Early life lead exposure and behavioral problems among children in the HOME Study
Bibliographic record
Abstract
Background: Lead exposure is associated with behavioral problems in children, but the ages when children are most susceptible to lead toxicity are unclear. Our objective was to evaluate the association of repeated blood lead concentrations with parent-reported behaviors and identify periods of heightened susceptibility.Methods: Between 2003-2006, we recruited pregnant women (n=389) living in homes built pre-1978 from Cincinnati, Ohio (HOME Study) and followed their children until age 8 years. We quantified lead in whole blood samples collected from children at ages 1, 2, 3, 4, 5, and 8 years. We assessed parent-reported child behavior using the Behavioral Assessment System for Children-2 (BASC-2) when children were ages 2, 3, 4, 5, and 8 years. Using linear regression with generalized estimating equations adjusted for covariates, we estimated associations of time-varying blood lead concentrations (ln-transformed, g/L) with behavioral profiles using the BASC-2 composite scales. We used multiple informant models to assess heterogeneity in these associations across exposure periods (n=241).Results: The median blood lead concentration peaked at 15 g/L around age 2 years (25th, 75th=10, 22 g/L) and gradually decreased to 6 g/L around age 8 years (25th, 75th=4, 9) g/L). Higher time-varying blood lead concentrations were associated with more externalizing problems (β:1.8-point; 95% CI= 0.3, 3.2). The association between blood lead levels and externalizing problems varied by exposure timing (lead x period interaction p-value=0.11), with heightened susceptibility around ages 3 (β:2.1-point; 95% CI= 0.6, 3.6) and 8 (β:3.5-point; 95% CI= 1.2, 5.7) years compared with other ages. Conclusion: Children with higher blood lead levels had more parent-reported hyperactive and aggressive behaviors. Future research could investigate if the periods of heightened susceptibility around ages 3 and 8 years are due to unique neurodevelopmental processes.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".