Sugar‐sweetened soft drinks, diet soft drinks, and serum uric acid level: The third national health and nutrition examination survey
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Sugar-sweetened soft drinks contain large amounts of fructose, which may significantly increase serum uric acid levels and the risk of gout. Our objective was to evaluate the relationship between sugar-sweetened soft drink intake, diet soft drink intake, and serum uric acid levels in a nationally representative sample of men and women. METHODS: Using data from 14,761 participants age>or=20 years from the Third National Health and Nutrition Examination Survey (1988-1994), we examined the relationship between soft drink consumption and serum uric acid levels using linear regression. Additionally, we examined the relationship between soft drink consumption and hyperuricemia (serum uric acid level>7.0 mg/dl for men and >5.7 mg/dl for women) using logistic regression. Intake was assessed by a food-frequency questionnaire. RESULTS: Serum uric acid levels increased with increasing sugar-sweetened soft drink intake. After adjusting for covariates, serum uric acid levels associated with sugar-sweetened soft drink consumption categories (<0.5, 0.5-0.9, 1-3.9, and >or=4 servings/day) were greater than those associated with no intake by 0.08, 0.15, 0.33, and 0.42 mg/dl, respectively (95% confidence interval 0.11, 0.73; P<0.001 for trend). The multivariate odds ratios for hyperuricemia according to the corresponding sweetened soft drink consumption levels were 1.01, 1.34, 1.51, and 1.82, respectively (P=0.003 for trend). Diet soft drink consumption was not associated with serum uric acid levels or hyperuricemia (multivariate P>0.13 for trend). CONCLUSION: These findings from a nationally representative sample of US adults suggest that sugar-sweetened soft drink consumption is associated with serum uric acid levels and frequency of hyperuricemia, but diet soft drink consumption is not.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it