Associations between plasma persistent organic pollutants and type II diabetes in Canadians: a nationally-representative, cross-sectional study.
Bibliographic record
Abstract
Background: There is increasing evidence from epidemiological and toxicological studies that persistent organic pollutants (POPs) contribute to the pathogenesis of type II diabetes. Aims: To quantify the associations between plasma POPs and diabetes in cycle 1 (2007-2009) of the Canadian Health Measures Survey, a cross-sectional multistage sample representing 96% of Canadians. Methods: Our sample included 1669 participants aged 20 to 79. We used logistic regression with bootstrap resampling to analyze 19 POPs detectable in at least 60% of plasma samples. Diabetes was defined as any of self-reported doctor diagnosis, use of diabetic medication, fasting HbA1C >=6.5% or fasting glucose >=7.0 mmol/L. Results: The relative odds of diabetes (OR, 95% CI) for interquartile increases in log-transformed and lipid-normalized POPs after adjustment for BMI, waist-to-hip ratio (WHR), BMI-WHR interaction, daily leisure energy expenditure and age (sex was not a confounder) were 2.0 (1.2-3.3) for Arochlor 1260; 1.7 (1.1-2.9) for PCB 138; 2.1 (1.2-3.5) for PCB 153; 1.9 (1.0-3.4) for PCB 163; 1.9 (1.2-3.0) for PCB 170; 1.8 (1.2-2.8) for PCB 180; 1.7 (1.0-2.9) for PCB 187; 1.5 (1.1-2.1) for betahexachlorohexane; 1.4 (1.0-1.8) for hexachlorobenzene and 2.1 (1.0-4.6) for oxychlordane. Adjusted interquartile ORs with 2-sided p value >0.05 were 1.6 (0.9-2.7) for PCB 118; 1.6 (1.0-2.6) for PCB 146; 1.6 (0.9-2.7) for PCB 156; 1.3 (0.9-1.9) for PCB 194; 1.4 (0.9-2.1) for PCB 201; 1.3 (0.9-1.9) for PCB 203; 1.5 (0.9-2.3) for pp-DDE; 1.9 (0.7-4.8) for transnonachlor; and 1.1 (0.8-1.5) for PBDE 47. Conclusions: Most POPs were positively associated with the odds of diabetes in this sample although some estimates had insufficient precision. Our results add to the weight of evidence that POPs contribute to the pathogenesis of type II diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".