Background/Objectives: Recovery nutrition must restore near-term readiness without indiscriminately suppressing biological signals that contribute to repair and training adaptation. This review evaluates recovery-adaptation coupling (RAC) as a research framework and clarifies its contribution relative to established recovery, nutrient-periodization, and athlete-monitoring models. Methods: Targeted narrative searches of PubMed/MEDLINE, Scopus, and Web of Science were supplemented by Google Scholar citation tracking and backward and forward screening. Peer-reviewed English-language literature available through 31 May 2026 was considered. Human athlete studies, randomized trials, systematic reviews, meta-analyses, consensus statements, and position stands were prioritized; mechanistic evidence was used to explain pathways rather than to support stand-alone performance recommendations. The final cited corpus comprised 130 records. No formal risk-of-bias tool, certainty grading, PRISMA denominator, or quantitative pooling was used. Claims were instead identified as established practice (EP), context-dependent evidence (CDE), mechanistic rationale (MR), or RAC hypothesis (RH). Results: The most consistent applied support concerns adequate energy availability, distributed high-quality protein, carbohydrate restoration when recovery windows are short, and individualized fluid and sodium replacement. Evidence for polyphenol-rich products, curcumin, omega-3 fatty acids, and creatine is context- and product-dependent. Collagen or gelatin evidence is mainly mechanistic or pilot-level, while RAC recovery-pattern categories and multimodal monitoring rules remain unvalidated hypotheses. RAC differs from existing frameworks by jointly specifying the next athletic demand, dominant recovery bottleneck, possible adaptive cost of intervention, and response-verification plan. Conclusions: RAC should presently be interpreted as an evidence-organization and hypothesis-generation architecture, not as a validated predictive, diagnostic, or treatment algorithm. Prospective comparative studies are required before RAC-specific decision rules can guide individualized practice.

Background/Objectives: Recovery between exercise exposures is often framed as the rapid suppression of soreness, inflammation, oxidative stress, and fatigue, although the same perturbations may also initiate tissue repair and training adaptation. This review proposes recovery-adaptation coupling (RAC) as a decision framework for matching nu-tritional strategies to recovery bottlenecks while preserving adaptive signals. Methods: A mechanistic narrative synthesis integrated evidence on exercise-induced muscle dam-age, inflammation resolution, immune-redox regulation, muscle protein turnover, glyco-gen restoration, connective-tissue remodeling, micronutrient sufficiency, nutrient timing, individual variability, and recovery monitoring. Results: RAC links four tar-gets—damage attenuation, inflammation resolution, anabolic remodeling, and adaptive signal preservation—to the next athletic demand, the dominant recovery bottleneck, and the markers used to verify response. Nutritional strategies are interpreted according to context, dose, timing, and response phenotype. Conclusions: RAC is a heuristic decision architecture rather than a validated universal algorithm; it aims to restore readiness without indiscriminately suppressing the signals required for longer-term adaptation.

Body composition is a key factor in volleyball performance, but research on female athletes has largely focused on only a few general traits. This study compared elite and sub-elite female volleyball players using a multilevel body composition framework to compare structural and potentially modifiable characteristics across competitive levels. Forty female volleyball players were assessed and classified as elite (n = 15) or sub-elite (n = 25). Body composition was assessed using anthropometry and ultrasound. Elite players were taller (183.1 ± 8.2 vs. 170.7 ± 8.8 cm), heavier (76.0 ± 8.5 vs. 65.8 ± 9.1 kg), and displayed distinct body proportions compared with sub-elite players. The elite group also showed higher skeletal muscle index (SMI: 8.1 ± 0.7 vs. 7.3 ± 0.7 kg·m−2) and lower fat mass percentage (22.3 ± 2.2 vs. 25.3 ± 4.4%). However, differences in adiposity were attenuated when normalized for stature using fat mass index (FMI: 5.1 ± 0.8 vs. 5.8 ± 1.5 kg·m−2). Ultrasound-derived data indicated greater regional muscularity in elite players, whereas no differences were observed in the sum of adipose tissue layers, consistent with anthropometric skinfolds. The muscle-to-bone ratio did not differ between groups, suggesting proportional development of muscle and bone mass. Elite female volleyball players were characterized by greater structural dimensions and muscularity, whereas FMI appeared more informative than FM% for assessing adiposity.

