Age of Greatest Susceptibility to Childhood Lead Exposure: A New Statistical Approach
Bibliographic record
Abstract
BACKGROUND: Susceptibility to lead toxicity is often assumed to be greatest during early childhood (e.g., 2 years of age), but recent studies suggest that blood lead concentrations (BPb) taken at 5-7 years of age are more strongly associated with IQ. OBJECTIVE: We aimed to determine the age of greatest susceptibility to lead exposure using an innovative statistical approach that avoids the problem of correlated serial BPb measurements. METHODS: We analyzed two cohorts of children that were followed from infancy to 6 years of age in Rochester, New York (n = 211), and Cincinnati, Ohio (n = 251). Serial BPb levels were measured and IQ tests were done when children were 6 years of age. After adjustment for relevant covariates, the ratio of 6-year BPb to 2-year BPb was added to the multiple regression model to test whether the pattern of BPb profiles during childhood had additional effect on IQ. RESULTS: The ratio of BPb at 6 years to the BPb at 2 years showed a strong effect on IQ (p < .001) when added to the multiple regression model that included the average childhood BPb. IQ decreased by 7.0 points for children whose BPb at 6 years of age was 50% greater than that at 2 years compared with children whose 6-year BPb was 50% less than their 2-year BPb. Similarly, criminal arrest rates were a factor of 3.35 higher for those subjects whose 6-year BPb was 50% higher than their 2-year BPb. CONCLUSIONS: We conclude that 6-year BPb is more strongly associated with cognitive and behavioral development than is BPb measured in early childhood.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".