Association between Cardiovascular Disease Risk Factor Knowledge and Lifestyle
Bibliographic record
Abstract
Objective: To relate cardiovascular risk factor knowledge to lifestyle. Methods: In this cross-sectional study, food consumption and lifestyle characteristics were recorded using mailed questionnaires. The dietary pattern was described using the Mediterranean Diet Score (MDS). An open ended questionnaire without predefined choices or answers was used to capture cardiovascular knowledge. Results: Lack of physical activity, smoking and eating too much fat were the 3 most cited potential cardiovascular risk factors, while being overweight, eating too much salt and a low consumption of fruits and vegetables were the least cited risk factors. Age, Body Mass Index, physical activity, smoking, income and dietary habits were not consistently associated with knowledge of risk factors. A low socioeconomic position as measured by the indicator education was associated with a lower knowledge of established and modifiable cardiovascular risk factors. Conclusions: Risk factor knowledge, an essential step in prevention of CVD, is not systematically associated with a healthier lifestyle. The findings of this study confirm that there is a gap between risk factor knowledge and lifestyle.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".