Developing a novel conceptual model of how UK food and drink tax policy impacts on consumption, health, environmental and economic outcomes.

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Penny Breeze, Amelia Lake, Helen Moore, Natalie Connor, Andrea Burrows, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5397071/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background Food taxes have been proposed to encourage people to choose healthier foods and reduce diet-related disease. Rising obesity in the UK has been explained through various causal mechanisms and systems. Economic evaluation of obesity interventions would benefit from a documented understanding of system complexity. We aimed to describe the parts of the system affected (components), the causal pathways through which the effects work (mechanisms), and the individual and system-level factors that impact on food tax impacts (context). Methods We developed the conceptual model through an iterative process to develop the diagrammatic representation of the conceptual model. We first undertook a synthesis of reviews of food taxes and a rapid review of economic evaluations of food and drink taxes. The research team synthesised these results to describe mechanisms and outcomes for inclusion in the conceptual model. Secondly, the conceptual model was validated and revised according to feedback from 14 stakeholders across academia, policy, and third sector organisations. Results Our final conceptual model illustrates system components which were grouped into eight sub-systems including policy infrastructure, industry behaviour, consumer behaviour, household expenditure, nutrition outcomes, health outcomes, environmental outcomes, and macroeconomic outcomes. Food taxes will influence consumption through price changes impacting purchases of taxed food and other purchases resulting in changes to consumption. Industry may modify the effects by absorbing the tax burden, marketing and product development and reformulation. We identify health, macroeconomic and environmental outcomes linked to food, and explore complex feedback loops linking health and macroeconomic performance to household finances further modifying food purchasing. We identify individual and contextual factors that modify these mechanisms. Conclusions When developing a health economic individual simulation model of the impact food taxes, researchers should consider the mechanisms by which individuals and industry can modify the effects of food taxes, and the extent to which these actions can be anticipated. System-wide factors can be documented so that the modelled evidence can be interpreted considering these factors even if they are not explicitly modelled. The conceptual model v3.0 remains dynamic and can be updated as evidence and perspectives on the food tax policy system develop over time. Fiscal policy Public health Simulation Complex systems Economic Nutrition Figures Figure 1 Figure 2 Background Dietary shifts towards food high in sugar, fats and/or salt and ultra-processed are contributing to non-communicable diseases and mortality (1). Less healthy foods have greater environmental impacts and are associated with unsustainable agricultural practices for the production of many foods (2). Socioeconomic factors also affect individual’s consumption of cheaper unhealthy foods because these foods are more affordable for families living on low incomes (3). For the purposes of this study, we refer to food and drink as any substance consumed to provide nutrition, hydration and energy to humans. Alcoholic beverages are excluded from this work because the motivations for people to drink alcohol are distinct from food choices (4, 5). In the United Kingdom (UK) most foods in retail settings do not incur value added taxes (VAT), whilst standard VAT is applied to some food groups and out of home venues. Since 2018 the Sugar Drinks Industry Levy (SDIL) has been applied to the production and import of soft drinks with more than 5g sugar per 100ml. Food taxes in the UK have been shown to improve dietary patterns by influencing consumer behaviour and encouraging healthier choices because price is a major driver of food choice (6, 7). Previous analysis has shown that a salt and sugar tax on foods with added sugar and salt will lead to price rises, but will make those foods more expensive relative to healthier options, which could reduce purchases of unhealthy foods (8). Taxes provide industry incentives for product reformulation of food products to improve the nutritional content of food as seen with the SDIL (9), and increases to government revenue, which can be allocated to other food policies such as free school meals. Public health interventions operate within a complex system, and it is therefore necessary to understand how public health policies impact all aspects of the system (10). It is not sufficient to consider only the expected effects on the parts of the system that are targeted by the policy. Policy evaluation should be embedded in a systems approach and aim to understand interactions with the environment and economy, which are important components of the food system (11). Understanding how the system might impact the policy’s effectiveness and potential wider outcomes of the policy are also important components of complex systems evaluations (12, 13). Food taxes are predominantly evaluated through empirical real-world evaluation (14, 15) or mathematical modelling (16, 17), both of which have been identified as suitable complex systems methodologies (18). However, it widely acknowledged that systems mapping process to describe how the policy interacts with the system to generate outcomes are an important initial step of complex systems methodologies (18–20). This paper is a sub-study