Analysis of tobacco control policies in Nigeria: historical development and application of multi-sectoral action
Bibliographic record
Abstract
BACKGROUND: Tobacco use is a major risk factor for non-communicable diseases and policy formulation on tobacco is expected to engrain international guidelines. This paper describes the historical development of tobacco control policies in Nigeria, the use of multi-sectoral action in their formulation and extent to which they align with the World Health Organisation "best buy" interventions. METHODS: We adopted a descriptive case study methodology guided by the Walt and Gilson Policy Analysis Framework. Data collection comprised of document review (N = 18) identified through search of government websites and electronic databases with no date restriction and key informant interviews (N = 44) with stakeholders in public and private sectors. Data was integrated and analyzed using content analysis. Ethical approval was granted by the University of Ibadan and University College Hospital Ethics Review Committee. RESULTS: Although the agenda for development of a national tobacco control policy dates back to the 1950s, a comprehensive Framework Convention for Tobacco Control (FCTC) compliant policy was only developed in 2015, 10 years after Nigeria signed the FCTC. Lack of funding and conflict of interest (of protecting citizens from harmful effect of tobacco viz. a viz. the economic gains from the industry) are the major barriers that slowed the policy process. Current tobacco -related policies developed by the Federal Ministry of Health were formulated through strong multi-sectoral engagement and covering all the four WHO "best buy" interventions. Other policies had limited multi-sectoral engagement and "best buy" strategies. The tobacco industry was involved in the development of the Standards for Tobacco Control of 2014 contrary to the long-standing WHO guideline against engagement of the industry in policy formulation. CONCLUSIONS: Nigeria has a comprehensive national policy for tobacco control which was formulated a decade after ratification of the FCTC due to constraints of funding and conflict of interest. Not all the tobacco control policies in Nigeria engrain the principles of multisectorality and best buy strategies in their formulation. There is an urgent need to address these neglected areas that may hamper tobacco control efforts in Nigeria.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".