ArticleBMC public health2021
Conceptualising changes to tobacco and alcohol policy as affecting a single interlinked system.
Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Options for modifying UK alcohol and tobacco tax: A rapid scoping review of the evidence over the period 1997-2018.NIHR open research · 2023Pooled it
- "Availability is the poor cousin of marketing and pricing": qualitative study of stakeholders' views on policy priorities around tobacco and alcohol availability.Drugs (Abingdon, England) · 2025Article
- Scoping of Policy Impacts for Regulating E-cigarettes (SPIRE): findings from a data and decision analytic model mapping project.NIHR open research · 2025Article
- Corporate activities that influence population health: a scoping review and qualitative synthesis to develop the HEALTH-CORP typology.Globalization and health · 2024Article
- Prevention Lab: a predictive model for estimating the impact of prevention interventions in a simulated Italian cohort.BMC public health · 2024Article
- The long-term effectiveness and cost-effectiveness of public health interventions; how can we model behavior? A review.Health economics · 2023Review
- Conceptualising changes to tobacco and alcohol policy as affecting a single interlinked system.BMC public health · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundTo support a move towards a coordinated non-communicable disease approach in public health policy, it is important to conceptualise changes to policy on tobacco and alcohol as affecting a single interlinked system. For health economic models to effectively inform policy, the first step in their development should be to develop a conceptual understanding of the system complexity that is likely to affect the outcomes of policy change. Our aim in this study was to support the development and interpretation of health economic models of the effects of changes to tobacco and alcohol policies by developing a conceptual understanding of the main components and mechanisms in the system that links policy change to outcomes.
methodsOur study was based on a workshop from which we captured data on participant discussions on the joint tobacco-alcohol policy system. To inform these discussions, we prepared with a literature review and a survey of participants. Participants were academics and policy professionals who work in the United Kingdom. Data were analysed thematically to produce a description of the main components and mechanisms within the system.
resultsOf the people invited, 24 completed the survey (18 academic, 6 policy); 21 attended the workshop (16 academic, 5 policy). Our analysis identified eleven mechanisms through which individuals might modify the effects of a policy change, which include mechanisms that might lead to linked effects of policy change on tobacco and alcohol consumption. We identified ten mechanisms by which the tobacco and alcohol industries might modify the effects of policy changes, grouped into two categories: Reducing policy effectiveness; Enacting counter-measures. Finally, we identified eighteen research questions that indicate potential avenues for further work to understand the potential outcomes of policy change.
conclusionsModel development should carefully consider the ways in which individuals and the tobacco and alcohol industries might modify the effects of policy change, and the extent to which this results in an unequal societal distribution of outcomes. Modelled evidence should then be interpreted in the light of the conceptual understanding of the system that the modelling necessarily simplifies in order to predict the outcomes of policy change.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.