BACKGROUND:The ketogenic diet (KD) is a widely used nutritional intervention for weight loss. The beneficial effects of the KD are intrinsically linked to the state of physiological ketosis, where ketone bodies (KBs) raise, even though minimal effective threshold of blood ketone concentration that correlates with significant weight loss remains unclear. Therefore, the main purpose of this study was to identify the optimal β-hydroxybutyrate (βHB) threshold associated with weight loss in individuals with overweight or obesity undergoing a KD. METHODS:This secondary analysis included 217 participants (111 males and 106 females) with overweight or obesity, who followed a KD for 14 days. Time to Ketosis (TtK)-defined as the number of days needed to reach and maintain a given ketone concentration-was calculated for each threshold. RESULTS:Regression analysis showed that a βHB concentration of ≥0.5 mmol/L was the most associated with significant weight loss. Moreover, body weight and gender significantly influenced TtK, suggesting interindividual variability in achieving effective ketosis. CONCLUSIONS:Achieving and maintaining a ketonemia of at least 0.5 mmol/L may represent a clinically meaningful threshold to optimize weight loss in individuals undergoing a KD. Monitoring βHB levels and reducing TtK may improve individual responsiveness to KD-based interventions.

Background and aims: Accurate assessment of body composition in field settings remains challenging, as commonly used techniques such as anthropometry, bioelectrical impedance analysis (BIA), and ultrasound (US) provide only partial and method-specific information. This study investigated whether integrating these approaches improves the prediction of fat mass (FM) and appendicular lean soft mass (ALSM). Methods Ninety-six adults (42 women, 54 men; 18–84 years) were assessed using surface anthropometry, foot-to-hand BIA, and B-mode US. Dual-energy X-ray absorptiometry served as the reference method. Bivariate correlations and multiple linear regression models adjusted for sex and age were used to evaluate the independent predictive value of each technique, whereas hierarchical models tested the incremental explained variance (ΔR²) obtained by combining methods. To facilitate model integration, only selected anthropometric variables were retained in the hierarchical analyses. Results For FM, anthropometry showed the highest predictive power (R²=0.87), followed by US (R²=0.80), whereas BIA explained less variance (R²=0.32). In hierarchical models, US markedly improved FM prediction when added to anthropometric girths (ΔR²=0.48, p < 0.001), whereas anthropometry provided a smaller but significant improvement when added after US (ΔR²=0.06, p < 0.001). For ALSM, anthropometry was the strongest individual predictor (R²=0.91), followed by BIA (R²=0.82) and US (R²=0.81). Anthropometry provided the largest incremental contribution when added to either BIA or US (ΔR²=0.11–0.14, p < 0.001), whereas US did not further improve ALSM prediction once anthropometry and BIA were included. Conclusions Combining two techniques improved predictive accuracy, supporting a multimodal approach to body composition evaluation. In addition, a new standardized US protocol was presented.

BACKGROUND AND AIM:Anthropometric equations are widely used to estimate fat mass (FM). This study aimed firstly to develop and validate new anthropometric equations for estimating FM using dual-energy X-ray absorptiometry (DXA) as reference method in apparently healthy young adults. Then, we aimed to compare their accuracy with previously published two-component-based models. METHODS AND RESULTS:Five hundred fifteen adults (60% men, 40% women; age 24.2 ± 6.0 years, range 18-45; BMI 23.6 ± 3.1 kg m-2, range 16.2-36.0) underwent standardized anthropometric assessment according to International Society for the Advancement of Kinanthropometry (ISAK) guidelines, including measurement of eight skinfolds, and whole-body DXA. Participants were randomly divided into a development sample (n = 344) and an independent validation sample (n = 171). Two multiple-regression models were developed: a comprehensive equation based on all eight skinfolds and a simplified equation based on a four-skinfold protocol. Model performance was evaluated using R2, standard error of estimate (SEE), mean absolute error (MAE), root mean square error (RMSE), and Bland-Altman analysis. In validation, the 8-skinfold and 4-skinfold equations explained 82% and 80% of the variance in DXA-derived FM, respectively, with low prediction error (MAE 2.23-2.37 kg; RMSE ≤3.03 kg) and no significant bias versus DXA (p > 0.25). In contrast, all previously published equations showed significant bias (p < 0.001), consistently underestimating FM. CONCLUSIONS:DXA-referenced equations derived from standardized ISAK anthropometry demonstrated improved agreement and lower systematic bias compared with traditional two-component-based models.

