standards. Five different models were computed to estimate body fat from body density. The one-way ANOVA compared age categories, while the stepwise procedure selected the best regressors for model predictions. The paired student test compared the first assessment and cross-validation outcomes, while the Bland-Altman method checked for bias. Results Adult players were heavier (+ 10.69%), taller (+ 2.83%), and reported larger limb circumferences. Whilst their BV was higher (+ 9.89%), the rate of BM was ~ 8% higher, resulting in lower BF across most models, and wider body water (TBW) mass. BV was strongly related to circumferences (p < 0.001), resulting in the best prediction (adj. R ² = 95.04%, with 99.97% accuracy, 97.69% precision, and 94.5% reliability). Conclusion Women’s players need specific references to achieve optimal seasonal goals, and validated methods and guidelines are mandatory for evaluating and monitoring their health.

Objective: Since specific bioelectrical reference values for Italian adults are lacking, this study aims to define specific values and test their suitability in pathological cases and athletes. Methods: A sample of 1049 Italian individuals (441 men, 608 women) aged 30–65 years was considered. Competitive athletes (bodybuilding, streetlifting and tennis) were identified within the general sample, and an independent group of individuals with obesity or anorexia nervosa was analyzed for comparison. Anthropometric (weight, kg; stature, mid-upper arm, waist and calf circumferences; cm) and bioelectrical (resistance and reactance, at 50 kHz) variables were taken. Resistivity, (Rsp, Ωcm), reactivity (Xcsp, Ωcm), impedivity (Zsp, Ωcm) and phase angle (PhA, °) were calculated. Two-way ANOVA and Hotelling’s T² test were applied to assess group differences. These data were then pooled with existing datasets to create a comprehensive reference for individuals aged 18 to 100 years. Results: The specific bioelectrical variables were: Rsp = 352.3 ± 55.5, Xcsp = 41.8 ± 9.1, PhA = 6.8 ± 1.0, r (Rsp, Xcsp) = 0.67 (men); Rsp = 384.9 ± 71.2, Xcsp = 40.7 ± 9.4, PhA = 6.1 ± 1.0, r (Rsp, Xcsp) = 0.72 (women). Men showed higher PhA values (p < 0.001), reflecting higher muscle mass and quality, and shorter vectors (p < 0.001), indicative of lower relative fat mass (FM%), than women. Advancing age was associated with lower PhA and longer vectors (p < 0.001). Bioelectrical vectors of individuals with obesity or anorexia nervosa were outside the 95% variability, indicating abnormal values of FM%, whereas those of athletes fell within the lower left quadrant. Conclusions: The specific tolerance ellipses for the Italian adult population fill a gap in the existing literature, providing essential new tools for evaluating body composition in clinical and sports settings, and for comparative analyses.

Elderly patients with femoral fractures need specific rehabilitation after surgery that aims to improve their self-reliance and life quality, reducing their mortality rate. Although worsening patient body composition increased the risk of an unfavourable prognosis, it remains unclear whether evaluating bioelectrical impedance analysis (BIA) parameters can predict any functional recovery. A longitudinal design was conducted on 45 elders (84.59 ± 7.18 years, 75.6% female) who underwent femoral surgery to examine BIA features as rehabilitation biomarkers. The patient’s body composition, assessed by anthropometry and bioimpedance analysis (BIA), and self-reliance were evaluated three times during follow-up in both healthy and surgical lower limbs. The ANCOVA test, adjusted for gender and side of surgery, found improvements in daily living activities, while only thigh circumferences decreased over time. Regarding the BIA, the surgical leg showed a wider decrement in bioelectrical resistance (R), whereas the bioelectric reactance (Xc) exhibited similar trends. Females who underwent surgery on their dominant leg showed significant changes (p < 0.001) in bioimpedance vectorial analysis (BIVA), with a linear trend from baseline to postoperative time, while males exhibited beneficial variations only between baseline and time 2 (p < 0.01). Geriatric patients exhibit characteristic traits that require additional attention. BIA may be a feasible and non-invasive method for monitoring patient prognosis and reducing national health system costs.