of a project to identify food tax policies and quantitatively evaluate the outcomes of these policies by developing and adapting an existing model (HEALTHEI - NIHR133927) (21, 22). We aim to develop our quantitative modelling by following the Squires et al. framework for developing the structure of public health economic models (19). We took a systems approach to understand the relevant mechanisms that link a change in policy to its outcomes, and developed a visual representation of the system in consultation with academic experts and policy stakeholders. The specific objectives of this study were to undertake two evidence reviews to inform a conceptual diagram, run a series of workshops with academic experts and policy stakeholders, and finally to produce a consensus based a conceptual model. This model documents the components of the food tax system, the mechanisms within the system that link policy change to outcomes, and the contextual factors affecting those relationships. Methods An iterative process was taken to create the conceptual model following a published framework for developing economic models for public health (19). Figure 1 illustrates the stages of development and processes employed at each stage. In the first stage, version 1.0 of the conceptual model was prepared to consolidate existing knowledge and understanding of the food tax system. Existing logic models of food taxes were used to inform and structure version 1.0. Version 2.0 of the conceptual model was informed by the results of two evidence reviews as well as expert opinions of the research team and their understanding of the food tax system (researchers PB, KP, AL, HM, CR, CV, RW, AB). Version 1.0 and 2.0 of the conceptual model are provided in the supplementary material: Appendix A. Workshop discussion with stakeholders were used to extend and refine the conceptual model. Contributions from stakeholders were incorporated into version 3.0 of the conceptual model. 2.1 Evidence Reviews For stage one a synthesis of systematic reviews and discussion papers from international literature on food tax policy was conducted (Supplementary material: Appendix B) (23). This synthesis identified two useful diagrammatic representations/logic models of the food system (24, 25), which were used to structure version 1.0 of the conceptual model and inform data extraction for the review (24). This synthesis of systematic reviews aimed to identify a broad evidence base that could be used to describe and identify key characteristics relating to the food tax system. The data extraction process included collecting information across five themes informed by the logic models and team discussions. These themes include: (i) The mechanisms through which taxation translates to a change in consumption; (ii) The mechanisms linking food consumption to health; (iii) The mechanisms linking food consumption and health to non-health outcomes; (iv)The mechanisms linking household finances to the food system; (v) Contextual factors and individual characteristics. A second rapid review aimed was undertaken to identify the mechanisms and outcomes used in previous economic models for food taxes. The rapid review included studies from high- and middle-income countries which included simulation studies that evaluated food taxes. We extracted data on the components, mechanisms or contextual factors included in their analyses (see supplementary material Appendix C). 2.2 Workshops with stakeholders Stakeholders were invited to attend workshop and were asked to answer the following questions: (i) What components of the system are not represented in version 2.0 of the conceptual model? (ii) What mechanisms describing how the policy impacts the outcomes are not represented by the conceptual model? (iii) What demographic and social characteristics will affect the components and mechanisms of the model? We hosted three online workshops in January-March 2022, to offer participants a choice of workshops and increase attendance. Participants who attended one of these three workshop were invited to attend a final workshop in person in October 2022. Participants were purposely selected to cover a mix of backgrounds. Participants from local authorities, national government departments, non-governmental organisations, and academia with an interest in food policy and food systems were invited to attend. Invitations purposively targeted experts with a range of expertise including health, nutrition, economics, and environment. Of 33 invitations distributed a total of 14 participants were available and consented to attend the online workshops. Participants were from non-government organisations (NGOs) (n = 9), academia (n = 3), the Civil Service (n = 1) and a local authority (n = 1). Of these 14 participants, nine also attended the in-person workshop in October. The study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Teesside University Psychology Research Ethics Sub-Committee, and all participants provided consent to participate. Each participant was provided with a discussion document prior to the meeting. During the first three workshops version 2.0 of the conceptual model was displayed using interactive software to capture participants feedback and comments. The project lead (PB) presented the conceptual model, introducing the aims of the conceptual model, and provided details of how the conceptual model would be used to inform the later quantitative modelling work. Firstly, participants were asked to provide feedback on the conceptual model, through open discussion with other participants. Notes were taken to document these discussions. Secondly, all participants were asked to add comments to the online document. The conceptual model was grouped into sub-systems to aid presentation of the model and to allow participants to provide written comment at the sub-system level. The conceptual model was updated (by PB and KP) with feedback between the three online workshops to avoid duplication of comments. Finally, version 3.0 of the model was displayed in a poster on the wall at the third and final workshop. All participants were provided with post-it notes and encouraged to add written comments and feedback on a printed posted version the diagram. 