Associations of Urinary Concentrations of Organophosphates and Pyrethroids with Obesity and Diabetes in Canadian Adults
Bibliographic record
Abstract
Background: The relationships between both obesity and diabetes and the exposure to insecticides, specifically organophosphates and pyrethroids, in the adult Canadian population are not well-understood. Methods: Urinary concentrations of 4 organophosphate metabolites (DEP, DEPT, DMP, and DMPT) and of 4 pyrethroid metabolites (cis-DBCA, cis-DCCA, 3-PBA, and trans-DCCA) were measured for 1,147 adult Canadians aged between 18-79 years old. The geometric means and medians of both creatinine-adjusted and unadjusted urinary insecticide metabolites were estimated. Multiple linear regression and logistic regression analyses were employed to examine the associations between the insecticide metabolite concentrations and obesity and diabetes measures. Results: Both insecticides had detectable levels in over 70% of CHMS respondents. Most metabolites demonstrated a negative significant relationship between their urinary concentrations and BMI as well as waist circumference. No significant relationship was found in regard to HbA1c levels or for diabetes. Conclusion: Organophosphate and pyrethroid metabolites were detected in more than 70% of Canadian adults. Our data showed no evidence that organophosphate and pyrethroid exposures increase the risks of obesity and diabetes in adults. These results should be interpreted with caution as diet may play a large confounding role in the relationships of study.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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 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".