BACKGROUND AND AIMS:Direct assessment of skinfold thickness and waist and hip girths provides information about body fat and its distribution, avoiding estimation errors due to predictive equations. The present study aimed to provide new centile curves for the sum of eight skinfold thicknesses (Σ8SKF) and waist-to-hip ratio (WHR) in adult population, and to identify breakpoints during adulthood. METHODS:The present investigation was conceived as a multicenter, cross-sectional study. Stature, body mass, eight skinfold thicknesses (i.e., triceps, biceps, subscapular, iliac crest, supraspinal, abdominal, thigh, and calf) and waist and hip girths were measured according to the International Society for the Advancement of Kinanthropometry protocol in 1,313 men and 1,194 women aged 18-65 years. Smoothed age- and sex-specific percentile curves were generated using the Lambda Mu and Sigma method. For both sexes, simple linear regressions of the dependent variable (Σ8SKF and WHR) versus the explanatory variable (age) were performed to investigate changes in the response variable's slope and to test for potential breakpoints. RESULTS:Reference percentile curves (3rd, 10th, 25th, 50th, 75th, 90th, and 97th) for Σ8SKF and WHR were provided. In men, Σ8SKF increased by 1.0 mm/year between the ages of 21 and 59, while in women, it increased by 3.8 mm/year between the ages of 38.5 and 47. In men, WHR showed a progressive increase of 0.004/year until the age of 28.4, followed by a slower increase of 0.003/year throughout the lifespan. In women, WHR increased by 0.003/year from the age of 20-65. CONCLUSIONS:Σ8SKF and WHR appear sex- and age-specific. Scientists and practitioners are provided with reference values for the adult population.

Background: The evaluation of body composition is considered a key factor for assessing nutritional status. In several settings, ultrasound (US) has been used as a useful tool in nutritional practice by estimating body composition parameters, such as the whole-body fat mass (FM). The estimation of FM can be carried out by using predictive equations that generally require measurements of skinfold thickness, which can be measured directly via US imaging. The main aim of this study was to evaluate the validity of US-derived skinfolds within anthropometric equations for estimating whole-body FM. Methods: Skinfold thickness was measured in 37 active individuals (19 males, age 24.2 ± 4.3 years, and 18 females, age 25.3 ± 4.2 years) using both anthropometry and US. The skinfolds obtained from anthropometry and US were entered into Evans' equation to estimate the FM and were validated against a four-component model (4C) as a reference. Results: The use of US-derived skinfolds within anthropometric equations resulted in an overestimation of FM (4.8%, p < 0.01). An agreement analysis between the FMs estimated with US-derived skinfolds and the 4C model revealed a concordance correlation coefficient of 0.33, 95% limits of agreements ranging from -3.4% to 0.6%, and a positive trend (r = 0.8; p < 0.01). Conclusions: The practice of doubling the US thickness to approximate skinfold thickness leads to an overestimation of FM by ~5%, and it should be avoided. This results in a lack of agreement with the 4C model at both the group and individual levels. New equations based on US measurements should be developed to enhance the accuracy of body composition evaluation and help optimize nutritional strategies.

Regarding skeletal muscle hypertrophy, resistance training and nutrition, the most often discussed and proposed supplements include proteins. Although, the correct amount, quality, and daily distribution of proteins is of paramount importance for skeletal muscle hypertrophy, there are many other nutritional supplements that can help and support the physiological response of skeletal muscle to resistance training in terms of muscle hypertrophy. A healthy muscle environment and a correct whole muscle metabolism response to the stress of training is a prerequisite for the increase in muscle protein synthesis and, therefore, muscle hypertrophy. In this review, we discuss the role of different nutritional supplements such as carbohydrates, vitamins, minerals, creatine, omega-3, polyphenols, and probiotics as a support and complementary factors to the main supplement i.e., protein. The different mechanisms are discussed in the light of recent evidence.