2.3 Analysis The study collected data from the synthesis of systematic reviews, rapid review, notes taken in the workshops, and written comments provided by participants at the workshops. The conceptual model was developed with a cascading approach in which each stage of the research contributed to the evolving conceptual model, i.e. data from workshop 1 was used to update the diagram presented in workshop 2. We documented components, mechanisms and contextual factors in the system using a framework from Soft Systems Methodology (26) recommended by the Squires et al framework (19). In this approach the system is described as a set of interconnected components, and mechanisms as links between the components (26, 27). The data analysis was documented in a narrative analysis of the components, mechanisms and contextual factors in the system. The documentation informs a diagrammatic representation of the components and mechanisms to illustrate the conceptual model. The arrows linking components represent relationships between components such that a change in one component is expected to impact on a change in another. The direction of arrows illustrates the mechanisms through which the policy impacts the system. Results The synthesis of reviews identified 2,100 articles of which 32 eligible papers were identified. The rapid review of economic evaluations identified 2274 papers in the searches of which 21 met the inclusion criteria. A summary of each review and the findings are provided in supplementary material: Appendix B and C. Key feedback from stakeholders expanded the contextual factors for the individual and system-level. The mechanisms through which consumers and industry respond to taxes were expanded to include feedback loops through marketing strategies, and consumer tastes. In addition, stakeholders highlighted the importance of reflecting the costs of food taxes within the policy infrastructure sub-system, and increased the number of environmental and macroeconomic outcomes. Figure 2 illustrates the final conceptual model (version 3.0). 3.1 Conceptual model components Within the conceptual model components were grouped into 8 sub-systems defined by PB to aid interpretation. Policy infrastructure refers to the national and local government actions to introduce and maintain food taxes and related policies. Food system: Industry refers to the behaviours and supply decisions of producers and retailers of foods. Food system: Consumer behaviour , refers factors relating to the process of purchasing and consuming foods. Nutrition refers to the nourishment provided by the foods for health and growth. Health refers to the status of an individual including diagnosed and non-symptomatic factors that contribute to an individual’s health. Household outcomes , refers to the consequences for a group of individuals who live together in a single dwelling. Environment describes the effects or results of actions, policies, or processes on the natural environment. Macroeconomy refers to the overall functioning and performance of an economy at the national level. Interactions between sub-systems are highlighted to identify broad interdependencies between sub-systems. A description of each component is provided in the supplementary material: Appendix D. 3.2 Conceptual model mechanisms 3.2.1 Food mechanisms The impact of a tax on changes in consumption is dependent on tax pass-through . Tax pass through refers to the amount of a tax that is passed on to customers through a change in prices. Often it is assumed that 100% of a tax is passed onto customers, whereas lessons from historical data and other industries suggests that industry behaviour is more nuanced in their response (18, 25, 28, 29). Tax pass-through may vary across food types (28). Observations from the SDIL policy suggest that only 33% of taxes were passed on to customers (9). Price elasticity of demand measures consumers response after a change in a product's price (30–33). Economic theory would suggest an overall rule that consumers buy less of a product when prices increase, with some exceptions. Economic theory provides a theoretical framework to understand the mechanisms in which price influences demand and estimates of the response to price are informative to understand the potential effects of taxes (33). Consumers sensitivity to price varies across food products, individual characteristics and consumer preferences (30, 34). Empirical studies of the price elasticity of demand have been used extensively in the literature to estimate the impact of taxation on food purchases in modelling studies, and is supported by real world evaluations (25, 35, 36). Cross-price elasticity of demand measures the responsiveness of demand for other goods and services to a change in price of another product. Economic theory can be used to understand the responses (32). Products can be described as either substitutes or compliments. Substitute products will increase in demand due to an increase in price of another good, such as replacing an apple with a pear. In this instance, if the price of apples increases demand for pears increases. Complementary products will decrease in demand in response to an increase in price for another product. Complementary products are often consumed together, such as breakfast cereal and milk, such that