Knowledge of cardiovascular disease risk factors among the Canadian population: relationships with indicators of socioeconomic status.
Bibliographic record
Abstract
BACKGROUND: We examined the ability of adult Canadians to recall cardiovascular disease risk factors to determine the associations between their ability to recall risk factors for cardiovascular disease and their socioeconomic status. METHODS: This study used the database assembled by the Canadian Heart Health Surveys Research Group between 1986 and 1992--a stratified representative sample comprising 23,129 Canadian residents aged 18 to 74. Nurses administered a standard questionnaire asking respondents to list the major risk factors for cardiovascular disease: fat in food, smoking, lack of exercise, excess weight, elevated blood cholesterol and high blood pressure. Six logistic regressions examined the multivariate associations between ability to recall each risk factor with education, income adequacy, occupation, sex, age, marital status and province of residence. RESULTS: More people knew about the behaviour-related risk factors for cardiovascular disease than about the physiologic risk factors: 60% recalled fat in food, 52% smoking and 41% lack of exercise, but only 32% identified weight, 27% cholesterol and 22% high blood pressure. Education was the socioeconomic status indicator most strongly and consistently associated with the ability to recall risk factors for cardiovascular disease. The odds ratios of reporting an association of the risks between people with elementary education and those with university degrees varied between 0.16 (95% confidence interval 0.12 to 0.22) for lack of exercise to 0.55 (95% confidence interval 0.39 to 0.77) for smoking. INTERPRETATION: People in categories at greater risk of cardiovascular disease, such as those aged 65 or more or those with only elementary education, are less able to recall important cardiovascular disease risk factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".