The Oslo Health Study: Soft drink intake is associated with the metabolic syndrome
Bibliographic record
Abstract
It has been reported that the frequency of cola intake (COLA) is positively associated with serum triglycerides and negatively associated with high-density-lioprotein (HDL) cholesterol, both components of the metabolic syndrome (MetS). The question now is whether noncola soft drink intake (NCOLA) is associated with MetS. Among the 18 770 participants in the Oslo Health Study, 5373 men and 6181 women had data on COLA and NCOLA and risk factors for MetS (except fasting glucose). Main MetS requirements are central obesity and 2 of the following: increased triglycerides, low HDL cholesterol, increased systolic or diastolic blood pressure, and elevated fasting blood glucose. The MetSRisk index was calculated to estimate many MetS components. Using regression analyses, the association between COLA (NCOLA) and MetS (MetSRisk) was studied. In young (aged 30 years), middle-aged (aged 40 and 45 years), and senior (aged 59 and 60 years) men and women, there was, in general, a positive correlation between COLA and MetSRisk, and between COLA and single MetS risk factors, except HDL cholesterol, which was negatively correlated. A less consistent picture was found for NCOLA. By regression analyses, after adjustment for sex, age, time since last meal, and use of sugar-sweetened soft drinks, a positive association between COLA (NCOLA) and MetSRisk (MetS) was still found. However, when also controlling for cheese, fatty fish, coffee, alcohol, smoking, physical activity, education, and birthplace, only the association with COLA remained significant, irrespective of the presence or absence of sugar. In conclusion, the self-reported intake frequency of soft drinks can be positively associated with MetS.
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.
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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".