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Record W4311303644 · doi:10.1136/tc-2022-057284

Impact of waterpipe tobacco taxation on consumption, government revenue and premature deaths averted in Jordan, Lebanon and Palestine: a simulation study

2022· article· en· W4311303644 on OpenAlexfundno aff
Mohammed Jawad, Sameera Awawda, Ruba Abla, Ali Chalak, Yousef Khader, Rima Nakkash, Aya Mostafa, Ramzi G. Salloum, Niveen M E Abu-Rmeileh

Bibliographic record

VenueTobacco Control · 2022
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersUniversity of Cape TownInternational Development Research Centre
KeywordsExciseConsumption (sociology)Tax revenueRevenuePalestineGovernment revenueGovernment (linguistics)BusinessEnvironmental healthEconomicsMedicinePublic economicsAncient historyFinance

Abstract

fetched live from OpenAlex

INTRODUCTION: Despite the high prevalence of waterpipe tobacco smoking in the Eastern Mediterranean region, evidence supporting its fiscal measures is limited. We modelled the impact of waterpipe tobacco-specific excise taxes on consumption, government revenue and premature deaths averted in Jordan, Lebanon and Palestine. METHODS: We developed a simulation model using country-specific and market share-specific price, consumption and price elasticity data from WHO, UN Comtrade and nationally representative surveys. We modelled increases to specific excise taxes to meet a 35.9% tax burden on 20 g of waterpipe tobacco in Lebanon and Jordan, in line with the global average, and to double government revenues from excise duties in Palestine, which has surpassed this average. RESULTS: taxes) and $2.39 ($1.72-$4.11) in Palestine per 20 g of waterpipe tobacco. Government revenue increased by $126.3 million in Jordan, $53.8 million in Lebanon and $162.4 million in Palestine while waterpipes smoked decreased by 32.4% in Jordan, 71.0% in Lebanon and 16.3% in Palestine. The corresponding numbers of premature deaths averted annually were approximately 162 000; 1 000 000; and 52 000. DISCUSSION: Increases in waterpipe tobacco-specific excise taxes substantially reduce smoking and increase government revenue and averted premature deaths in Jordan, Lebanon and Palestine. This has positive implications for both public health and financing and should be considered a policy priority.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.303
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2022
Admission routes1
Has abstractyes

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