Evaluating compliance of labelling on tobacco packets in countries across the Middle East
Bibliographic record
Abstract
Background Despite knowledge of harms, smoking rates remain high and continue to rise in Middle Eastern Countries. Initiatives such as the FCTC were developed to address the tobacco epidemic through health policy. Despite its positive impact, implementation remains a challenge. In this study, we assess compliance of labelling on tobacco packets from twelve Middle Eastern countries with national legislation and FCTC recommendations. Methods Investigators from twelve Middle Eastern Countries collected at least 10 unique packets of the most commonly consumed and cheapest brands of cigarettes between January 2015 and November 2016. The countries included Bahrain, Israel, Kuwait, Oman, Qatar, Saudi Arabia, United Arab Emirates (High-Income Countries - HIC), Jordan, Lebanon, Turkey (Upper-Middle Income Countries - UMIC), Egypt, and Palestine (Low-Middle-Income Countries - LMIC). A total of 140 packets were inspected using a structured data collection tool; all labels were assessed for content, size, and location. Results Health Warnings were present on the Principal Display Area (PDA - front and back panel) on 98% of packets. All countries except for Palestine met or exceeded the WHO minimum recommendations that 30% of the packets PDA should be covered by a health warning label. However, only Bahrain, Israel, Kuwait, Qatar, and Turkey met their own national legislation about the minimum area of the packets PDA that must be covered by a health warning label. Promotional labels were present on all packages. Deceptive terms such as 'light' and 'blue' were found on 55% of all packs. Conclusions Most countries were compliant with WHO recommendations on health warning labelling. However, there is poor compliance and implementation of national legislation in these countries. Promotional and deceptive labelling were present on packets from all countries despite being banned accordingly to WHO recommendations and national legislation. Monitoring labelling on tobacco packets with country-specific feedback may help improve compliance and implementation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".