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Tobacco industry data on illicit tobacco trade: a systematic review of existing assessments. | LitMetric

AI Article Synopsis

Article Abstract

Objective: To examine the quality of tobacco industry-funded data on the illicit tobacco trade (ITT) through a systematic review of existing assessments of industry-funded data on ITT.

Data Sources: Papers and reports assessing tobacco industry-funded data on ITT were obtained via searches of 8 academic databases, Google searches and correspondence with ITT experts.

Study Selection: Inclusion criteria identified 35 English-language papers containing an original assessment of tobacco industry-funded data.

Data Extraction: Using a coding framework, information was extracted from the assessments regarding the quality of tobacco industry data. Documents were second-coded, achieving 94% intercoder reliability with all disagreements resolved.

Data Synthesis: Of the 35 assessments reviewed, 31 argued that tobacco industry estimates were higher than independent estimates. Criticisms identified problems with data collection (29), analytical methods (22) and presentation of results (21), which resulted in inflated ITT estimates or data on ITT that were presented in a misleading manner. Lack of transparency from data collection right through to presentation of findings was a key issue with insufficient information to allow replication of the findings frequently cited.

Conclusions: Tobacco industry data on ITT are not reliable. At present, the tobacco industry continues to fund and disseminate ITT research through initiatives such as PMI IMPACT. If industry data on ITT cannot meet the standards of accuracy and transparency set by high-quality research publications, a solution may be to tax tobacco companies and administer the resulting funds to experts, independent of the tobacco industry, who use previously developed reliable models for measuring ITT.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580768PMC
http://dx.doi.org/10.1136/tobaccocontrol-2018-054295DOI Listing

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