Environmental contaminant body burdens and the relationship with blood pressure measures among Indigenous Canadians: Results from the Nituuchischaayihtitaau Aschii: Multi-Community Environment-and-Health Longitudinal Study in Eeyou Istchee, a cross-sectional study
Bibliographic record
Abstract
OPS 18: Cardiometabolic effects of chemical exposures, Room 110, Floor 1, August 26, 2019, 1:30 PM - 3:00 PM Blood pressure (BP) increments increase cardiovascular disease (CVD) risk. Recently, clinical practice guidelines lowered hypertension definitions. Indigenous Canadians experience slightly higher CVD compared to non-Indigenous Canadians. Environmental contaminant body burden from persistent organochlorine pollutants, organic compound concentrations (OCs), and metals have been linked with hypertension risk. This study examined the role of OCs, and metals on hypertension among Indigenous Canadians. Methods: Using data from the Environment-and-Health Study in Eeyou Istchee territory of northern Québec, Canada, the sample restricted to adults over 20-years of age, with valid BP measures and detectable body burden mixtures. In total, n=774 participants were eligible, of which, n=452, 58% females. Principal Component Analysis (PCA) was used to reduce the complexity of the contaminant data. Orthogonal principal component (PC) variables were used as independent predictors in both multivariable linear regression, and modified Poisson regression models with robust variance estimation, deriving relative risk for hypertension defined using systolic BP (SBP) ≥140 mm Hg or diastolic BP (DBP) ≥90 mm Hg. Results: Three PCs were extracted from the PCA analysis. PC-1, PC-2, and PC-3, explained 72%, 5.5% and 4.8% of the variation, respectively. Polychlorinated biphenyls and OCs positively highly loaded on the first axes (PC-1), followed by moderate loadings for metal mercury. Lead loaded positively, whereas DDT negatively loaded on PC-2, and cadmium strongly loaded on the third PC axis. Systolic BP measures were significantly associated with PC-1 across all models. In the final model, PC-1 increased SBP β=1.72 (95% CI 0.42, 3.02). PC-3, represented by cadmium was associated with SBP but after adjusting for body mass, PC-3 was no longer associated with SBP. Hypertension was consistently and significantly associated with PC-1 across models, RR=1.14 (95% CI 1.02, 1.28) in the final adjusted model. Conclusion: Using a reduction technique, this cross-sectional analysis found OCs to be associated with increased SBP.
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 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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".