Investigating the relationship of serum vitamin D levels with blood pressure and hypertension risk in The HUNT Study: Using traditional observational and Mendelian randomization approaches
Bibliographic record
Abstract
Abstract Background Limited studies have triangulated the relationship between serum vitamin D [25(OH)D] levels and systolic blood pressure (SBP), diastolic blood pressure (DBP) or hypertension risk using traditional observational and Mendelian randomization (MR) approaches. Methods and results Data were obtained from the Norwegian Trøndelag Health Study (HUNT). A cross-sectional study was performed among 5854 participants from HUNT2. Among them, 3592 participants were followed over 11 years for a prospective analysis. Furthermore, a one-sample MR was conducted with 86,324 participants from HUNT. An externally weighted genetic risk score based on 19 genetic variants for 25(OH)D was used as instrument and the Wald ratio method was applied to evaluate causal associations. Additionally, two-sample MR were performed using updated publicly available data. Our cross-sectional analyses showed a 25 nmol/L increase in 25(OH)D was associated with a 1.73 mmHg decrease in SBP (95 % CI -2.46 to -1.01), a 0.91 mmHg decrease in DBP (95% CI - 1.35 to -0.47) and 19% lower prevalence of hypertension (OR 0.81, 95% CI 0.74 to 0.90) after adjusting for important confounders. However, these associations disappeared in prospective analyses. Both one-sample and two-sample MR results suggested no causal associations. Conclusions Cross-sectional findings of inverse associations between serum 25(OH)D levels and blood pressure or hypertension were not supported by results from the prospective and MR analyses, suggesting no causal links. Clinical Perspective What Is New? We triangulated the potential relationships of serum 25(OH)D with blood pressure and hypertension using several observational methods such as cross-sectional, prospective cohort, one-sample and two-sample Mendelian randomization (MR) approaches. What Are the Clinical Implications? The consistency across the prospective, one-sample MR and two-sample MR analyses enhanced the robustness of the findings of no causal association between vitamin D and blood pressure or hypertension. Clinicians should be cautious when recommending vitamin D supplementation to the general population for the prevention of cardiovascular diseases.
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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 | 0.057 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".