Regional advocacy workshop on noncommunicable disease priorities among children and adolescents in the Eastern Mediterranean Region
Bibliographic record
Abstract
Background: There has been a surge of noncommunicable diseases (NCDs) globally, and particularly in the Eastern Mediterranean Region. Data indicate a notable prevalence of NCD risk factors among children and adolescents, including physical inactivity, tobacco use, as well as high salt, sugar and fat intake, highlighting the need for urgent actions. Aim: To present key recommendations and follow-up actions from a workshop on noncommunicable diseases among children and adolescents in the Eastern Mediterranean Region. Method: In March 2023, the WHO Regional Office for the Eastern Mediterranean held a workshop in Oman which discussed the challenges, early interventions, policy changes, and prioritization of NCDs prevention for children and adolescents in the region. Results: Participants, including a considerable representation of the youth group, shared experiences on risk factors, prevention, treatment, and suitable platforms for NCD care among children and adolescents, and the importance of systematic monitoring and evaluation. Following the workshop, the youth were engaged in the development of a regionspecific NCDs intervention roadmap. Conclusion: Further youth engagement, multisectoral collaborations, and the establishment of dedicated national authorities to oversee proposed interventions are needed to reduce premature deaths due to NCDs by one-third by 2030, as indicated in the Sustainable Development Goals target 3.4.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".