Evaluating the impact of minimum unit pricing for alcohol in Scotland: a theory-based synthesis of the evidence.

BACKGROUND: In May 2018, the Scottish Government set a minimum unit price (MUP) of £0·50 per unit of alcohol sold in Scotland to reduce alcohol-related health harms. We synthesised evidence to establish the effects of MUP on alcohol-related health and social harms, at population level and within specific societal groups. METHODS: We did a theory-based synthesis of academic and grey research evidence about impacts of MUP in Scotland, including compliance, price, consumption, health outcomes, social outcomes, public attitudes, and the alcoholic drinks industry. We searched the Public Health Scotland's MUP evaluation portfolio and relevant grey and academic literature for studies published between Jan 1, 2018, and Jan 31, 2023. We conducted systematic searches and screening of bibliographic databases (Scopus, Public Health Database, EconLit, MEDLINE, ProQuest Public Health, Social Policy and Practice, NHS Scotland Knowledge Network Library Search, medRxiv, bioRxiv, SSRN, Idox Knowledge Exchange, Social Policy & Practice, and Google Search). Search terms were tailored to specific databases but included variants of the terms "minimum unit pricing", "alcohol", and "policy". Eligibility literature included English-language research into impacts of MUP on either the population of Scotland or a specific subpopulation. We excluded conference abstracts, literature reviews, articles that did not report research, and research based solely on data from before the introduction of MUP. FINDINGS: We included 40 reports in our analysis. On the balance of evidence, MUP improved population-level health outcomes, demonstrated most starkly by a 13·4% reduction in alcohol-attributable deaths in Scotland compared with England. There was no evidence of substantial negative effects on the alcoholic drinks industry or social harms at the population level. While population-level outcomes were predominantly positive, some qualitative evidence suggests that MUP might have exacerbated health and social harms for some individuals or groups, especially those with alcohol dependence who were financially vulnerable. INTERPRETATION: MUP in Scotland has been effective in reducing alcohol-related health harms, with little evidence of any effect on social harms. If MUP continues, policymakers should consider raising the £0·50 per unit threshold and supplementing the intervention with policies or services to address any unintended negative effects experienced by specific groups. The synthesis is persuasive due to the prospective, theory-based design of the evaluation portfolio and the quality and comprehensiveness of the evidence. FUNDING: Scottish Government.

Evidence synthesis for constructing directed acyclic graphs (ESC-DAGs): a novel and systematic method for building directed acyclic graphs.

BACKGROUND: Directed acyclic graphs (DAGs) are popular tools for identifying appropriate adjustment strategies for epidemiological analysis. However, a lack of direction on how to build them is problematic. As a solution, we propose using a combination of evidence synthesis strategies and causal inference principles to integrate the DAG-building exercise within the review stages of research projects. We demonstrate this idea by introducing a novel protocol: 'Evidence Synthesis for Constructing Directed Acyclic Graphs' (ESC-DAGs)'. METHODS: ESC-DAGs operates on empirical studies identified by a literature search, ideally a novel systematic review or review of systematic reviews. It involves three key stages: (i) the conclusions of each study are 'mapped' into a DAG; (ii) the causal structures in these DAGs are systematically assessed using several causal inference principles and are corrected accordingly; (iii) the resulting DAGs are then synthesised into one or more 'integrated DAGs'. This demonstration article didactically applies ESC-DAGs to the literature on parental influences on offspring alcohol use during adolescence. CONCLUSIONS: ESC-DAGs is a practical, systematic and transparent approach for developing DAGs from background knowledge. These DAGs can then direct primary data analysis and DAG-based sensitivity analysis. ESC-DAGs has a modular design to allow researchers who are experienced DAG users to both use and improve upon the approach. It is also accessible to researchers with limited experience of DAGs or evidence synthesis.