The prevalence of excess weight among Vietnamese adults: A pooled analysis of 58 studies with more 430 thousand participants over the last three decades
Bibliographic record
Abstract
Background Chronic noncommunicable diseases (NCDs) associated with excess weight as a significant risk factor, but few studies have been sufficient enough to examine the magnitude of excess weight of Vietnamese adults. This review aimed to provide a generalized estimate of the prevalence of excess weight among Vietnamese adults. Methods PubMed, Scopus and national database were used to identify articles published up to May 2022. The Newcastle-Ottawa Quality Assessment Scale was used to rate the study quality. The data was analyzed using RStudio software, and the combined effects were estimated using random-effects meta-analysis. The Cochran's Q-test and the I 2 test were employed to examine heterogeneity, and subgroups were conducted. Egger's test and visual inspection of the symmetry in funnel plots were used to determine publication bias. Results 58 studies with 432,585 participants from 1998 to 2020 were suitable for inclusion in the final model after meeting the prerequisites. Over the last three decades, the combined pooled prevalence of excess weight among adults in Vietnam was 20.3% (95% CI: 15.2–26.6). Notably, this proportion has a tendency to go up between 1998 and 2020. Moreover, rates of excess weight were found to be substantially higher in non-national studies (23.1%, 17.3–30.1) compared to national studies (8.4%, 3.6–18.3) and significantly higher when Asian and Pacific cut-offs (27.6%, 20.0–36.7) were used rather than WHO classification (11.2%, 6.7–18.0). Conclusion The findings suggest healthcare professionals and policymakers should focus more on designing and implementing preventive initiatives to lower the rising prevalence of excess weight adults in Vietnam.
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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 | 0.024 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.031 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".