SynthesisPublic health nutrition2026
Application of acceptability in dietary optimisation models: a systematic review.
Synthesis in Public health nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
objectiveDiet optimisation models have been developed to deal with the complexities of designing a sustainable diet. Diet acceptability is one aspect of a sustainable diet that has had limited integration into these models. This systematic review summarises and critically assesses the available literature regarding diet acceptability in optimisation studies.
designA systematic search on Medline and EMBASE was implemented, followed by a snowballing search until no new articles were found. Inclusion criteria were as follows: (1) diet optimisation studies; (2) acceptability included in model; (3) outcome diet referred to as 'acceptable'; (4) published between 2013-2025.
settingDiets.
participantsAdult population.
resultsA total of forty-nine studies were included in this review. Definitions of acceptability varied considerably. Analysis of the studies found six overarching themes were used to define acceptability in diets, with minimisation of deviation from observed diet and setting of lower and upper bounds on intake being most commonly used. Only 25 % of studies assessed the impact of acceptability models, objective functions and/or constraints, on the dietary output to some degree. Assessing three pathways (deduction, translation and induction) for defining and operationalising acceptability presents new opportunities to include citizens in the development of acceptable dietary models.
conclusionsIncluding acceptability into diet optimisation models is imperative as they can influence dietary structure, nutritional content, price and environmental impact, although they present certain trade-offs compared to other optimisation goals. Further work on real-world testing and contextualisation of these often-theoretical diets is needed, alongside testing and justification of the models' parameters for acceptability.
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