P2-239 Associations between sex hormones and bone mineral density and bone resorption in 50-year-old men: the Newcastle Thousand Families Study
Bibliographic record
Abstract
Introduction While much research relating sex hormones to bone health has centred on oestrogen deficiency in postmenopausal women, far less is known regarding the potential for sex hormone levels to influence bone health in men. We investigated the influence of sex hormone concentrations on bone health in men at age 50, using data from the Newcastle Thousand Families Study. Methods The study included 171 men who attended for DEXA scanning (giving measures of bone mineral density (BMD) for the hip and lumbar spine) and also gave blood samples allowing measurement of concentrations of testosterone, oestradiol, sex hormone binding globulin (SHBG), free androgen index (FAI), free oestrogen index (FEI), luteinising hormone (LH), follicle stimulating hormone (FSH), free testosterone and serum β C-telopeptide of type 1 collagen (CTX), a biochemical marker of bone resorption. Results There were significant correlations between total hip BMD and FEI (p=0.03), total spine BMD and SHBG (p=0.006), FEI (p=0.008) and FAI (p=0.008) and serum CTX and free testosterone (p=0.016). After adjustment for body weight the only associations that remained were between total spine BMD and FAI (p=0.046) and between serum CTX and free testosterone (p=0.014). Conclusions Our results suggest that while there are associations between serum sex hormone concentrations and BMD, they are mostly explained by an adjustment for contemporary body weight. The inverse association between serum CTX and free testosterone is more robust, remaining significant after adjustment. This suggests that free testosterone levels are independently associated with bone resorption levels.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".