Obesity is defined as a complex, systemic disease characterized by excessive and dysfunctional adipose tissue, leading to adverse health effects. This condition is marked by low-grade inflammation, oxidative stress, and metabolic abnormalities, including mitochondrial dysfunction. These factors promote energy dysregulation and impact body composition not only by increasing body fat but also by promoting skeletal muscle mass atrophy. The decline in muscle mass is associated with an increased risk of all-cause mortality in individuals with this disease. The European Food Safety Authority approved pyrroloquinoline quinone (PQQ), a natural compound, as a dietary supplement in 2018. This narrative review aims to provide a comprehensive overview of the potential role of PQQ, based on its anti-inflammatory and antioxidant properties, in addressing dysfunctional adipose tissue metabolism and related disorders.

The appropriate use of predictive equations in estimating body composition through bioelectrical impedance analysis (BIA) depends on the device used and the subject's age, geographical ancestry, healthy status, physical activity level and sex. However, the presence of many isolated predictive equations in the literature makes the correct choice challenging, since the user may not distinguish its appropriateness. Therefore, the present systematic review aimed to classify each predictive equation in accordance with the independent parameters used. Sixty-four studies published between 1988 and 2023 were identified through a systematic search of international electronic databases. We included studies providing predictive equations derived from criterion methods, such as multi-compartment models for fat, fat-free and lean soft mass, dilution techniques for total-body water and extracellular water, total-body potassium for body cell mass, and magnetic resonance imaging or computerized tomography for skeletal muscle mass. The studies were excluded if non-criterion methods were employed or if the developed predictive equations involved mixed populations without specific codes or variables in the regression model. A total of 106 predictive equations were retrieved; 86 predictive equations were based on foot-to-hand and 20 on segmental technology, with no equations used the hand-to-hand and leg-to-leg. Classifying the subject's characteristics, 19 were for underaged, 26 for adults, 19 for athletes, 26 for elderly and 16 for individuals with diseases, encompassing both sexes. Practitioners now have an updated list of predictive equations for assessing body composition using BIA. Researchers are encouraged to generate novel predictive equations for scenarios not covered by the current literature.Registration code in PROSPERO: CRD42023467894.

Type I diabetes has an incidence of 15 per 100,000 people. Though it is a metabolic disorder, it can be seen in top, even professional athletes. Physical activity is recommended to manage diabetes, but there is a lack of specific knowledge on diabetes management and exercise from dedicated medical staff. This bias leads to suboptimal diabetes management, causing frequent hyper and hypoglycemia, a dysregulation of glycated hemoglobin, blood glucose out of control, and consequent needs to often intervene with extra insulin or carbohydrates. For 5 years, we followed a highly competitive male Caucasian athlete Vovinam Viet Vo Dao, with type I diabetes, aged 17. We monitored his glycated hemoglobin, the insulin drug administered, and glycemia blood level averages. We obtained, over time, a decrease in glycated hemoglobin by almost -22% and insulin administered by -37.33%, and average blood glycemia levels diminished by almost -27%. In addition, we carried out bioimpedance analysis and stratigraphy on the abdomen. Federation trainers supervised all physical training; we recorded an improvement in the general condition, underlined in particular by an increase in phase angle (from bioimpedance) of +17%.

