Risk Factors for and Barriers to Control Type-2 Diabetes among Saudi Population
Bibliographic record
Abstract
BACKGROUND: The prevalence of Type-2 Diabetes is dramatically increasing in urban areas within Saudi Arabia. Hence, Type-2 Diabetes has now become the most common public health problem. Understanding the major risk factors for and barriers to control Type-2 Diabetes may lead to strategies to prevent, control, and reduce in the burden of disease cases. OBJECTIVE: To describe risk factors for and barriers to control Type- 2 Diabetes in Saudi Arabia. METHODS: The literature search was conducted on risk factors for and barriers to control Type- 2 Diabetes in Saudi Arabia using the databases PubMed, MEDLINE, and Google Scholar (2007-2015). The literature search yielded 80 articles, of which 70 articles were included in this review after excluding non-relevant articles. RESULTS: The literature review revealed that obesity, physical inactivity, unhealthy diet, smoking, and aging are the major risk factors for Type-2 Diabetes in Saudi Arabia. Further, the review allocated a complex set of barriers including, lack of education, social support, and healthy environment. These barriers may hinder Saudis with Type-2 Diabetes from controlling their disease. CONCLUSION: The prevalence of Type-2 Diabetes is high among the Saudi population and represents a major public health problem. Effective research programs are needed to address the modifiable risk factors for and barriers to control Type-2 Diabetes among Saudi population.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".