a price rise for cereals will decrease demand for milk. Cross-price elasticity of demand is important because preferences for substitute foods will impact on nutritional intake (31, 37–39). Food taxes may lead to reformulation of food and product supply (18). Firstly, manufacturers may use product “shrinkflation” to avoid changes in price. Secondly, manufacturers may modify existing recipes to reduce a tax burden (37, 39). This pattern was observed in response to the UK SDIL policy, in which many drinks were reformulated to reduce sugar content (9). Thirdly, manufacturers may be incentivised to increase the supply of healthier products to avoid the tax and decrease the supply of products incurring a tax (40). Marketing and advertising are used by companies to promote food products to consumers, and influence consumer demand. Industries may use promotions and advertisements to offset loss of sales from price increases (18). The visibility and public awareness of a tax may modify consumer responses to advertising campaigns (37). 3.2.2 Health mechanisms The conceptual model includes relationships for excess calorie intake and nutritional intake supported by a strong evidence base as a precursor to weight gain, body mass index (BMI) and obesity (Supplementary material: Appendix C). Cardiometabolic risks are impacted by nutritional intake. Therefore, it is important to acknowledge the effects of dietary change beyond weight and obesity. There may complementary or competing mechanisms within the wider nutritional effects on cardiometabolic risks (28, 41). Changes to diet are complex and unhealthy foods are not necessarily substituted for healthy alternatives, for example chocolate substituted for crisps. Type 2 diabetes and cardiovascular diseases are strongly associated with BMI and cardiometabolic risks and were most commonly included as outcomes in the economic evaluations of food taxes (16, 17, 42–47) (see review of modelling studies in the supplementary material: Appendix C). The literature review identified that heart failure, osteoarthritis and cancers had also been linked to BMI in other economic evaluations. Dementia, non-alcoholic fatty liver disease , dental caries and depression were identified in only one review of food policy economic models (24). Quality adjusted life years, healthcare costs and mortality are impacted by the health outcomes listed above. Workshop stakeholders highlighted the importance of social care costs and informal care costs of many of these conditions, and the increased cost of social care in individuals with multi-morbidities. 3.2.3 Mechanisms to environmental and macroeconomic outcomes The conceptual model describes three main mechanisms in which macroeconomic outputs are impacted by food tax policy. Firstly, government revenues will be raised from food taxes (48). This revenue can be used to fund health programmes or complementary food subsidies (35, 49, 50). However, revenue may be volatile and estimates are usually imprecise (37). Secondly, food purchases contribute to Gross Domestic Product (GDP) (8). The overall impact on GDP depends on the extent that household spending shifts to other goods and services (50). Therefore, the industries contributing to food production and supply will be impacted by any changes in purchases through changes to sales revenue from increases/decreases in purchases (50). Thirdly, the health status of the population is associated with labour participation and productivity, both in employment (50) and informal caring responsibilities. There is a direct association between food production and environmental outcomes, such as greenhouse gases (43), water and land use (51). Food is a driver of greenhouse gases through respiration of plants and animals, deforestation, and requires a large amount of water and land in agricultural processes. In addition, stakeholders highlighted that food waste and plastic packaging are linked to food purchases (52, 53). These mechanisms vary between product types, with raw products using less plastic, but typically having shorter shelf-lives possibly leading to greater food waste (54). 3.2.4 Mechanisms between household and the food system The conceptual model identifies that household finances are impacted by changes to health and the macroeconomic environment. Health outcomes impact household finances where illnesses require individuals to take sick leave, reduce working hours or shift to lower paid jobs. Similarly, macroeconomic output will impact household finances through wages. Changes to household income may further impact food consumption. Substitution between food expenditure and non-food expenditure (45) may further impact the system by changes to environmental outcomes, macroeconomic outcomes, and industry behaviour (55). These mechanisms introduce feedback loops through which the policy may have additional effects as the behaviour of consumers and industry iterates through incremental changes and responses which slowly emerge over time (55). The feedback loops can reinforce health benefits, for example if a healthier population have higher incomes to spend on fruit and veg. However, these loops may mitigate benefits if reduced macroeconomic output from the food sector reduces household finances leading to shifts to cheaper processed foods. The overall consequence of feedback loops are difficult to predict and will be sensitive to other dynamic factors, such as the waiting times for healthcare and inflation (37). 