Athletes are increasingly consuming (poly)phenol supplements to modify oxidative stress and/or exercise-induced inflammation, in the hope that this will enhance exercise performance. Chokeberries are rich in (poly)phenols and may therefore influence the health and performance of athletes. The objective of this systematic review was to comprehensively explore the effects of chokeberry supplementation on performance and exercise-induced biomarkers of oxidative stress, inflammation, and haematology in the athletic population. A search was conducted in PubMed, Web of Science, and SCOPUS. Studies were included if the participants were athletes, supplemented with chokeberry or chokeberry-based products, and evaluated sports-related outcomes. A total of ten articles were included in the study. The participants of all the studies were athletes and included rowers, football players, handball players, triathletes, and runners. A qualitative comprehensive summary of the applications of chokeberry supplementation targeting the athletic population has been evaluated. This included the effect of chokeberry supplementation on redox status, exercise-induced inflammation, haematology, iron metabolism, platelet aggregation, metabolic markers, body composition, and exercise performance. Chokeberry (poly)phenol-rich supplementation may be effective in enhancing the redox balance of athletes, yet more evidence is required to provide solid conclusions on its effect on inflammation, platelet function, iron metabolism and exercise performance.

Background & aims: The bioelectrical impedance vector analysis (BIVA) represents a qualitative analysis of body composition. The vector, defined by resistance (R) and reactance (Xc) standardized by stature, can be evaluated compared to the 50%,75%, and 95% tolerance ellipses representative of the reference populations. The tolerance ellipses for healthy adults have been provided in 1995 and were developed by mixing underage, adult, and elderly subjects, possibly misrepresenting the actual adult population. The current multicentric, cross-sectional study aimed to provide new tolerance ellipses specific for the general adult population and as a secondary aim to present centile curves for the bioelectrical phase angle. Methods: R, Xc, and phase angle were measured in 2137 and 2230 males and females using phase-sensitive foot-to-hand analyzers at 50 kHz. A minimum of 35 subjects were included for each sex and age category from 18 to 65 years. Results: The new mean vectors showed a leftward shift on the R-Xc graph with respect to the former reference values (males: F = 75.3; p < 0.001; females: F = 36.6, p < 0.001). The results provided new 3rd, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 97th percentile curves for phase angle, identifying time point phases of decrement (males:-0.03 degrees per year at 33.0-51.0 years and-0.05 degrees per year after 51 years; females:-0.03 degrees per year from 37.2 to 57.9 years). Conclusions: Compared to the original references, the new data are characterized by a different distribution within the R-Xc graph with a higher phase angle. Thirty years after the BIVA invention, the current study presents new tolerance ellipses and phase angle reference values for the adult population. (c) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Together with the global rise in obesity and metabolic syndrome, the prevalence of individuals who suffer from nonalcoholic fatty liver disease (NAFLD) has risen dramatically. NAFLD is currently the most common chronic liver disease and includes a continuum of liver disorders from initial fat accumulation to nonalcoholic steatohepatitis (NASH), considered the more severe forms, which can evolve in, cirrhosis, and hepatocellular carcinoma. Common features of NAFLD includes altered lipid metabolism mainly linked to mitochondrial dysfunction, which, as a vicious cycle, aggravates oxidative stress and promotes inflammation and, as a consequence, the progressive death of hepatocytes and the severe form of NAFLD. A ketogenic diet (KD), i.e., a diet very low in carbohydrates (<30 g/die) that induces "physiological ketosis", has been demonstrated to alleviate oxidative stress and restore mitochondrial function. Based on this, the aim of the present review is to analyze the body of evidence regarding the potential therapeutic role of KD in NAFLD, focusing on the interplay between mitochondria and the liver, the effects of ketosis on oxidative stress pathways, and the impact of KD on liver and mitochondrial function.

: Sitting behavior research rarely consider non-ambulatory movement in separate body regions. This study used accelerometers, a sedentary cut off criterion, and measurement variables to evaluate movement accumulation in trunk, waist, and foot regions of students in a 42-minute classroom session. Findings show that all three sites were unique in stationary and movement measures (P≤0.012). Trunk and waist spent almost entire lesson period in stationary state (98%) whereas foot spent larger proportion in movement (9%). In addition, longest stationary period in trunk and waist regions exceeded the 30-minute threshold of prolonged sitting by a margin of 1 to 2 minutes as opposed to the foot. Altogether, trunk and waist recorded negligible seated activity and foot recorded sporadic and frequent movement. Based on health connection of body regions movement while sitting, we believe that some movement may be better than no movement at all. Since trunk and wait were inactive during the lesson period, strategies could be established to encourage intermittent movement in static body regions and facilitation of movement in already active regions. However, further investigation is needed to better understand dependencies of localized body activity on students’ wellbeing in prolonged sessions of classroom lessons.

