Metals exposure and risk of small-for-gestational age birth in a Canadian birth cohort: The MIREC study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Lead, mercury, cadmium and arsenic are some of the most common toxic metals to which Canadians are exposed. The effect of exposure to current low levels of toxic metals on fetal growth restriction is unknown. OBJECTIVE: The aim of this study was to examine relationships between exposure to lead, mercury, cadmium and arsenic during pregnancy, and risk of small for gestational age (SGA) birth. METHODS: Lead, mercury, cadmium and arsenic levels were measured in blood samples from the first and third trimesters in 1835 pregnant women from across Canada. Arsenic species in first trimester urine were also assessed. Relative risks and 95% confidence intervals were estimated using log binomial multivariate regression. Important covariates including maternal age, parity, pre-pregnancy BMI, and smoking, were considered in the analysis. An exploratory analysis was performed to examine potential effect modification of these relationships by single nucleotide polymorphisms (SNPs) in GSTP1 and GSTO1 genes. RESULTS: No association was found between blood lead, cadmium or arsenic and risk for SGA. We observed an increased risk for SGA for the highest compared to the lowest tertile of exposure for mercury (>1.6 µg/L, RR=1.56.; 95% CI=1.04-2.58) and arsenobetaine (>2.25 µg/L, RR=1.65; 95% CI=1.10-2.47) after adjustment for the effects of parity and smoking. A statistically significant interaction was observed in the relationship between dimethylarsinic acid (DMA) levels in urinary arsenic and SGA between strata of GSTO1 A104A (p for interaction=0.02). A marginally significant interaction was observed in the relationship between blood lead and SGA between strata of GSTP1 A114V (p for interaction=0.06). CONCLUSIONS: These results suggest a small increase in risk for SGA in infants born to women exposed to mercury and arsenic. Given the conflicting evidence in the literature this warrants further investigation in other pregnant populations.
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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 | 0.006 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it