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Conceptualising changes to tobacco and alcohol policy as affecting a single interlinked system
Duncan Gillespie1,2,3, Jenny Hatchard4,5, Hazel Squires6,4
1School of Health and Related Research, The University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK. duncan.gillespie@sheffield.ac.uk.
BMC Public Health
|January 5, 2021
Summary
Understanding the complex interplay between tobacco and alcohol policies is crucial for effective public health. This study identifies key mechanisms by which individuals and industries influence policy outcomes, guiding better health economic modeling.
Area of Science:
- Public Health Policy
- Health Economics
- Non-communicable Disease Prevention
Background:
- Coordinated public health policy requires conceptualizing tobacco and alcohol policies as an interlinked system.
- Health economic models must understand system complexity to effectively inform policy changes.
- Developing conceptual understanding of policy-system interactions is vital for accurate outcome prediction.
Purpose of the Study:
- To develop a conceptual understanding of the system linking tobacco and alcohol policy changes to outcomes.
- To support the development and interpretation of health economic models for these policies.
- To identify key components and mechanisms within the joint tobacco-alcohol policy system.
Main Methods:
- A workshop involving UK academics and policy professionals was conducted.
- Participant discussions were informed by a literature review and survey.
- Thematic analysis was used to identify system components and mechanisms.
Main Results:
- Eleven mechanisms identified for individual modification of policy effects on tobacco and alcohol consumption.
- Ten industry mechanisms identified to reduce policy effectiveness or enact countermeasures.
- Eighteen research questions proposed for future investigation into policy outcomes.
Conclusions:
- Health economic models must account for individual and industry modifications of policy effects.
- Consideration of unequal societal distribution of outcomes is essential.
- Modelled evidence interpretation requires an understanding of the simplified system representation.
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