3.4 Individual and system level contextual factors We identified contextual factors to acknowledge that the mechanisms within the system are not homogenous, and that responses will vary according to these factors and characteristics (56). The system-level factors mainly focussed on those which impact the implementation and sustainability of a food tax. We identified that taxes are more likely to be implemented with robust designs when accompanied by strong political leadership and positive support from public opinion and media (28, 37). Publicity prior to the tax is important particularly if this focusses on the promotion of healthy alternatives (56–58). Technical barriers to implementation can arise from legal challenges to government regulations , and conflicts with border controls and tariffs . Industry responses may depend on the industry types or size of business, and on their level of preparedness for the policy. Finally, food environment and food access differences will influence which populations can access to healthy alternatives and their flexibility to adapt to price changes. These impacts are likely to vary across local areas (urban/rural/coastal) , and cultural groups within the UK. Individual-level characteristics will influence the way that components are impacted by food taxes. Demographic factors such as age, sex (gender), household composition, and ethnicity are associated with patterns of food consumption, and health (34, 37, 59). Socioeconomic factors such as education and income provide individuals with differential resources to adapt and respond to a food tax (60). Discussion This novel study brings together a rich and emerging field of evidence to develop a conceptual model linking food tax policy to its outcomes with contributions and validation from an engaged group of expert stakeholders. This study attempted to take a broad overview of the food system, and identify the mechanisms through which food taxes impact individuals, households, healthcare, and the wider economic and environmental systems. This work also identifies the contextual features that interact with the mechanisms to modify the effects. The conceptual model does not aim to describe the quality of evidence for the mechanisms we have identified, but rather capture a comprehensive set of system components relevant to food taxes (19). Key mechanisms within the conceptual model such as behavioural responses to price changes, and the effects of calories on weight gain, have a strong theoretical and evidence base. These mechanisms have been used extensively in modelling studies to evaluate food taxes. Other mechanisms in the conceptual model, such as linking health to unpaid care outcomes or household income, have weaker foundation in the reviewed evidence, and some mechanisms describe hypothesised causal relationships. We identified feedback loops within the system through which initial changes to the system (i.e. increase in price reduces consumption of unhealthy foods) may lead to secondary effects through further modification to industry behaviour (advertising campaigns to increase consumer demand), government revenue (financing new fruit and veg subsidies) or consumer behaviour (increased household income from health improvement increases spending on fruit and vegetables). This study takes a complex systems approach to defining the conceptual model prior to economic model development. We have expanded on two existing logic models reporting the pathways through which food taxes would impact obesity (24, 25), and other health and non-health outcomes (24). In other disciplines systems mapping exercises have aimed to understand the complex system of food systems focussing on supply chains, retailers and industry (61–63). These systems maps highlight the range of pathways industry could adapt to policy change (61), and identify dynamic changes in food products responding to consumer demand for choice and drive to keep costs down (63). This is consistent with our conceptual model in which we have identified multiple mechanisms through which industry could enhance or mitigate the health benefits of a tax. This study advances existing literature by capturing the dynamic interplay of factors and identify key points of change in the system that can enhance or mitigate the policy effects. The conceptual model may provide insight into assessment of current barriers and enablers to change, actions that should be taken to overcome them, and possible consequences of doing so. In addition, the conceptual model developed in this study can be used by researchers as a guide to the development of evaluations to design health economic models, inform the selection of outcomes and potential confounders for real-world evaluations. The conceptual model can be used to identify the strengths and limitations of fiscal policy evaluations across empirical and modelling study designs, which will assist policymakers in critically analysing the evidence prior to policy introduction and also for policy evaluation. The conceptual model can be used as a tool to communicate the assumptions analysts make and highlight the wider context in which the analysis sits. This model might be particularly useful to explain findings that may be mitigated by unintended consequences and highlight areas for further data collection or research. Previous policy evaluation techniques often simplifying assumptions about the wider system either due to methodological or data limitations. The novel conceptual model could be used to communicate wider system effects to policymakers and other people affected by the food tax policy. The conceptual model may not include all components of the food tax system, and consultation with a range of different stakeholders may have resulted in a different focus or presentation of the conceptual model. Recruitment to the stakeholder workshops was challenging because many participants were not available to attend. Citizens and industry stakeholders were not invited to participate and their views may have raised other factors for inclusion in the