Background: This study investigated the relationships between hematological and bone metabolism variables in 35 elite female trail runners, focusing on identifying key hematological correlates of bone health. Methods: Forty-four hematological variables, including biochemical, hormonal, metabolic, liver enzyme, and iron profiles, as well as complete blood count and platelet indices, were analyzed. Bone mineral density (BMD) and bone mineral content (BMC) were assessed at multiple skeletal regions via dual-energy X-ray absorptiometry (DXA). A cross-sectional design was employed, utilizing descriptive statistics, correlation analyses, and multiple linear regression to analyze the associations between hematological markers and BMC and BMD. Results: Significant but moderate associations were identified: magnesium consistently emerged as a negatively associated factor, particularly associated with BMC and BMD in the lumbar spine (L1–L4) and whole-body, potentially reflecting hypothesized mineral mobilization during chronic physical stress. Follicle-stimulating hormone showed positive associations with BMD, suggesting a potential protective association in bone turnover regulation. Additionally, calcium and thyroid hormones were linked to regional bone properties, highlighting site-specific skeletal vulnerabilities. Conclusions: These findings suggest a complex interplay between mineral homeostasis and hormonal balance that may be related to skeletal integrity in elite female trail runners. This work provides a foundation for developing evidence-based guidelines to support the health and performance of female endurance athletes. Further research is warranted to confirm these results through longitudinal evaluations.

Background: This study examined nutritional intake, body composition, menstrual health, and performance in elite female trail runners. Methods: A cross-sectional multivariate analysis was conducted on 35 athletes (14 eumenorrheic, 21 amenorrheic/oligomenorrheic). Nutritional intake was assessed through 7-day and 24 h food records; anthropometry followed ISAK standards; performance was evaluated via ITRA and UTMB rankings. Statistical analyses included t-tests, MANCOVA, regression models, and Random Forest, adjusting for body composition and covariates. Results: Although energy availability (EA) did not differ significantly between groups, 94.3% of athletes had clinically low EA (<30 kcal/kg FFM/day). Amenorrheic athletes consumed more simple carbohydrates (21.8 ± 5.7% vs. 17.2 ± 3.1%), protein (2.5 ± 0.6 vs. 1.7 ± 0.2 g/kg/day), fiber, and lipids, while eumenorrheic athletes consumed more complex carbohydrates (129.7 ± 27.0 vs. 82.5 ± 33.3 g/day) and most vitamins. Both groups had inadequate calcium and iron intake. Low EA was moderately associated with an ectomorphic somatotype (r = 0.418). Performance negatively correlated with simple carbohydrates (r = −0.624) and positively with complex carbohydrates, total energy, protein, polyunsaturated fats, and zinc (r = 0.300–0.580). No significant performance differences were found between menstrual status groups. Conclusions: Menstrual irregularities did not affect performance, but nutritional patterns strongly influenced both performance and energy availability. Personalized nutrition strategies are essential for optimizing performance and safeguarding health in elite female trail runners.

Background: Between-limb lean-mass asymmetry has been proposed for injury-risk and re-turn-to-sport monitoring. Dual-energy X-ray absorptiometry (DXA), the reference method, requires a fixed installation and ionizing radiation; segmental bioelectrical impedance analysis (BIA) is fast, inexpensive and field-applicable. Agreement for the asymmetry itself, rather than absolute limb values, is unresolved. Methods: In this cross-sectional method-comparison study, 127 trail runners (90 men, 37 women) underwent eight-electrode segmental BIA and DXA in the same session. An asymmetry index, the between-limb difference relative to the limb mean, was computed from raw leg resistance (BIA) and leg lean mass (DXA), and assessed by Bland–Altman analysis, concordance correlation (CCC) and kappa. Results: Mean bias was −0.97 percentage points, but the 95% limits of agreement spanned −6.67 to +4.73 pp, three to four times the observed interquartile range; CCC was 0.414. The same leg was identified in 70.9% of runners (kappa 0.309) against a right-side predomi-nance of 75.6%, and BIA did not outperform a constant right-leg rule (p = 0.451). Conclusions: Segmental BIA and DXA are not interchangeable for between-limb lean-mass asymmetry in trail runners: the disagreement between methods exceeds the asymmetries observed, and directional agreement must be read against the base rate.

Background: Converting skinfold thicknesses into body fat percentage (%BF) assumes that subcutaneous adipose tissue (SAT) represents a fixed fraction of total fat, an assumption untested at extreme leanness. This study assessed whether skinfold–dual-energy X-ray absorptiometry (DXA) disagreement is random or structured by regional SAT. Methods: Thirty-five elite (Tier 4) female trail runners underwent anthropometry (Withers equation) and DXA in one session. Agreement was evaluated via Bland–Altman analysis and Lin's concordance correlation coefficient (CCC). The inter-method difference (%BF_GAP = %BF_WITHERS − %BF_DXA) was regressed on android SAT, adjusted for total adiposity, and benchmarked against DXA-derived negative controls. Results: The methods correlated closely (r = 0.866, 95% CI: 0.749 to 0.931) but showed poor concordance (CCC = 0.311). Skinfolds systematically underestimated DXA by 5.50 percentage points (pp; total error 5.74 pp), displaying proportional bias that widened with adiposity. Android SAT pre-dicted %BF_GAP (R² = 0.489). Residualized on total fat mass, SAT retained an independent contribution (ΔR² = 0.106), which no negative control showed. Propagated skinfold imprecision (SD = 0.19 pp) accounted for only ~1.3% of the observed difference variance (SD = 1.66 pp). Conclusions: The disagreement is systematic, phenotype-dependent, and structured by regional SAT, reflecting accuracy rather than precision limitations. Con-verted skinfold %BF should not be reported alone or compared against DXA reference data; raw skinfold sums are preferable, as a variable to be observed rather than a target to be reduced.

Background: Between-limb lean-mass asymmetry has been proposed for injury-risk and return-to-sport monitoring. Dual-energy X-ray absorptiometry (DXA), the reference method, requires a fixed installation and ionizing radiation; segmental bioelectrical impedance analysis (BIA) is fast, inexpensive and field-applicable. Agreement for the asymmetry itself, rather than absolute limb values, is unresolved. Methods: In this cross-sectional method-comparison study, 127 trail runners (90 men, 37 women) underwent eight-electrode segmental BIA and DXA in the same session. An asymmetry index, the between-limb difference relative to the limb mean, was computed from raw leg resistance (BIA) and leg lean mass (DXA), and assessed by Bland–Altman analysis, concordance correlation (CCC) and kappa. Results: Mean bias was −0.97 percentage points (pp), but the 95% limits of agreement spanned −6.67 to +4.73 pp, three to four times the observed interquartile range; CCC was 0.414. The same leg was identified in 70.9% of runners (kappa 0.309) against a right-side predominance of 75.6%, and the BIA classification was not significantly better than a constant right-leg rule (p = 0.451). Conclusions: Segmental BIA cannot replace DXA for assessing between-limb lean-mass asymmetry in individual trail runners. The disagreement between methods exceeds the asymmetries observed, and directional agreement must be read against the base rate.