Can Phase Angle Be Associated With Muscle Strength in Healthy Male Army Cadets?
Bibliographic record
Abstract
INTRODUCTION: Phase angle (PhA) determined by bioelectrical impedance (BIA) is related to body fluid balance and cell membrane integrity. Handgrip strength (HGS) is used to assess muscle strength and as an indicator of health. We aimed to determine the relationship between PhA and HGS in healthy young males and to verify whether this relationship is dependent on body components. MATERIALS AND METHODS: Hundred and sixty-three healthy male army cadets (18.8 ± 0.6 years old) participated in the study. PhA was determined by BIA, HGS was assessed by a hydraulic dynamometer, and dual-energy X-ray absorptiometry determined: fat mass (FM), bone mineral content (BMC), and lean soft tissue (LST). Participants were divided according to the PhA tertile (first tertile: PhA < 7.14°, second tertile: 7.14° ≤ PhA < 7.83°, and third tertile: PhA ≥ 7.83°). RESULTS: Youth from the first tertile of PhA had lower BMC (2.8 kg vs. 3.0 kg and vs. 3.1 kg) and LST (51.7 vs. 53.8 kg and vs. 57.6 kg) compared to youth from the second and third tertile of PhA (P < .001), respectively. Additionally, lower HGS (83.0 kg vs. 93.1 kg) was found in the first tertile compared to the third tertile of PhA (P < .001). PhA explained 3% of the HGS variation (R2 = 0.029), while LST and BMC explained 39% (R2 = 0.385) and 22% (R2 = 0.221), respectively. Furthermore, the correlation between PhA and HGS was dependent on LST (P = .567) and BMC (P = .182). CONCLUSION: In this sample, PhA showed a small relationship with HGS, remaining dependent on BMC and LST values. These results reinforce the importance of maintaining a physically active lifestyle with great lean mass and muscle strength values.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".