Examining chronic inflammatory markers on blood pressure measures in the presence of vitamin D insufficiency among indigenous cree adults: results from the cross-sectional Multi-Community Environment-and-Health Study in <i>Eeyou Istchee</i> , Quebec, Canada
Bibliographic record
Abstract
OBJECTIVE: High blood pressure (BP) is a risk factor for cardiovascular disease. Examining the role of inflammatory mediators on BP is important since vitamin D (VD) is a modifiable risk factor, which possibly modulates inflammatory cytokines. This study simulated what are known as average 'controlled direct effects (CDE)' of inflammatory markers, C reactive protein (CRP), tumour necrosis factor-α (TNF-α), and interlukin-6 (IL-6) on continuous BP measures, while fixing VD, an intermediate variable to specific level. DESIGN: Cross-sectional study. SETTING: , Quebec, Canada. PARTICIPANTS: This study recruited 1425 study Indigenous Cree participants from seven Cree communities. Only adults with serum VD levels, inflammatory markers and BP measures were included in this data analysis. PRIMARY AND SECONDARY OUTCOMES MEASURES: Inflammatory markers examined the top 25th exposure percentiles. VD 'insufficiency' (ie, 25-hydroxyvitamin-D levels<50 nmol/L) defined by the Institute of Medicine. CDE for each inflammatory marker in the presence and absence of population VD insufficiency simulated the average direct effect change for systolic and diastolic BP (SBP and DBP) measures. All models were adjusted for exposure-and-mediator outcome relationship. RESULTS: Among 161 participants, 97 (60 %) were female. The prevalence of VD insufficiency was 32%. CDE estimates show in the presence and absence of population vitamin D insufficiency, inflammatory markers have a slightly different association on BP. TNF-α significantly and inversely associated with SBP in the presence of vitamin D insufficiency, fully adjusted model β = -13.61 (95% CI -24.42 to -2.80); however, TNF-α was not associated with SBP in the absence of vitamin D insufficiency. CRP, IL-6 were also not significantly associated with BP measures, although the magnitude of association was greater for those with elevated inflammation and VD insufficiency. CONCLUSION: This novel analysis shows in the presence of VD insufficiency, inflammation (particularly TNF-α) may affect SBP. Additional research is needed to elucidate these findings, and the temporal relationship between these variables.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".