Environmental Co-Exposure to Lead and Manganese and Intellectual Deficit in School-Aged Children
Bibliographic record
Abstract
Studies have demonstrated that, for urban children, dust represents the main exposure to sources of metals like lead (Pb) and manganese (Mn). We aimed to investigate the exposure to these metals and their association with intellectual deficit in children living in an industrial region. This cross-sectional study recruited volunteers from four elementary schools in the town of Simões Filho, Brazil. We evaluated 225 school-aged children (7–12 years) for blood lead (PbB) and manganese hair (MnH) and toenails (MnTn) by graphite furnace atomic absorption spectrometry. Child and maternal IQs were estimated using the Wechsler Abbreviated Scale for Intelligence (WASI). Median and range PbB were 1.2 (0.3–15.6) μg/dL. MnH and MnTn medians (ranges) were 0.74 (0.16–8.79) μg/g and 0.85 (0.15–13.30) μg/g, respectively. After adjusting for maternal IQ, age and Mn exposure, child IQ drops by 8.6 points for a 10-fold increase in PbB levels. Moreover, an effect modification of Mn co-exposure was observed. In children with low MnTn, association between Pb and child IQ was not significant (β = −6.780, p = 0.172). However, in those with high MnTn, the association was increased by 27.9% (β = −8.70, p = 0.036). Low Pb exposure is associated with intellectual deficit in children, especially in those with high MnTn.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".