(1) Background/Objectives: Cardiovascular diseases (CVD) are the leading cause of morbidity and mortality globally, necessitating effective risk prediction strategies. This study was aimed at developing and validating a multivariate predictive model integrating body composition and lipid profile to assess cardiovascular risk in an adult population. (2) Methods: A cross-sectional analysis of 90 participants from the general Spanish population was conducted. Participants were classified into cardiovascular risk groups (low, medium, high) based on systolic blood pressure. (3) Results: Descriptive and multinomial logistic regression analyses revealed significant associations between cardiovascular risk and specific parameters, such as visceral fat, glucose levels, and waist-to-hip ratio. Visceral adiposity emerged as a strong predictor of high cardiovascular risk, highlighting its critical role in cardiovascular health. Glucose levels were also significantly associated with increased risk, underscoring the importance of metabolic health in cardiovascular outcomes. Contrary to expectations, lipid markers like cholesterol and triglycerides did not show significant variations across risk categories, suggesting that traditional lipid profiles may not fully capture cardiovascular risk in the study group. Waist-to-hip ratio showed significant associations with cardiovascular risk transitions, particularly between low and medium risk, emphasizing the importance of fat distribution patterns. (4) Conclusions: These findings suggest that body composition, particularly visceral fat, is a crucial determinant of cardiovascular risk, necessitating more personalized risk assessment approaches that move beyond traditional lipid markers.

Algae-based supplements are gaining attention for their potential metabolic, antioxidant, and anti-inflammatory properties in sports nutrition. Methods: A 30-day pilot randomized controlled trial was conducted in 70 healthy male athletes (mean age 25.4 ± 4.9 years) from competitive soccer and handball teams. Participants were randomly assigned to a supplementation group (6 g/day of Ulva-derived algae powder) or a control group. Both groups followed identical training routines and adhered to standardized nutritional recommendations, including macronutrient distribution and permitted supplements (e.g., isotonic drinks, protein shakes). Biochemical markers analyzed at baseline and post-intervention included HbA1c, lipid profile, malondialdehyde (MDA), catalase, myeloperoxidase (MPO), erythrocyte sedimentation rate (ESR), and cortisol. Genetic polymorphisms related to metabolic traits were also assessed. Results: Significant group × time interactions (p < 0.001) were observed for HbA1c, LDL, triglycerides, MDA, MPO, ESR, and cortisol, all of which improved in the algae-supplemented group. Correlation analysis revealed associations between HbA1c and LDL/TG as well as between cortisol and MPO. No significant genetic modulation of responses was detected, although a trend was noted for cortisol variation and insulin resistance risk. Conclusions: Algae-based supplementation led to favorable metabolic, oxidative, and inflammatory changes. These findings suggest its potential utility as a nutritional strategy to support recovery in athletes during periods of high training load or competition.

Background and Objectives: Individuals with chronic tetraplegia frequently present altered body composition and metabolic dysregulation, which may not be adequately reflected by traditional markers such as body mass index. This study aimed to evaluate body composition, dietary patterns, and biochemical profiles in adults with chronic tetraplegia, and to explore cross-domain associations between these outcomes. Materials and Methods: Eleven adults with chronic tetraplegia underwent anthropometric assessment (BMI, body fat %, triceps skinfold), dietary evaluation, and fasting biochemical analysis (lipids and glucose). Data distribution was tested with Shapiro–Wilk. Between-sex comparisons were explored with Mann–Whitney U tests. Pearson correlations were performed across domains (diet—body composition; diet—biochemical markers; body composition—biochemical markers). Statistical significance was set at p < 0.05. Results: Despite normal BMI values, participants showed elevated body fat percentages. Dietary intake was characterized by excessive lipid consumption and suboptimal protein contribution. Cross-domain correlations revealed that higher energy and macronutrient intakes were associated with one another. Protein intake was inversely correlated with triglyceride levels (r = −0.63, p = 0.038), while triceps skinfold showed a strong correlation with body fat percentage (r = 0.78, p = 0.004). Fasting glucose was positively correlated with total cholesterol (r = 0.61, p = 0.046). Most correlations did not reach statistical significance, likely due to limited sample size, but provided exploratory insight into the interplay between diet, adiposity, and metabolic markers. Conclusions: Individuals with chronic tetraplegia may exhibit increased adiposity and early metabolic alterations despite normal BMI and modest reported energy intake. These findings reinforce the inadequacy of BMI for nutritional assessment in SCI and highlight the need for integrated evaluation—including body composition, dietary quality, and biochemical monitoring—to guide personalized interventions aimed at reducing cardiometabolic risk.

Breast cancer survivors frequently experience adverse changes in body composition, cardiometabolic biomarkers, functional capacity and quality of life that may worsen long-term prognosis, yet the comparative effectiveness of lifestyle interventions across delivery formats and supervision levels remains unclear. Background/Objectives: This systematic review assessed the effects of structured diet and exercise interventions on body composition, metabolic and inflammatory biomarkers, functional capacity, dietary habits and quality of life in breast cancer survivors. Methods: Following PRISMA guidelines, Cochrane, PubMed, Scopus and Web of Science were searched for randomized controlled trials and quasi-experimental studies published in English between 2016 and 2026. Risk of bias was assessed with RoB 2 and ROBINS-I and certainty of evidence with GRADE. Results: Of 1413 records, 15 studies (11 RCTs; mean age 46–60 years; mostly overweight or obese post-treatment women) met the inclusion criteria; twelve interventions were supervised and three home-based or web-based. Within the assessed domains, many studies reported significant improvements in body composition, quality of life and metabolic or inflammatory biomarkers. Effects were larger in multimodal supervised programs combining caloric restriction with moderate-to-vigorous aerobic plus resistance training (5–8% weight loss; 19–29% visceral fat reduction; improved insulin, IGF-1, leptin, adiponectin and EORTC QLQ-C30 scores), whereas digital or low-intensity interventions produced smaller, less uniform objective effects despite improving dietary behaviors. GRADE certainty ranged from very low to moderate–high. Conclusions: Multimodal supervised programs offer the most robust benefits; digital formats require additional supervision. Standardized protocols and longer follow-up are needed.