Prevalence of high bloodpressure, hyperglycemia, dyslipidemia, metabolic syndrome and their determinants in Ethiopia: Evidences from the National NCDs STEPS Survey, 2015
Bibliographic record
Abstract
The prevalence of diabetes, dyslipidemias, and high blood pressure is increasing worldwide especially in low and middle income countries. World Health Organization has emphasized the importance of the assessment of the magnitude of the specific disease in each country. We determined the prevalence and determinant factors of high blood pressure, hyperglycemia, dyslipidemias and metabolic syndrome in Ethiopia. A community based survey was conducted from -April to June 2015 using WHO NCD STEPS instrument version 3.1. 2008. Multistage stratified systemic random sampling was used to select representative samples from 9 regions of the country. A total of 10,260 people aged 15-69 years participated in the study. Blood pressure (BP) was measured for 9788 individuals. A total of 9141 people underwent metabolic screening. The prevalence of raised blood pressure (SBP ≥140 and/or DBP ≥ 90 mmHg) was 15.8% (16.3% in females and 15.5% in males). The prevalence of diabetes mellitus (FBS ≥ 126 mg /dl) including those on medication was 3.2% (3.5% males and 3.0% females). The prevalence of impaired fasting glucose was 9.1% with ADA criteria and 3.8% with WHO criteria. Hypercholesterolemia was found in 5.2%, hypertriglyceridemia in 21.0%, high LDL cholesterol occurred in 14.1% and low HDL cholesterol occurred in 68.7%. The prevalence of metabolic syndrome using IDF definition was 4.8% (8.6% in females and vs. 1.8% in males). Advanced age, urban residence, lack of physical exercise, raised waist circumference, raised waist hip ratio, overweight or obesity, and total blood cholesterol were significantly associated with raised blood pressure (BP) and diabetes mellitus. Increased waist- hip ratio was an independent predictor of raised blood pressure, hyperglycemia and raised total cholesterol. Our study showed significantly high prevalence of raised blood pressure, hyperglycemia and dyslipidemia in Ethiopia. Community based interventions are recommended to control these risk factors.
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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 | 0.000 | 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".