Relationship Of Bone Mineral Density, Aerobic Power, Muscular Strength, And Body Composition In Adult Males
Bibliographic record
Abstract
Indirect indicators of bone mineral density (BMD) can offer important and useful information to practitioners. Finding a more time and cost effective method for estimating BMD in different locations could aid in the treatment and prevention of osteoporosis and osteopenia. Increased muscle strength has been shown to correlate with increased total body BMD in both men and women. There have been a number of studies examining predictors of BMD in women; however there have been substantially fewer studies involving men. This over-representation of the female population has led to the belief that osteoporotic fractures are less frequent in men where in actuality the rate of hip fractures increases more dramatically in men with age. PURPOSE: The purpose of this study was to examine the relationship between muscular strength, aerobic capacity, body composition and BMD in healthy male subjects. METHODS: Participants were seven physically active, adult men (mean age: 28.3 years; range: 21-38). Maximal oxygen consumption (VO2max) was directly measured during treadmill running. Bone mineral density and body composition were determined using Dual X-Ray Absorptiometry (DEXA). Upper body strength was measured with a hand grip dynamometer, and lower body strength (isometric leg extension) using a cable tensiometer. Pearson Correlation coefficients were used to test for significant relationships between the measured variables. RESULTS: Lower body strength increased concomitant with lower body (r = 0.676), total body (r = 0.709), and total spine BMD (r = 0.915); this was also seen in the thoracic (r = 0.931) and lumbar spine (r = 0.891). As lean body mass (LBM) increased, mean upper body BMD increased (r = 0.646). As total body % fat increased, upper body strength increased (r = 0.825). There were no significant correlations between BMD and absolute or relative VO2max. There were also no significant correlations between lower body strength and VO2max. CONCLUSION: In physically active, adult men, lower body strength is a strong predictor of increased total spine BMD, particularly in the thoracic and lumbar regions. LBM is a strong indicator of upper body BMD. Total body % fat is also a strong predictor of increased upper body strength. Neither absolute nor relative VO2max were good indicators of BMD or lower body strength.
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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 | 0.000 |
| 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) | 0.002 | 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".