Associations between persistent organic pollutants and blood pressure in a native population of Quebec (Canada)
Bibliographic record
Abstract
Background: Recent evidence suggests that exposure to persistent organic pollutants (POPs) increase the risk of hypertension in environmentally exposed populations. High POP levels have been detected in Arctic populations and the exposure is related to high consumption of fish and marine mammals, which represents the traditional diet of these populations. Aim: We examined the associations between polychlorinated biphenyls (PCBs), organochlorine (OC) pesticides and hypertension among Inuit from Nunavik (Quebec, Canada). Methods: A complete set of data was obtained for 315 Inuit ? 18 years who participated in the “Santé Quebec” health survey that was conducted in the 14 villages of Nunavik. Fourteen polychlorinated biphenyls (PCBs) and 8 OC pesticides or their metabolites were quantified in plasma samples using a gas chromatography method. Blood pressure (BP) was measured using a standardised protocol and information regarding anti-hypertensive medication was obtained through questionnaires. The associations between log-transformed POPs and hypertension (systolic BP ? 140 mm Hg, diastolic BP ? 90 mm Hg or anti-hypertensive medication) were analyzed using multiple logistic regressions. Results: Total PCBs as well as the sum of non-dioxin-like PCBs were significantly associated with higher risk of hypertension. Furthermore, the risk of hypertension increased with higher plasma concentrations of congeners 101, 105, 138 and 187. Regarding OC pesticides, p,p’-dichlorodiphenyldichloroethylene (p,p’-DDE) was associated with increased risk of hypertension while inverse associations were observed with p,p’-dichlorodiphenyltrichloroethane (p,p’-DDT), ?-hexachlorocyclohexane (HCH) and oxychlordane. Conclusions: Some PCB congeners were associated with higher risk of hypertension in this highly exposed population. However, the analyses of OC pesticides revealed divergent results, which need to be confirmed in further cohort and experimental studies.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".