Soft drinks, fructose consumption, and the risk of gout in men: prospective cohort study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To examine the relation between intake of sugar sweetened soft drinks and fructose and the risk of incident gout in men. DESIGN: Prospective cohort over 12 years. SETTING: Health professionals follow-up study. PARTICIPANTS: 46 393 men with no history of gout at baseline who provided information on intake of soft drinks and fructose through validated food frequency questionnaires. MAIN OUTCOME MEASURE: Incident cases of gout meeting the American College of Rheumatology survey criteria for gout. RESULTS: During the 12 years of follow-up 755 confirmed incident cases of gout were reported. Increasing intake of sugar sweetened soft drinks was associated with an increasing risk of gout. Compared with consumption of less than one serving of sugar sweetened soft drinks a month the multivariate relative risk of gout for 5-6 servings a week was 1.29 (95% confidence interval 1.00 to 1.68), for one serving a day was 1.45 (1.02 to 2.08), and for two or more servings a day was 1.85 (1.08 to 3.16; P for trend=0.002). Diet soft drinks were not associated with risk of gout (P for trend=0.99). The multivariate relative risk of gout according to increasing fifths of fructose intake were 1.00, 1.29, 1.41, 1.84, and 2.02 (1.49 to 2.75; P for trend <0.001). Other major contributors to fructose intake such as total fruit juice or fructose rich fruits (apples and oranges) were also associated with a higher risk of gout (P values for trend <0.05). CONCLUSIONS: Prospective data suggest that consumption of sugar sweetened soft drinks and fructose is strongly associated with an increased risk of gout in men. Furthermore, fructose rich fruits and fruit juices may also increase the risk. Diet soft drinks were not associated with the risk of gout.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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