Sex- and age-differences in blood manganese levels in the U.S. general population: national health and nutrition examination survey 2011–2012
Bibliographic record
Abstract
BACKGROUND: Manganese is an essential element, but excessive manganese exposure has neurotoxic effects. OBJECTIVE: To examine blood manganese levels in the general population with respect to sex, age, race/ethnicity, pregnancy and menauposal status, as well as levels of trace elements in blood. METHODS: We used data from the National Health and Nutrition Examination Survey, a national survey of U.S. residents (n = 7720 participants, ages 1 to 80 years). General linear models and generalized additive models were used to examine the association between blood manganese concentration and participants' characterisics, accounting for the complex survey design. RESULTS: Blood manganese levels ranged from 1.6 to 62.5 μg/L, with arithmetic means of 10.6 and 9.2 μg/L for women and men, respectively. The following characteristics were significantly associated with higher blood manganese levels: female sex, younger age, Asian origin, and being pregnant. In addition, there were non-linear relationships between blood manganese levels and cadmium, iron, lead, and mercury levels. CONCLUSION: The higher blood manganese levels observed among females suggest sex-related metabolic differences in the regulation of manganese, and elevated levels among pregnant women suggest an important role of manganese in reproduction. The present study supports the need to take into consideration age- and sex-related differences in blood manganese levels, as well as pregnancy status when examining manganese essentiality or toxicity.
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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 | 0.000 | 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".