model, particularly those related to social or psychological factors. The model is focused on the UK context and may not be generalisable to other international contexts. However, a published framework was adopted to develop this conceptual model, and international literature was used to inform the early version of the model. Due to these limitations, we would not characterise this conceptual model as a fixed output, but plan to use it as an evolving resource throughout the lifecycle of this project (NIHR133927) and beyond. The evidence base for fiscal food policies is rapidly emerging and the conceptual model needs to adapt to a dynamic social context to accommodate the ongoing effects of the cost-of living crisis and wider obesity policy. In conclusion, we demonstrate the mechanisms by which individuals and industries might modify the effects of food tax policy change, and the extent to which these responses results in health and wider societal impacts. Evidence for food taxes can be interpreted in the light of the conceptual understanding of the system to interpret results from observational studies and add depth to the interpretation of modelling studies. We will use this conceptual model to inform the assumptions and data inputs to an evaluation of food taxes in the UK, set the modelling boundary, and interpret the finding of our analyses. Declarations Ethical approval and consent to participate The study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects. Ethical approval for the stakeholder workshops was obtained from the School of Social Sciences, Humanities and Law Psychology Ethics Sub-Committee at Teesside University (Ref: 2022 Dec 11124 Moore; 2023 Jan 11124 Moore; 2023 May 11124 Moore). Written informed consent was obtained from all respondents. Consent for publication Not applicable. Competing Interests CV has a non-financial research collaboration with a UK supermarket chain. CV has no other conflicting interests to declare.CR has advisory positions on boards at the Nutrition Society (Food systems theme lead) and the Institute of Food Science & Technology (Sustainability working group). CR is part of the Sustainable Diet Working Group, Faculty of Public Health, and the British Standards Institution/ International Organization for Standardization committee ISO/TC 34/SC 20 (Food loss and waste). CR has received payment via City, University of London for consulting for: WRAP (a UK NGO); Zero Waste Scotland; DEFRA and the FSA (UK government). CR has been paid a Speaker's Stipend by the following events: The Folger Institute (2020). CR is a member of EGEA Scientific Committee and co-chair of a session of the EGEA conference (2023). This has meant his registration and flight/accommodation have been paid by Aprifel. CR has won competitive research funding (€49,858) from the following independent foundation: The Alpro Foundation, (2020). All other authors have no conflicts of interest to declare. Funding This study is funded by the NHIH Public health Research committee (NIHR133927) The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. Author Contribution PB was responsible for the conception of the project and led the development of the conceptual model. PB, AL, HJM, NC, ABur, formed the core group who conducted the rapid review of evidence and stakeholder workshop. KP, CR,RW and ABren contributed to the design of the study and provided comment throughout the development the conceptual model. All authors contributed to and approved the submitted version of the paper. Acknowledgement We thank the participants at the stakeholder workshops for their contribution to this work. Availability of data and materials All data generated or analysed during this study are included in this published article [and its References Afshin A, Sur PJ, Fay KA, Cornaby L, Ferrara G, Salama JS, et al. Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. The lancet. 2019;393(10184):1958-72. Springmann M, Clark MA, Rayner M, Scarborough P, Webb P. The global and regional costs of healthy and sustainable dietary patterns: a modelling study. 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Modelled health benefits of a sugar-sweetened beverage tax across different socioeconomic groups in Australia: A cost-effectiveness and equity analysis. PLoS medicine. 2017;14(6):e1002326. Sacks G, Veerman JL, Moodie M, Swinburn B. ‘Traffic-light’nutrition labelling and ‘junk-food’tax: a modelled comparison of cost-effectiveness for obesity prevention. International journal of obesity. 2011;35(7):1001-9. Smith-Spangler CM, Juusola JL, Enns EA, Owens DK, Garber AM. Population strategies to decrease sodium intake and the burden of cardiovascular disease: a cost-effectiveness analysis. Annals of internal medicine. 2010;152(8):481-7. Colchero MA, Paraje G, Popkin BM. The impacts on food purchases and tax revenues of a tax based on Chile’s nutrient profiling model. PLoS One. 2021;16(12):e0260693. Niebylski ML, Redburn KA, Duhaney T, Campbell NR. Healthy food subsidies and unhealthy food taxation: A systematic review of the evidence. Nutrition. 2015;31(6):787 − 95. Mounsey S, Veerman L, Jan S, Thow AM. The macroeconomic impacts of diet-related fiscal policy for NCD prevention: a systematic review. Economics & Human Biology. 2020;37:100854. Poore J, Nemecek T. Reducing food’s environmental impacts through producers and consumers. Science. 2018;360(6392):987 − 92. Williams H, Wikström F, Otterbring T, Löfgren M, Gustafsson A. Reasons for household food waste with special attention to packaging. Journal of cleaner production. 2012;24:141-8. Wohner B, Pauer E, Heinrich V, Tacker M. Packaging-related food losses and waste: an overview of drivers and issues. Sustainability. 