The Oslo Health Study: A Dietary Index estimating high intake of soft drinks and low intake of fruits and vegetables was positively associated with components of the metabolic syndrome
Bibliographic record
Abstract
A previous finding that soft drink intake is associated with increased serum triglycerides and decreased high-density-lipoprotein (HDL) cholesterol, both components of the metabolic syndrome (MetS), raises the question of whether other aspects of an unhealthy diet might be associated with MetS. Main MetS requirements are central obesity and 2 of the following: increased triglycerides, low HDL, increased systolic or diastolic blood pressure, and elevated fasting blood glucose. Of the 18 770 participants in the Oslo Health Study, there were 13 170 respondents (5997 men and 7173 women) with data on MetS factors (except fasting glucose) and on the components used to determine the Dietary Index score (calculated as the intake estimate of soft drinks divided by the sum of intake estimates of fruits and vegetables). MetSRisk was calculated as the sum of arbitrarily weighted factors positively associated with MetS divided by HDL cholesterol. Using regression analyses, the association of the Dietary Index with MetSRisk, with the number of MetS requirements present, and with the complete MetS was studied. In young, middle-aged, and senior men and women, there was, in general, a positive association (p < 0.001) between the Dietary Index and the MetS estimates, which persisted in regression models adjusted for sex, age, time since the last meal, intake of cheese, intake of fatty fish, intake of coffee, intake of alcohol, smoking, physical activity, education, and birthplace. Thus, an index reflecting a high intake of soft drinks and a low intake of fruit and vegetables was positively and independently associated with aspects of MetS.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".