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Record W4407718447 · doi:10.1038/s41598-025-87918-4

Association of body composition measures to muscle strength using DXA, D3Cr, and BIA in collegiate athletes

2025· article· en· W4407718447 on OpenAlexaff
Devon Cataldi, Jonathan P. Bennett, Brandon K. Quon, Lambert T. Leong, Thomas L. Kelly, Alexandra M. Binder, James W. Evans, CARLA PRADO, Steven B. Heymsfield, John Shepherd

Bibliographic record

VenueScientific Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicBody Composition Measurement Techniques
Canadian institutionsUniversity of Alberta
FundersNational Cancer InstituteNational Heart, Lung, and Blood InstituteHologic
KeywordsAthletesComposition (language)Muscle strengthMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Muscle mass and strength are crucial for physiological function and performance in athletes, playing a significant role in maintaining health and optimal athletic performance. Skeletal muscle, which constitutes the majority of lean soft tissue (LST) and appendicular lean soft tissue (ALST) when measured by dual-energy X-ray absorptiometry (DXA), represents a commonly used surrogate for strength. Research has investigated alternative measures of body composition, such as the assessment of ALST through bioelectrical impedance analysis (BIA) and the determination of whole-body muscle mass from creatine pool size using the deuterated creatine (D 3 Cr) dilution method, for their associations to strength. While the relationship between body composition measures and strength has been studied in older adults, this relationship remains unexplored in athletic populations. This study examined muscle body composition measures using DXA, D 3 Cr, and BIA and their association with strength in a sample of collegiate athletes. The study enrolled 80 collegiate athletes (40 females) of differing sports disciplines who consumed a 60 mg dose of D 3 Cr and completed DXA and BIA measures in addition to trunk and leg strength tests. Analysis was sex-stratified using Pearson’s correlations, linear regression, and quartile p trend significance. With an average participant age of 21.8 years, whole-body DXA correlations to muscle strength surpassed height- or mass-normalized values. This trend was especially pronounced in trunk strength’s relationship with body composition over leg strength, across measurement methods. While DXA LST values were higher than BIA and D 3 Cr in predicting strength, the values did not differ significantly. Adjustments for age, BMI, and BIA variables didn’t enhance this association. A significant trend between DXA LST and all strength measures underscored the equal relevance of DXA and D 3 Cr muscle mass to strength, favoring whole-body over regional assessments. This calls for future research on muscle mass’s effects on LST and functional outcomes in broader groups, highlighting the importance of comprehensive body composition analysis in athletic performance studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.293
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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