2019;11(1):264. Raak N, Symmank C, Zahn S, Aschemann-Witzel J, Rohm H. Processing-and product-related causes for food waste and implications for the food supply chain. Waste management. 2017;61:461 − 72. Shemilt I, Marteau TM, Smith RD, Ogilvie D. Use and cumulation of evidence from modelling studies to inform policy on food taxes and subsidies: biting off more than we can chew? BMC Public Health. 2015;15:1–8. Afshin A, Penalvo JL, Del Gobbo L, Silva J, Michaelson M, O'Flaherty M, et al. The prospective impact of food pricing on improving dietary consumption: a systematic review and meta-analysis. PloS one. 2017;12(3):e0172277. Slapø H, Schjøll A, Strømgren B, Sandaker I, Lekhal S. Efficiency of in-store interventions to impact customers to purchase healthier food and beverage products in real-life grocery stores: a systematic review and meta-analysis. Foods. 2021;10(5):922. Hartmann-Boyce J, Bianchi F, Piernas C, Riches SP, Frie K, Nourse R, et al. Grocery store interventions to change food purchasing behaviors: a systematic review of randomized controlled trials. The American journal of clinical nutrition. 2018;107(6):1004-16. Adam A, Jensen JD. What is the effectiveness of obesity related interventions at retail grocery stores and supermarkets?—a systematic review. BMC public health. 2016;16:1–18. Backholer K, Sarink D, Beauchamp A, Keating C, Loh V, Ball K, et al. The impact of a tax on sugar-sweetened beverages according to socio-economic position: a systematic review of the evidence. Public health nutrition. 2016;19(17):3070-84. Bertscher A, Nobles J, Gilmore AB, Bondy K, Van Den Akker A, Dance S, et al. Building a systems map: applying systems thinking to unhealthy commodity industry influence on public health policy. International Journal of Health Policy and Management. 2024;13(1):1–17. Boelsen-Robinson T, Blake MR, Brown AD, Huse O, Palermo C, George NA, et al. Mapping factors associated with a successful shift towards healthier food retail in community-based organisations: a systems approach. Food Policy. 2021;101:102032. Kumar M, Srai J, Pattinson L, Gregory M. Mapping of the UK food supply chains: capturing trends and structural changes. Journal of Advances in Management Research. 2013;10(2):299–326. Additional Declarations Competing interest reported. CV has a non-financial research collaboration with a UK supermarket chain. CV has no other conflicting interests to declare. CR has advisory positions on boards at the Nutrition Society (Food systems theme lead) and the Institute of Food Science & Technology (Sustainability working group). CR is part of the Sustainable Diet Working Group, Faculty of Public Health, and the British Standards Institution/ International Organization for Standardization committee ISO/TC 34/SC 20 (Food loss and waste). CR has received payment via City, University of London for consulting for: WRAP (a UK NGO); Zero Waste Scotland; DEFRA and the FSA (UK government). CR has been paid a Speaker's Stipend by the following events: The Folger Institute (2020). CR is a member of EGEA Scientific Committee and co-chair of a session of the EGEA conference (2023). This has meant his registration and flight/accommodation have been paid by Aprifel. CR has won competitive research funding (€49,858) from the following independent foundation: The Alpro Foundation, (2020). All other authors have no conflicts of interest to declare. Supplementary Files Supplmentarymaterialv3.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 11 Nov, 2024 Editor assigned by journal 07 Nov, 2024 Submission checks completed at journal 07 Nov, 2024 First submitted to journal 05 Nov, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5397071","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":376576113,"identity":"509b5f58-0517-4c05-b4ce-a51c42b2d484","order_by":0,"name":"Penny 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16:38:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5397071/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5397071/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69826435,"identity":"f2ce789e-a88c-4594-9782-082e543336fa","added_by":"auto","created_at":"2024-11-25 15:02:24","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51658,"visible":true,"origin":"","legend":"\u003cp\u003eA flow diagram of methods used to iteratively develop the conceptual model\u003c/p\u003e","description":"","filename":"Figure1methods.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5397071/v1/4cc3da03292d2a3552aea13a.jpg"},{"id":69825978,"identity":"d9ee2a3b-5400-4a40-946b-975a94813ac3","added_by":"auto","created_at":"2024-11-25 14:54:24","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":234715,"visible":true,"origin":"","legend":"\u003cp\u003eA conceptual model illustrating the mechanisms that food taxes will impact the wider system\u003c/p\u003e","description":"","filename":"Figure2Foodtaxsystemfinalv3.0.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5397071/v1/4dd539f260e7e13d58c65956.jpg"},{"id":69826438,"identity":"ca976887-ebb4-4f5e-b82b-252a428f004c","added_by":"auto","created_at":"2024-11-25 15:02:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":890852,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5397071/v1/3d318493-9758-4cc8-aff3-20678fae2de3.pdf"},{"id":69826013,"identity":"05f15a2a-e71e-48d5-a4ee-4e923d53b4ab","added_by":"auto","created_at":"2024-11-25 14:54:26","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":480757,"visible":true,"origin":"","legend":"","description":"","filename":"Supplmentarymaterialv3.docx","url":"https://assets-eu.researchsquare.com/files/rs-5397071/v1/f841f1215d60ee2053cdefd2.docx"}],"financialInterests":"Competing interest reported. CV has a non-financial research collaboration with a UK supermarket chain. CV has no other conflicting interests to declare.