Elevated levels of gonadotrophins but not sex steroids are associated with musculoskeletal pain in middle-aged and older European men
Bibliographic record
Abstract
The aim of this study was to determine the association of hormone levels with the occurrence of musculoskeletal pain. Men ages 40 to 79 years were recruited from population registers in 8 European centres. Subjects were asked to complete a postal questionnaire, which enquired about lifestyle and the occurrence of musculoskeletal pain over the past month. Total testosterone (T), oestradiol (E2), luteinising hormone (LH), and follicle-stimulating hormone (FSH) were assayed from a fasting blood sample. The association between pain status and hormone levels was assessed using multinomial logistic regression with results expressed as relative risk ratios (RRR) and 95% confidence intervals (CI). A total of 3206 men had complete data on pain status. Of these, 8.7% reported chronic widespread pain (CWP), whereas 50% had some pain although not CWP and were classified as having some pain. T and E2 were not associated with musculoskeletal pain, whereas significant differences in LH and FSH levels were found between pain groups. After adjustment for age and other possible confounders, the association between pain status and both LH and FSH persisted. Compared with those in the lowest tertile of LH, those in the highest tertile were more likely to report some pain (vs no pain, RRR=1.28; 95% CI 1.09 to 1.50) and also CWP (vs no pain, RRR=1.51; 95% CI 1.10 to 2.07). Similar results were found for FSH. Gonadotrophins, but not sex steroid hormone levels, are associated with musculoskeletal pain in men.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".