Association of health knowledge with adoption of heart healthy behaviours: a cross-sectional analysis using data from the PURE study
Bibliographic record
Abstract
AIMS: This study aims to assess aspects of health knowledge: i) awareness of health effect of tobacco smoking and ii) awareness of preventive actions for heart disease and stroke, and their relationships with adoption of heart healthy behaviours (smoking cessation and utilisation of antihypertensive treatment). METHODS: In this multi-cohort study, we recruited adults aged 35 to 70 years from 21 countries. Data on health effects of tobacco smoking (10 questions) and health actions to prevent heart disease or stroke (11 questions) were collected at baseline. Logistic regression analyses were used to examine the relationship with the outcomes of smoking cessation and use of antihypertensive treatment adjusting for adjusting for possible confounders. RESULTS: Of the 12,962 included in the descriptive analysis, 50.0% were female, 42.9% had no or primary education, and 53.3 % were residing in low or lower middle-income country. Among current and former smokers, having knowledge of health effect of tobacco smoking on heart disease [Adjusted Odds Ratio (aOR): 1.70, 95% CI: 1.19, 2.43)], stroke (1.41, 1.08,1.86), and on heart disease in non-smokers exposed to others smoking (1.40, 1.06,1.86) were significantly and positively associated with smoking cessation compared to those who were not aware of health effects. Knowledge of the importance of reducing dietary salt aOR 1.62 (1.23,2.13), dietary fat aOR 1.56 (1.17,2.08) and exercising more aOR 1.48 (1.22,1.80) to prevent heart disease or stroke were positively associated with taking anti-hypertensive medication compared to those who were not aware of preventative actions. CONCLUSION: This study reinforces that better health knowledge shapes adoption of heart healthy behaviours such as smoking cessation and taking anti-hypertensive treatment even after accounting for baseline education and wealth.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".