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Abstract
Background
Cardiometabolic diseases (CMDs), including cardiovascular disease (CVD) and type 2 diabetes (T2DM), are major contributors to morbidity, mortality, and rising healthcare costs. Effective disease prevention programs rely on robust mathematical models to generate long-term evidence regarding the effectiveness, cost-effectiveness, and policy implications of interventions in the population. Population-level interventions, such as dietary policies, are recognised as essential prevention strategies, yet there is limited syntheis of policy models assessing their impact. This study systematically reviews existing CMD policy models to provide: (i) a comprehensive overview of current models, and (ii) a critical appraisal of their application, particularly in the context of primordial prevention programmes.
Methods
A systematic search was conducted across MEDLINE (Ovid), EMBASE (Ovid), CINAHL, Google Scholar, and Open Grey. The search focused on publications from 1st January 2000, to 31st May 2024, using Medical Subject Headings (MeSH) for “cardiovascular,” “diabetes,” “decision model,” and “policy model.” Full-text articles were independently appraised independently by three reviewers using the Phillips et al. checklist, and the review process adhered to PRISMA guidelines.
Results
Thirty-two articles met the inclusion criteria and were critically appraised. Policy models were assessed across three domains: structure, data, and consistency. Most models (79%) demonstrated well-defined structures, aligning inputs and objectives with the stated perspective and initial justifications. However, fewer than 60% of studies clearly reported the quality of their data sources and provided clear information in terms of consistency. The reviewed studies employed diverse methodologies, including parameter incorporation, simulation modelling, and outcome analysis.
Conclusion
The review highlights substantial heterogeneity in the quality, structure, and data use of policy models evaluating dietary interventions for CMD prevention. To advance CMD policy modeling, this study provides recommendations for improving conceptualisation, methodological rigor, and applicability to prevention programmes.
Trial registration
Registered protocol at PROSPERO: CRD42022354399.
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