Prenatal Organophosphorus Pesticide Exposure and Child Neurodevelopment at 24 Months: An Analysis of Four Birth Cohorts
Bibliographic record
Abstract
BACKGROUND: Organophosphorus pesticides (OPs) are used in agriculture worldwide. Residential use was common in the United States before 2001. OBJECTIVES: We conducted a pooled analysis of four birth cohorts (children's centers; n = 936) to evaluate associations of prenatal exposure to OPs with child development at 24 months. METHODS: Using general linear models, we computed site-specific and pooled estimates of the association of total dialkyl (ΣDAP), diethyl (ΣDEP), and dimethylphosphate (ΣDMP) metabolite concentrations in maternal prenatal urine with mental and psychomotor development indices (MDI/PDI) and evaluated heterogeneity by children's center, race/ethnicity, and PON1 genotype. RESULTS: There was significant heterogeneity in the center-specific estimates of association for ΣDAP and ΣDMP and the MDI (p = 0.09, and p = 0.05, respectively), as well as heterogeneity in the race/ethnicity-specific estimates for ΣDAP (p = 0.06) and ΣDMP (p = 0.02) and the MDI. Strong MDI associations in the CHAMACOS population per 10-fold increase in ΣDAP (β = -4.17; 95% CI: -7.00, -1.33) and ΣDMP (β = -3.64; 95% CI: -5.97, -1.32) were influential, as were associations among Hispanics (β per 10-fold increase in ΣDAP = -2.91; 95% CI: -4.71, -1.12). We generally found stronger negative associations of ΣDAP and ΣDEP with the 24-month MDI for carriers of the 192Q PON1 allele, particularly among blacks and Hispanics. CONCLUSIONS: Data pooling was complicated by center-related differences in subject characteristics, eligibility, and changes in regulations governing residential use of OPs during the study periods. Pooled summary estimates of prenatal exposure to OPs and neurodevelopment should be interpreted with caution because of significant heterogeneity in associations by center, race/ethnicity, and PON1 genotype. Subgroups with unique exposure profiles or susceptibilities may be at higher risk for adverse neurodevelopment following prenatal exposure. CITATION: Engel SM, Bradman A, Wolff MS, Rauh VA, Harley KG, Yang JH, Hoepner LA, Barr DB, Yolton K, Vedar MG, Xu Y, Hornung RW, Wetmur JG, Chen J, Holland NT, Perera FP, Whyatt RM, Lanphear BP, Eskenazi B. 2016. Prenatal organophosphorus pesticide exposure and child neurodevelopment at 24 months: an analysis of four birth cohorts. Environ Health Perspect 124:822-830; http://dx.doi.org/10.1289/ehp.1409474.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".