Vitamin supplementation and blood pressure in Type 2 diabetes
Bibliographic record
Abstract
AIMS: Vitamin D levels are inversely related to blood pressure. Given that low sun exposure can create a greater reliance on dietary sources of vitamin D, we aimed to determine whether dietary vitamin D and blood pressure associations differ between periods of low and high sun exposure. METHODS: Dietary intake, vitamin supplementation, blood pressure, and anthropometric parameters were assessed each season for 1 year (174 adults with Type 2 diabetes). Separate linear regression models were constructed for high and low sun exposure periods to examine associations of systolic blood pressure with dietary vitamin D intake and vitamin supplement use (adjusted for age, gender, BMI, ethnicity, smoking, alcohol, physical activity, antihypertensive medication and nutrient intake). Robustness of findings was confirmed with within-subject repeated measures analysis, including an interaction term for sun exposure period. RESULTS: Vitamin D intake from food sources was low year-round and no conclusive association with blood pressure was identified during either period. Systolic blood pressure was 5.1 mmHg lower during the low sun exposure period (95% CI 0.5-9.7) in daily supplement users compared with non-users. The interaction term between supplement use and sun exposure period was significant (low sun exposure* no supplement, P = 0.02). Systolic blood pressure was relatively stable in users (low and high sun exposure periods, respectively, mean ± SE: 135.2 ± 2.6 mmHg and 134.2 ± 2.5 mmHg), but not in non-users (140.2 ± 2.7 mmHg and 130.5 ± 2.5 mmHg). CONCLUSIONS: Vitamin supplementation may stabilize systolic blood pressure in adults with Type 2 diabetes across seasons.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".