Low Serum Testosterone Levels Are Associated with Elevated Urinary Mandelic Acid, and Strontium Levels in Adult Men According to the US 2011–2012 National Health and Nutrition Examination Survey
Bibliographic record
Abstract
BACKGROUND: Little is known regarding the effects of environmental exposure of chemicals on androgenic system in the general population. We studied 5,107 subjects included in the National Health and Nutrition Examination Survey (2011-2012). METHODS: Urinary, serum, and blood levels of 15 subclasses comprising 110 individual chemicals were analyzed for their association with serum testosterone levels. The subjects were divided into high and low testosterone groups according to the median testosterone concentration (374.51 ng/dL). Odds ratios (ORs) of individual chemicals in association with testosterone were estimated using logistic regression after adjusting for age, ethnicity, cotinine, body mass index, creatinine, alcohol, and the poverty income ratio. RESULTS: Adjusted ORs for the highest versus lowest quartiles of exposure were 2.12 (95% CI: 1.07, 4.21; Ptrend = 0.044), 1.84 (95% CI: 1.02, 3.34; Ptrend = 0.018) for the association between urinary mandelic acid, and strontium quartiles with low testosterone concentrations in adult men, respectively. However, no association was observed for the remaining chemicals with testosterone. CONCLUSIONS: The National Health and Nutrition Examination Survey data suggest that elevations in urinary mandelic acid, and strontium levels are negatively related to low serum testosterone levels in adult 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 | 0.000 | 0.001 |
| 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 | 0.000 | 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".