Lay knowledge of cardiovascular disease and risk factors in three communities in Accra, Ghana: a cross-sectional survey
Bibliographic record
Abstract
OBJECTIVES: Cardiovascular disease is a major cause of morbidity and mortality in Ghana, and urban poor communities are disproportionately affected. Research has shown that knowledge of cardiovascular disease (CVD) is the first step to risk reduction. This study examines knowledge of CVD and risk factors and determinants of CVD knowledge in three urban poor communities in Accra, Ghana. METHODS: Using the Cardiovascular Disease Risk Factors Knowledge Level Scale, which has been validated in Ghana, we conducted a cross-sectional survey with 775 respondents aged 15-59 years. CVD knowledge was computed as a continuous variable based on correct answers to 27 questions, and each correct response was assigned one point. Linear regression was used to determine the factors associated with CVD knowledge. RESULTS: The mean age of the participants was 30.3±10.8 years and the mean knowledge score was 19.3±4.8. About one-fifth of participants were living with chronic diseases. Overall, 71.1% had good CVD knowledge, and 28.9% had moderate or poor CVD knowledge. CVD knowledge was low in the symptoms and risk factor domains. A larger proportion received CVD knowledge from radio and television. The determinants of CVD knowledge included ethnicity, alcohol consumption, self-reported health and sources of CVD knowledge. CVD knowledge was highest among a minority Akan ethnic group, those who were current alcohol consumers and those who rated their health as very good/excellent, compared with their respective counterparts. CVD knowledge was significantly lower among those who received information from health workers and multiple sources. CONCLUSION: This study underscores the need for health education programmes to promote practical knowledge on CVD symptoms, risks and treatment. We outline health systems and community-level barriers to good CVD knowledge and discuss the implications for developing context-specific and culturally congruent CVD primary prevention interventions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".