Independent association of serum retinol and β‐carotene levels with hyperuricemia: A national population study
Bibliographic record
Abstract
OBJECTIVE: Uses of synthetic vitamin A derivatives (e.g., isotretinoin used for severe acne) and high doses of preformed vitamin A have been implicated in the pathogenesis of hyperuricemia and gout, whereas a trial reported that β-carotene may lower serum uric acid (UA) levels. We evaluated the potential population impact of these factors on serum UA in a nationally representative sample of US adults. METHODS: Using data from 14,349 participants ages ≥20 years in the Third National Health and Nutrition Examination Survey (1988-1994), we examined the relationship between serum retinol, β-carotene, and UA levels using weighted linear regression. Additionally, we examined the relationship with hyperuricemia using weighted logistic regression. RESULTS: Serum UA levels increased linearly with increasing serum retinol levels, whereas serum UA levels decreased with increasing serum β-carotene levels. After adjusting for age, sex, dietary factors, and other potential confounders, the serum UA level differences from the bottom (referent) to the top quintiles of serum retinol levels were 0, 0.16, 0.32, 0.43, and 0.71 mg/dl (P for trend <0.001), and for β-carotene were 0, -0.15, -0.29, -0.27, and -0.40 mg/dl (P for trend <0.001), respectively. Similarly, the multivariate odds ratios of hyperuricemia from the bottom (referent) to top quintiles of serum retinol levels were 1.00, 1.30, 1.83, 2.09, and 3.22 (P for trend <0.001) and for β-carotene were 1.00, 0.85, 0.68, 0.73, and 0.54 (P for trend <0.001), respectively. The graded associations persisted across subgroups according to cross-classification by both serum retinol and β-carotene levels. CONCLUSION: These nationally representative data raise concerns that vitamin A supplementation and food fortification may contribute to the high frequency of hyperuricemia in the US population, whereas β-carotene intake may be beneficial against hyperuricemia. The use of β-carotene as a novel preventive treatment for gout deserves further investigation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.000 | 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".