This study aimed to identify and compare the basic anthropometric characteristics, physical performance, and game-related skills of female soccer players across different age groups, including under-15 (U15), U17, U19, and first teams. Also, it aimed to account for performance tests variability through anthropometric features. A total of 56 athletes participated in a comprehensive test battery assessing anthropometric and bioelectrical parameters, air displacement plethysmography (ADP), and physical performance (Countermovement Jump Test (CMJ) and 30-15 _IFT ). The older groups outperformed the younger players in physical and physiological characteristics. Significant differences were observed in body dimensions and composition, with the first team showing higher fat-free mass (FFM) than U15 and U17 players. Skinfold thickness was consistent across groups. The first team also exhibited the highest levels of power and speed, while U15 athletes showed the lowest CMJ. General linear models by stepwise procedures identified training hours as the main predictor for CMJ and speed, with each additional hour of training improving CMJ by 1 cm and speed by 1 km/h. Additionally, a decrease in skinfold thickness predicted improved power. A multidimensional approach, including anthropometric, bioelectrical, and physical performance data, provides essential insights for supporting athletic development in young female soccer players and can inform tailored training strategies to enhance their physical performance.

The study of human body composition covers many fields, from clinical assessment to sports performance. Humans manifest different traits that set limitations in model estimation. This investigation aimed to (i) provide sport-specific densities for reducing biological variation in body composition assessment, and (ii) develop new regression models for body volume and density estimation by field applications. Thirty elite basketball players (16.84 ± 1.15 years; 188.48 ± 6.74 cm; 82.66 ± 12.23 kg) with a mean of 10.48 years of sport experience underwent anthropometric, bio-impedance (BIA) and air-displacement plethysmography (ADP) evaluations. Many models accounting for body fat percentage (BF) used the measured body mass (BM), volume (BV) and density (d) to analyse adipose and fat-free tissues. A new model payable for all players encompassed BF, with low error propagation (3.4% of BM). In addition, two new methods estimated BV by anthropometry (R² = 0.96, RMSE = 2.9%) or BIA (R² = 0.81, RMSE = 4.56%), with a high degree of precision (97.8 and 86.8%) and accuracy (100 and 99.6%). Body composition requires rigorous speculation, advanced instruments and high costs that could lead investigators to omit relevant concepts and produce estimation biases. Specific and easier methods may enhance its applicability.

In recent decades, extensive evidence has indicated that green spaces and physical activity (PA) are associated with mental health, while limited research has explored the combined effects of supervised PA in urban green spaces. To address the research gap, this study examines whether supervised PA within green spaces improves mental health among middle-aged adults (45–65 years) through a quasi-experimental longitudinal study developed as part of the “Moving Parks” project in Bologna, Italy. Using the Italian version of the Warwick–Edinburgh Mental Well-being Scale (WEMWBS), mental health was measured at pre- and post-assessment. A total of 340 participants (258 intervention, 82 control) were included in the study. The effects of intervention, group assignment, and their interaction on mental health scores were analysed using a two-way repeated measures ANOVA. No significant differences in mental health improvements were observed between the intervention group and control group. The results indicated significant main effects of time on total WEMWBS scores and several subscales such as optimism, usefulness, energy, and cheerfulness, but these changes were not significantly influenced by group assignment. The only significant group-by-time interaction was found in perceived usefulness. These findings do not provide conclusive support for the hypothesised benefits of the supervised PA intervention. Possible explanations include seasonal variation, baseline or ceiling effects, and the potential limitations of the WEMWBS in detecting short-term psychological changes. Future research should consider extending intervention duration, improving group comparability, and employing more sensitive assessment tools to better evaluate the mental health impact of green space–based PA programmes.