Prenatal current-use pesticide exposure and children's neurodevelopment at one year of age in the Infants' Environmental Health (ISA) birth cohort, Costa Rica
Bibliographic record
Abstract
Pesticide exposure may affect young children's neurodevelopment, but only few cohort studies have addressed possible effects of non-organophosphate pesticides. We evaluated associations between prenatal current-use pesticide exposure and neurodevelopmental outcomes among 1-year-old children from the Infants’ Environmental Health (ISA) birth cohort. To determine prenatal pesticide exposure, we measured biomarkers of pyrimethanil, chlorpyrifos, synthetic pyrethroids, and 2,4-D in urine samples among 355 women, 1–3 times during pregnancy. One-year post-partum, we evaluated children's neurodevelopment with the Bayley Scales of Infant and Toddler Development 3rd edition (BSID-III). We assessed associations between exposures and neurodevelopmental outcomes (composite and z-scores) using single-chemical linear regression models adjusted for possible confounders (maternal education, parity, sex, gestational age at birth, child age, HOME-score, location of assessment, biomarkers of mancozeb), and studied effect-modification by sex. We evaluated non-linear associations of multiple pesticide exposures with Bayesian kernel machine regression (BKMR). We found higher prenatal urinary 2,4-D concentrations were associated with lower language (βper ten-fold increase = −2.0, 95 % confidence interval (CI) = −3.5, −0.5) and motor (βper ten-fold increase = −2.2, 95 %CI = −4.2, −0.1) composite scores among all children. Also, higher chlorpyrifos exposure [measured as urinary 3,5,6-trichloro-2-pyridinol (TCPy)] was associated with lower cognitive composite scores (βper ten-fold increase = −1.9, 95 %CI = −4.7, 0.8), and lower motor composite scores among boys (βper ten-fold increase = −3.8, 95 % CI = −7.7, 0.1) but not girls (βper ten-fold increase = 2.3, 95 %CI = −1.6, 6.3, pINT = 0.11). Finally, higher pyrimethanil was associated with lower language abilities among girls, but not boys. Pyrethroid metabolite concentrations did not explain variability in BSID-III composite scores. Associations were similar for BSID-III z-scores, and we found no evidence for non-linear associations or mixture effects. Prenatal exposure to common-use pesticides may affect children's neurodevelopment at 1-year of age, some effects may be sex-specific.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".