Prevalence of hypertension and associated factors: a cross-sectional study in Riyadh, Saudi Arabia
Bibliographic record
Abstract
BACKGROUND: Hypertension is a chronic condition that represents a global burden across the world. The burden of hypertension is found to be particularly high in Middle Eastern countries such as Saudi Arabia. This study was undertaken to measure the prevalence of hypertension and its associated factors. An assessment of the impact of hypertension is required to alleviate/reduce the comorbidities and complications associated with hypertension in Saudi Arabia. MATERIALS AND METHODS: A cross-sectional survey was conducted among 14,239 individuals in Saudi Arabia. A valid and reliable questionnaire was administered after randomly selecting study participants from 48 primary healthcare centers. Univariate analysis was performed to investigate the relationship between independent variables and hypertension. P-values less than 0.05 were considered significant. Multivariate logistic regression was used to establish the major associated factors of hypertension among Saudi citizens. A 95% confidence interval (CI) was presented for each of the adjusted odds ratios (AORs). RESULTS: It was found that 11.1% of research participants reported having hypertension. Compared to younger participants of < 50 years, those who are 50 to 75 years old are two times more likely to be hypertensive (AOR: 2.05; 95% CI: 1.68, 2.50). Compared to employed Saudi residents, unemployed residents were 1.43 times more likely to be hypertensive (AOR: 1.43; 95% CI: 1.25, 1.65). The odds of hypertension were higher by 1.73 times among obese than non-obese individuals (95% CI: 1.33, 2.25). Individuals with heart disease were 3.72 times more likely to suffer from hypertension than individuals without heart disease (95% CI: 2.84, 4.88). Similarly, those with high cholesterol levels were 8.37 times more likely to have hypertension than those with low cholesterol levels (95% CI: 6.94, 10.09). Diabetic individuals were 10.45 times more likely to develop hypertension than non-diabetic individuals (95% CI: 8,87, 12.30). CONCLUSION: The prevalence of hypertension found in the current study was 11.1%. Older age, unemployment, insurance coverage, obesity, diabetes, heart disease, and high blood cholesterol were associated with high blood pressure in this study. The findings of this study suggest that researchers and policymakers should target modifiable risk factors to reduce the burden of hypertension among Saudi residents.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".