Determinants of urinary concentrations of dialkyl phosphates among pregnant women in Canada — Results from the MIREC study
Bibliographic record
Abstract
Organophosphate (OP) insecticides are commonly used in agriculture. Their use decreased in recent years as they were gradually replaced by other pesticides, but some OPs are still among the insecticides most used in Canada. Exposure to elevated levels of OPs during pregnancy has been associated with adverse birth outcomes and poorer neurodevelopment in children. The objective of the present study was to examine the relationship between the concentrations of OP pesticides urinary dialkyl phosphate (DAP) metabolites and various factors that are potential sources of exposure or determinants of DAP levels. In the Maternal-Infant Research on Environmental Chemicals (MIREC) Study, six DAPs were measured in 1st trimester urine samples of 1884 pregnant women living in Canada. They were grouped into sums of dimethyl alkyl phosphates (DMAP) and diethyl alkyl phosphates (DEAP) for statistical analysis. We found that 93% of women had at least one DAP detected in their urine. Geometric means (GM) of specific gravity-corrected levels for urine dilution were 59 (95% CI 56-62) and 21 (95% CI 20-22) nmol/L for DMAP and DEAP, respectively. The following characteristics were significantly associated with higher urinary concentrations of DMAP or DEAP: higher education, nulliparous, normal pre-pregnancy body mass index, non-smoker, not fasting at sampling, winter season at sampling, and early and late day collection times. Dietary items that were significantly related with higher urinary concentrations included higher intake of citrus fruits, apple juice, sweet peppers, tomatoes, beans and dry peas, soy and rice beverages, whole grain bread, white wine and green and herbal teas. This study indicates that exposure to these compounds is quasi-ubiquitous. The factors associated with greater DAP levels identified here could be useful to regulatory agencies for risk analysis and management. However, some exposure misclassification might occur due to the single DAP measurement available, and to the presence of preformed DAPs in the environment.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".