Childhood lead exposure is associated with lower cognitive functioning at older ages
Bibliographic record
Abstract
The Flint, Michigan water crisis renewed concern about lead toxicity in drinking water. While lead in drinking water has been shown to negatively affect cognition among children, much less is known about its long-term consequences for late-life cognition. Using a nationally representative sample of U.S. older adults linked to historical administrative data from 1940, we find that older adults who lived as children in cities with lead pipes and acidic or alkaline water-the conditions required for lead to leach into drinking water-had worse cognitive functioning but not steeper cognitive decline. About a quarter of the association between lead and late-life cognition was accounted for by educational attainment. Within the next 10 years, American children exposed to high levels of lead during the 1970s will enter older ages. Our evidence highlights the need for stronger actions to identify interventions to mitigate long-term damage among people at high risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".