Type 2 diabetes and hypertension in Vietnam: a systematic review and meta-analysis of studies between 2000 and 2020
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to determine the level of type 2 diabetes (T2DM) and hypertension (HTN) in Vietnam and to assess the trend and recommend the future direction of prevention research efforts. DESIGN: We searched scientific literature, databases including PubMed, EMBASE, CINHAL and Google Scholar; grey literature and reference lists for primary research published, nation database websites between 1 January 2000 and 30 September 2020. We adapted the modified Newcastle Ottawa Scale for assessing the quality of the study, as recommended by the Cochrane Collaboration. RESULTS: In total, 83 studies met our inclusion criteria, representing data of approximately 239 034 population of more than 15 years of age in Vietnam. The findings show that prevalence rates varied widely across studies, from 1.0% to 29.0% for T2DM and 2.0% to 47.0% for HTN. For the total study period, pooled prevalence of T2DM and HTN in Vietnam for all studies was 6.0% (95% CI: 4.0% to 7.0%) and 25% (95% CI: 19% to 31%), respectively. Prevalence rate of both T2DM and HTN was higher among the male population compared with female counterpart. CONCLUSION: There is evidence of a rising trend of HTN and T2DM prevalence in Vietnam. Future research should focus on the major drivers, incidence and prognosis of T2DM and HTN. Policy approaches should base upon the trends of T2DM and HTN in Vietnam over the last 20 years and pay more attention on the effective interventions to combat T2DM and HTN. In our study, we included both English and Vietnamese language articles and seems that majority of the articles came from Vietnamese language. PROSPERO REGISTRATION NUMBER: CRD42020182959.
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.025 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".