Exposure of pregnant women to neonicotinoids in Wenzhou City, East China: A biomonitoring study
Bibliographic record
Abstract
BACKGROUND: China produces and consumes a large amount of neonicotinoids. A non-negligible exposure to neonicotinoids might occur for Chinese pregnant women, but relevant data remain limited. OBJECTIVE: To investigate the exposure to neonicotinoids by urinary biomonitoring in pregnant women from Wenzhou City, East China. METHODS: We selected 432 pregnant women in Wenzhou City in 2022. A total of eight parent neonicotinoids and four metabolites were determined in single spot urine by liquid chromatography coupled to mass spectrometry. Basic characteristics, physical activity, pre-pregnant body mass index, and intake of drinking water and food were investigated by the questionnaire. Health risk was assessed by hazard quotient (HQ) and hazard index (HI) based on human safety thresholds derived from different health endpoints. RESULTS: Neonicotinoids and their metabolites in urine had a detection frequency between 0 % and 80.1 %. At least one neonicotinoid or metabolite was detected in 93.5 % of urine samples. Except for clothianidin (51.2 %) and N-desmethyl-acetamiprid (80.1 %), the detection frequencies of other neonicotinoids and metabolites ranged from 0 % to 43.8 %. The summed concentrations of all neonicotinoids and their metabolites ranged from < LOD to 222.83 μg/g creatinine with the median concentration of 2.58 μg/g creatinine. Maternal age, educational level, occupation, household income, screen time, and pre-pregnant body mass index were associated with detection frequencies or concentrations of neonicotinoids and their metabolites. Pregnant women with higher consumption frequencies of wheat, fresh vegetable, shellfish, fresh milk, and powdered milk had higher detection frequencies of neonicotinoids and their metabolites. Both HQ and HI were less than one. CONCLUSIONS: Overall, pregnant women in Wenzhou City showed a notable frequency of exposure to at least one neonicotinoid, although the exposure frequency for each specific neonicotinoid was generally low. Several food items derived from plants and animals were potential exposure sources. A low health risk was found based on current safety thresholds.
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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) | 0.002 | 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".