Tobacco control in the Eastern Mediterranean region: implementation progress and persisting challenges
Bibliographic record
Abstract
Tobacco use is the leading cause of preventable mortality worldwide, projected to claim 1 billion lives in the twenty-first century.1 Tobacco prevalence rates are expected to decrease across all the WHO regions by 2025 as a result of tobacco control efforts. However, the smallest decline is projected in the Eastern Mediterranean region (EMR)—from 33.3% in 2020 to 31.0% in 2025—making it almost certain that the region will not achieve WHO’s 30% relative reduction target by 2025.1 The EMR includes 22 member states, with a total population of nearly 680 million that is diverse in terms of demographic, geographic, political and socioeconomic characteristics. The EMR has a history of conflict and protracted political and humanitarian crises. These unstable conditions, in addition to underdeveloped public health systems,2 have undermined tobacco control efforts and contributed to the persistence of weak tobacco regulatory environments across countries in the region.3 Moreover, about one-third of the region’s population is between the ages of 15 and 29 years,4 representing a critical subgroup particularly susceptible to tobacco marketing. According to WHO estimates in 2021,1 the age-standardised current tobacco smoking prevalence among individuals aged 15 years or older in the region ranged from 8.1% in Oman to 35.0% in Jordan and Lebanon. Among men, the rates were highest in Jordan (57.1%), Egypt (47.6%), Tunisia (45.4%) and Lebanon (41.63%), and lowest in Oman (16.0%). Prevalence of tobacco smoking is markedly lower among women, ranging from 0.3% in Oman to 28.2% in Lebanon and 12.9% in Jordan (online supplemental table).1 Waterpipe tobacco smoking has spread rapidly in the region over the past three decades, especially among young people in the region.5 Although waterpipe smoking prevalence is higher among men in most EMR countries, the gender gap is smaller than that for cigarette smoking.5 Various factors have contributed to the rise in waterpipe smoking rates, including the introduction of flavoured tobacco, the perception of reduced harm and addiction relative to cigarette smoking, and inadequate policies and regulations addressing waterpipe smoking.6
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".