134 Impaired Sleep is Associated with Low Testosterone in US Adult Males: Results from the National Health and Nutrition Examination Survey
Bibliographic record
Abstract
Testosterone deficiency has been linked to several adverse health outcomes and recent data has suggested that abnormal sleep quality may result in lower testosterone levels. To assess the effect of self-reported sleep patterns on serum testosterone while controlling for co-morbidities, and baseline demographics. Using data collected from the 2011-2012 National Health and Nutrition Examination Survey (NHANES), we extracted serum total testosterone level, sleep duration, demographic, and co-morbidities for men aged 16 years and older. Univariate and multivariate linear regression was used to estimate the association of number of hours slept, co-morbidities, and demographics with serum testosterone. Among the 9,756 individuals in the NHANES dataset, 2,295 (23.5%) were males 16 years and older with a median (interquartile range) age of 46 years (29 - 62) who also had serum testosterone levels drawn. Median serum testosterone level was 377 ng/dL (IQR: 279 – 492 ng/dL). Median number of hours slept was 7 hours (IQR: 6 - 8 hours). On multivariate linear regression, we found serum testosterone decreased by 0.49 ng/dL per year of age (p = 0.04), 5.85 ng/dL per hour loss of sleep (p<0.01) and 6.18 ng/dL per unit of body mass index (BMI) increase (p<0.01).
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".