Bioelectrical impedance analysis (BIA) and anthropometry are considered alternatives to well-established reference techniques for assessing body composition. In team sports, the percentage of fat mass (FM%) is one of the most informative parameters, and a wide range of predictive equations allow for its estimation through both BIA and anthropometry. Although it is not clear which of these two techniques is more accurate for estimating FM%, the choice of the predictive equation could be a determining factor. The present study aimed to examine the validity of BIA and anthropometry in estimating FM% with different predictive equations, using dual X-ray absorptiometry (DXA) as a reference, in a group of futsal players. A total of 67 high-level male futsal players (age 23.7 ± 5.4 years) underwent BIA, anthropometric measurements, and DXA scanning. Four generalized, four athletic, and two sport-specific predictive equations were used for estimating FM% from raw bioelectric and anthropometric parameters. DXA-derived FM% was used as a reference. BIA-based generalized equations overestimated FM% (ranging from 1.13 to 2.69%, p < 0.05), whereas anthropometry-based generalized equations underestimated FM% in the futsal players (ranging from −1.72 to −2.04%, p < 0.05). Compared to DXA, no mean bias (p > 0.05) was observed using the athletic and sport-specific equations. Sport-specific equations allowed for more accurate and precise FM% estimations than did athletic predictive equations, with no trend (ranging from r = −0.217 to 0.235, p > 0.05). Regardless of the instrument, the choice of the equation determines the validity in FM% prediction. In conclusion, BIA and anthropometry can be used interchangeably, allowing for valid FM% estimations, provided that athletic and sport-specific equations are applied.

Background Bioelectrical impedance analysis (BIA) is a rapid and user-friendly technique for assessing body composition in sports. Currently, no sport-specific predictive equations are available, and the utilization of generalized formulas can introduce systematic bias. The objectives of this study were as follows: (i) to develop and validate new predictive models for estimating fat-free mass (FFM) components in male elite soccer players; (ii) to evaluate the accuracy of existing predictive equations. Methods A total of 102 male elite soccer players (mean age 24.7 ± 5.7 years), participating in the Italian first league, underwent assessments during the first half of the in-season period and were randomly divided into development and validation groups. Bioelectrical resistance (R) and reactance (Xc), representing the bioimpedance components, were measured using a foot-to-hand BIA device at a single frequency of 50 kHz. Dual-energy X-ray absorptiometry was employed to acquire reference data for FFM, lean soft tissue (LST), and appendicular lean soft tissue (ALST). The validation of the newly developed predictive equations was conducted through regression analysis, Bland–Altman tests, and the area under the curves (AUC) of regression receiver operating characteristic (RROC) curves. Results Developed models were: FFM = − 7.729 + (body mass × 0.686) + (stature 2 /R × 0.227) + (Xc × 0.086) + (age × 0.058), R 2 = 0.97, Standard error of estimation (SEE) = 1.0 kg; LST = − 8.929 + (body mass × 0.635) + (stature 2 /R × 0.244) + (Xc × 0.093) + (age × 0.048), R 2 = 0.96, SEE = 0.9 kg; ALST = − 24.068 + (body mass × 0.347) + (stature 2 /R × 0.308) + (Xc × 0.152), R 2 = 0.88, SEE = 1.4 kg. Train-test validation, performed on the validation group, revealed that generalized formulas for athletes underestimated all the predicted FFM components (p < 0.01), while the new predictive models showed no mean bias (p > 0.05), with R 2 values ranging from 0.83 to 0.91, and no trend (p > 0.05). The AUC scores of the RROC curves indicated an accuracy of 0.92, 0.92, and 0.74 for FFM, LST, and ALST, respectively. Conclusions The utilization of generalized predictive equations leads to an underestimation of FFM and ALST in elite soccer players. The newly developed soccer-specific formulas enable valid estimations of body composition while preserving the portability of a field-based method.