Bone mineral density and serum testosterone in chronically trained, high mileage 40–55 year old male runners
Bibliographic record
Abstract
OBJECTIVES: To identify physical activity that is beneficial for the maintenance of bone strength with increasing age by examining the relation between bone mineral density (BMD) and chronic endurance training in men. BMD at the proximal femur, its subregions, and the lumbar spine, and serum testosterone were compared between two groups of long distance runners with more than 20 years of training experience and non-athletic controls. METHODS: Runners (n = 12) were divided into (a) high volume runners (n = 7), running 64-80 km a week, and (b) very high volume runners (n = 5), running more than 95 km a week, and compared with non-athletic male controls, exercising in non-endurance oriented activities two to four times a week. BMD (g/cm2) at the total proximal femur, femoral neck, trochanteric region, and lumbar spine was measured by dual energy x ray absorptiometry. Total testosterone (nmol/l) and free testosterone (pmol/l) in serum were measured by radioimmunoassay from single fasting blood samples. RESULTS: Height, weight, and age (range = 40-55 years) were not significantly different between groups. The high volume runners had significantly higher BMD at the total proximal femur (1.09 (0.17) v 0.94 (0.056)), femoral neck (0.91 (0.16) v 0.78 (0.071)), and trochanteric region (0.85 (0.14) v 0.73 (0.053)) than controls (p<0.05). The differences in BMD for the proximal femur between the very high volume runners and the other two groups were not significant. There was no difference in lumbar spine BMD, total testosterone, or free testosterone between groups. However, there was a significant negative correlation between total testosterone (r = -0.73, p<0.01) and free testosterone (r = -0.79, p<0.005) and running volume in the distance runners. CONCLUSIONS: Long term distance running with training volumes less than 80 km a week had a positive effect on BMD of the proximal femur. With running volumes greater than 64 km a week, training was inversely related to testosterone levels, but levels remained within the normal range.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".