Nutritional breakfast quality and cardiometabolic risk factors: Health Survey of São Paulo, a population-based study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association between nutritional quality of breakfast and cardiometabolic risk factors. DESIGN: Cross-sectional study, 2015 Health Survey of São Paulo (2015 ISA-Capital) with Focus on Nutrition Study (2015 ISA-Nutrition). SETTINGS: Population-based study, with a representative sample of adults and elderlies living in São Paulo, Brazil. PARTICIPANTS: The sample included 606 adults (aged 20-59 years) and 537 elderlies (aged ≥60 years) from the 2015 Health Survey of São Paulo. Dietary intake was assessed by at least one 24-h recall. Breakfast quality was evaluated using the proposed Brazilian Breakfast Quality Index (BQI), ranging scores from 0 to 10. BQI associations with sociodemographic, lifestyle, dietetic and cardiometabolic variables were estimated using survey-weighted multiple logistic regression models. RESULTS: Being ≥60 years of age, self-identifying as White or Asian, having a per capita family income with ≥1 minimum wage, being sufficiently active at leisure time and non-smoker were associated with better scores of BQI. A higher BQI score was inversely associated with elevated blood pressure (OR 0·81, 95 % CI 0·70, 0·94), fasting glucose (OR 0·85, 95 % CI 0·73, 0·98), HOMA-IR (OR 0·86, 95 % CI 0·74, 0·98), total cholesterol (OR 0·87, 95 % CI 0·76, 0·99), LDL-C (OR 0·85, 95 % CI 0·74, 0·97), metabolic syndrome (OR 0·82, 95 % CI 0·72, 0·93) and being overweight (OR 0·87, 95 % CI 0·76, 0·99). CONCLUSIONS: Breakfast quality of Brazilian adults needs improvement with disparities across some sociodemographic factors. BQI was associated with lower odds of cardiometabolic risk factors, suggesting a beneficial effect in this population and emphasising the role of breakfast in reducing the risk of CVD.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".