Comparing DXA and Air Displacement Plethysmography to Assess Body Composition of Male Collegiate Hockey Players
Bibliographic record
Abstract
Delisle-Houde, P, Reid, RER, Insogna, JA, Prokop, NW, Buchan, TA, Fontaine, SL, and Andersen, RE. Comparing DXA and air-displacement-plethysmography to assess body composition of male collegiate hockey players. J Strength Cond Res 33(2): 474-478, 2019-Accurate assessment of body composition is an important consideration for athletes because it is a health/performance variable. However, little is known about the variability in values obtained across different assessment methods for specific athlete populations. The purpose of this study was to compare 2 common laboratory methods that assess body composition: air displacement plethysmography (BOD POD) and dual energy x-ray absorptiometry (DXA). Twenty-nine male collegiate hockey players, (Age = 24.07 ± 1.49, BMI = 26.5 ± 2.74) participated in this study. All participants underwent back-to-back BOD POD and DXA evaluations. Paired t-tests and Bland-Altman analyses were performed to compare differences in fat mass, fat percentage, and fat-free mass between methods. Average fat percentage reported by the DXA and BOD POD was 15.34 ± 3.53 and 11.66 ± 4.82 respectively, resulting in a bias score of 3.78 ± 2.33 kg (t(28) = 8.71, p ≤ 0.001). Average fat mass reported by the DXA and BOD POD was 13.42 ± 3.59 and 10.15 ± 4.54 kg respectively, resulting in a bias score of 3.27 ± 1.92 kg (t(28) = 9.18, p ≤ 0.001). Average fat-free mass reported by the DXA and BOD POD was 73.31 ± 5.30 and 76.25 ± 5.74 kg respectively, resulting in a bias score of -2.93 ± 2.06 kg (t(28) = -7.66, p ≤ 0.001). Our findings can help make more insightful comparisons between studies that use different body composition methodologies among athletic populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".