Cardiovascular disease risk perception among community-dwelling adults in southwest Nigeria: A mixed-method study
Bibliographic record
Abstract
OBJECTIVE: The rising prevalence of cardiovascular diseases (CVD) remains a global concern. In Nigeria, the current prevalence of CVD was 76.11% with its attendance burden. The CVD risk perception of individuals is a precursor to the desired lifestyle modification necessary for CVD prevention and management. This study assessed the CVD risk perception and sociodemographic determinants among rural and urban dwellers in southwest Nigeria. METHODS: The study employed a convergent parallel mixed-methods design involving concurrent data collection. The participants' CVD risk perception was obtained using the Perception of Risk of Heart Disease Scale (quantitative data) and a validated focus group discussion (FGD) guide (qualitative data). Quantitative analysis was completed using descriptive statistics, Phi, Cramer's V, and multivariate linear regression, while the FGD was thematically analysed. RESULTS: The quantitative study involved 1,493 participants (62.4% women) with a mean age of 46.90±15.65 years, while the FGD involved 53 participants (52.8% women) with a mean age of 50.10±13.5 years. Over a quarter (28%) of the participants had a poor CVD risk perception; the mean score was 44.40±8.07. Rural residents had a significantly poorer CVD risk perception than their urban counterparts (Mean difference = -3.16, p<0.001). Having tertiary education (β = 0.100, p < 0.001), living in urban areas (β = 0.174, p<0.001), and living in Lagos (β = 0.074, p = 0.013) and in Oyo, other than Ogun state (β = -0.156, p<0.001) significantly predicted having a good perception of CVD risk. FGD produced three themes: knowledge about CVD, CVD risk factors, and CVD prevention. CONCLUSION: Participants had a fair understanding of the causes and prevention of CVD. Yet, a substantial portion underestimated their own risk of developing CVD, particularly rural dwellers and people with lower education. More public health education is required to improve the CVD risk perception in southwestern Nigeria.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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".