Adverse effects of maternal lead levels on birth outcomes in the <scp>ALSPAC</scp> study: a prospective birth cohort study
Bibliographic record
Abstract
OBJECTIVE: To study the associations of prenatal blood lead levels (B-Pb) with pregnancy outcomes in a large cohort of mother-child pairs in the UK. DESIGN: Prospective birth cohort study. SETTING: Avon area of Bristol, UK. POPULATION: Pregnant women enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC). METHODS: Whole blood samples were collected and analysed by inductively coupled plasma dynamic reaction cell mass spectrometry (n = 4285). Data collected on the infants included anthropometric variables and gestational age at delivery. Linear regression models for continuous outcomes and logistic regression models for categorical outcomes were adjusted for covariates including maternal height, smoking, parity, sex of the baby and gestational age. MAIN OUTCOME MEASURES: Birthweight, head circumference and crown-heel length, preterm delivery and low birthweight. RESULTS: The mean blood lead level (B-Pb) was 3.67 ± 1.47 μg/dl. B-Pb ≥ 5 μg/dl significantly increased the risk of preterm delivery (adjusted odds ratio [OR] 2.00 95% confidence interval [95% CI] 1.35-3.00) but not of having a low birthweight baby (adjusted OR 1.37, 95% CI 0.86-2.18) in multivariable binary logistic models. Increasing B-Pb was significantly associated with reductions in birth weight (β -13.23, 95% CI -23.75 to -2.70), head circumference (β -0.04, 95% CI -0.07 to -0.06) and crown-heel length (β -0.05, 95% CI -0.10 to -0.00) in multivariable linear regression models. CONCLUSIONS: There was evidence for adverse effects of maternal B-Pb on the incidence of preterm delivery, birthweight, head circumference and crown-heel length, but not on the incidence of low birthweight, in this group of women.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".