Undiagnosed hypertension and associated factors among long-distance bus drivers in Addis Ababa terminals, Ethiopia, 2022: A cross-sectional study
Bibliographic record
Abstract
INTRODUCTION: Hypertension is a major public health problem that is often unrecognized, and its detection and control should be prioritized. The level of undiagnosed hypertension and its associated factors among long-distance bus drivers in Ethiopia is unknown. OBJECTIVE: This study aimed to assess the magnitude of undiagnosed hypertension and its associated factors among long-distance bus drivers in Addis Ababa bus terminals. METHODS: A facility-based cross-sectional study was conducted on 391 long-distance bus drivers from December 15, 2021, to January 15 2022 at five cross-country bus terminals in Addis Ababa. A standardized and structured questionnaire was adapted based on the WHO stepwise approach to a non-communicable disease study and translated into Amharic. Data were coded, cleaned, and entered using Epi-data version 4.6 and exported to SPSS version 26. Logistic regression analysis was performed. Variables with a P-value < 0.25 in the bivariable analysis were selected for multivariable logistic regression analysis. Independent variables with a P-value < 0.05 were considered statistically significant. The magnitude of association between independent and dependent variables was measured by odds ratio with a 95% confidence interval. RESULTS: In this study, 391 study participants were involved with a response rate of 97.1%. The prevalence of undiagnosed hypertension was 22.5% (CI: 18.7%, 26.6%). Poor level of knowledge (AOR: 2.00, CI: 1.08, 3.70), long duration of driving per day (AOR: 2.50, 95% CI: 1.37-4.56), habit of chewing of chat (AOR: 2.61, 95% CI: 1.44, 4.73), regular alcohol consumption (AOR = 3.46; 95% CI: 1.70, 7.05), overweight (AOR:3.14, 95%CI: 1.54,6.42) obesity (AOR: 3.21, 95% CI 1.35, 7.61) and regular physical exercise (AOR: 0.16, 95% CI: 0.09, 0.29) were statistically significantly associated with undiagnosed hypertension. CONCLUSION: This study revealed that the prevalence of undiagnosed hypertension among long-distance bus drivers was 22.5%, which was associated with modifiable behavioral factors, lack of regular physical exercise, lack of adequate awareness and high body mass index. RECOMMENDATION: Stakeholders must implement the necessary preventive measures. These include increasing the level of awareness of hypertension among long-distance drivers and developing prevention of hypertension strategies and policies focusing on lifestyle and behavioral modifications.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".