Predictors of Blood Pressure, Cholesterol, and Cardiovascular Screening Among Saudis at Primary Healthcare Settings in Riyadh, Saudi Arabia
Bibliographic record
Abstract
Purpose: This study was conducted to estimate proportion of individuals undergoing screening for cardiovascular disease (CVD) and its risk factors and to identify predictors of CVD, blood pressure, and blood cholesterol screening. Patients and Methods: This cross-sectional study was conducted in 48 primary healthcare centers in Saudi Arabia and 14,239 participants were enrolled. The analysis was performed in SPSS version 26 and adjusted odds ratios (AOR) and 95% Cis were reported. Results: Blood pressure screening was reported by 35.3%, cholesterol screening by 9.3%, and cardiovascular screening by 3.7%. Significant positive predictors for blood pressure screening included older age (50-75 years: AOR 1.34, 95% CI: 1.20-1.50; ≥75 years: AOR 2.12, 95% CI: 1.84-2.43), being married (AOR: 1.15; 95% CI: 1.04-1.27), non-smoking (AOR: 1.97; 95% CI: 1.79-2.17), physical activity (AOR: 1.16; 95% CI: 1.05-1.28), and diabetes (AOR: 2.14; 95% CI: 1.88-2.44). For cholesterol screening, significant positive predictors were older age (≥75 years: AOR 1.89, 95% CI: 1.56-2.29), unemployment (AOR: 1.26; 95% CI: 1.10-1.45), insurance coverage (AOR: 1.52; 95% CI: 1.33-1.74), smoking (AOR: 1.32; 95% CI: 1.14-1.53), diabetes history (AOR: 1.33; 95% CI: 1.09-1.61), and hypertension (AOR: 1.66; 95% CI: 1.36-2.02). For cardiovascular screening, significant positive predictors included older age (≥75 years: AOR 1.81, 95% CI: 1.35-2.43), unemployment (AOR: 1.53; 95% CI: 1.24-1.88), insurance coverage (AOR: 1.56; 95% CI: 1.27-1.92), smoking (AOR: 1.89; 95% CI: 1.52-2.34), diabetes (AOR: 1.85; 95% CI: 1.41-2.43), and high cholesterol (AOR: 1.76; 95% CI: 1.31-2.36). Conclusion: A very low proportion of Saudi residents have undergone blood pressure, cholesterol, and CVD screening. Common predictors of screening included older age, insurance coverage, diabetes, hypertension, physical activity, and high cholesterol levels. Low prevalence of screening is alarming, and Saudi Government needs to implement strategies that can help increase proportion of Saudi residents who receive blood pressure, cholesterol, and CVD screening.
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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 | 0.000 |
| 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".