Fructose and Vitamin C Intake Do Not Influence Risk for Developing Hypertension
Bibliographic record
Abstract
Higher uric acid levels are associated with an increased risk for developing hypertension. Higher intake of fructose increases plasma uric acid levels and higher intake of vitamin C reduces uric acid levels, but whether these nutrients are independently associated with the risk for developing hypertension is unknown. We studied this question by analyzing data from participants of three large and independent prospective cohorts: Nurses' Health Study 1 (n = 88,540), Nurses' Health Study 2 (n = 97,315), and the Health Professionals Follow-up Study (n = 37,375). Relative risks and 95% confidence intervals for incident hypertension were computed according to quintiles of fructose intake and categories of vitamin C intake using multivariable Cox proportional hazards regression. Fructose intake was not associated with the risk for developing hypertension; the multivariable relative risks (95% confidence intervals) for the highest compared with the lowest quintile of fructose intake were 1.02 (0.99 to 1.06) in Nurses' Health Study 1, 1.03 (0.98 to 1.08) in Nurses' Health Study 2, and 0.99 (0.93 to 1.05) in Heath Professionals Follow-up Study. Regarding vitamin C, the relative risks for individuals who consumed > or =1500 mg/d compared with those who consumed <250 mg/d were 0.89 (0.83 to 0.96) in Nurses' Health Study 1, 1.02 (0.91 to 1.14) in Nurses' Health Study 2, and 1.06 (0.97 to 1.15) in Health Professionals Follow-up Study. In conclusion, fructose and vitamin C intake do not substantially influence the risk for developing hypertension.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".