\nCR has advisory positions on boards at the Nutrition Society (Food systems theme lead) and the Institute of Food Science \u0026 Technology (Sustainability working group). CR is part of the Sustainable Diet Working Group, Faculty of Public Health, and the British Standards Institution/ International Organization for Standardization committee ISO/TC 34/SC 20 (Food loss and waste). CR has received payment via City, University of London for consulting for: WRAP (a UK NGO); Zero Waste Scotland; DEFRA and the FSA (UK government). CR has been paid a Speaker's Stipend by the following events: The Folger Institute (2020). CR is a member of EGEA Scientific Committee and co-chair of a session of the EGEA conference (2023). This has meant his registration and flight/accommodation have been paid by Aprifel. CR has won competitive research funding (€49,858) from the following independent foundation: The Alpro Foundation, (2020). All other authors have no conflicts of interest to declare.","formattedTitle":"Developing a novel conceptual model of how UK food and drink tax policy impacts on consumption, health, environmental and economic outcomes.","fulltext":[{"header":"Background","content":"\u003cp\u003eDietary shifts towards food high in sugar, fats and/or salt and ultra-processed are contributing to non-communicable diseases and mortality (1). Less healthy foods have greater environmental impacts and are associated with unsustainable agricultural practices for the production of many foods (2). Socioeconomic factors also affect individual\u0026rsquo;s consumption of cheaper unhealthy foods because these foods are more affordable for families living on low incomes (3).\u003c/p\u003e \u003cp\u003eFor the purposes of this study, we refer to food and drink as any substance consumed to provide nutrition, hydration and energy to humans. Alcoholic beverages are excluded from this work because the motivations for people to drink alcohol are distinct from food choices (4, 5). In the United Kingdom (UK) most foods in retail settings do not incur value added taxes (VAT), whilst standard VAT is applied to some food groups and out of home venues. Since 2018 the Sugar Drinks Industry Levy (SDIL) has been applied to the production and import of soft drinks with more than 5g sugar per 100ml. Food taxes in the UK have been shown to improve dietary patterns by influencing consumer behaviour and encouraging healthier choices because price is a major driver of food choice (6, 7). Previous analysis has shown that a salt and sugar tax on foods with added sugar and salt will lead to price rises, but will make those foods more expensive relative to healthier options, which could reduce purchases of unhealthy foods (8). Taxes provide industry incentives for product reformulation of food products to improve the nutritional content of food as seen with the SDIL (9), and increases to government revenue, which can be allocated to other food policies such as free school meals.\u003c/p\u003e \u003cp\u003ePublic health interventions operate within a complex system, and it is therefore necessary to understand how public health policies impact all aspects of the system (10). It is not sufficient to consider only the expected effects on the parts of the system that are targeted by the policy. Policy evaluation should be embedded in a systems approach and aim to understand interactions with the environment and economy, which are important components of the food system (11). Understanding how the system might impact the policy\u0026rsquo;s effectiveness and potential wider outcomes of the policy are also important components of complex systems evaluations (12, 13). Food taxes are predominantly evaluated through empirical real-world evaluation (14, 15) or mathematical modelling (16, 17), both of which have been identified as suitable complex systems methodologies (18). However, it widely acknowledged that systems mapping process to describe how the policy interacts with the system to generate outcomes are an important initial step of complex systems methodologies (18\u0026ndash;20).\u003c/p\u003e \u003cp\u003eThis paper is a sub-study of a project to identify food tax policies and quantitatively evaluate the outcomes of these policies by developing and adapting an existing model (HEALTHEI - NIHR133927) (21, 22). We aim to develop our quantitative modelling by following the Squires et al. framework for developing the structure of public health economic models (19). We took a systems approach to understand the relevant mechanisms that link a change in policy to its outcomes, and developed a visual representation of the system in consultation with academic experts and policy stakeholders. The specific objectives of this study were to undertake two evidence reviews to inform a conceptual diagram, run a series of workshops with academic experts and policy stakeholders, and finally to produce a consensus based a conceptual model. This model documents the components of the food tax system, the mechanisms within the system that link policy change to outcomes, and the contextual factors affecting those relationships.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eAn iterative process was taken to create the conceptual model following a published framework for developing economic models for public health (19). Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the stages of development and processes employed at each stage. In the first stage, version 1.0 of the conceptual model was prepared to consolidate existing knowledge and understanding of the food tax system. Existing logic models of food taxes were used to inform and structure version 1.0. Version 2.0 of the conceptual model was informed by the results of two evidence reviews as well as expert opinions of the research team and their understanding of the food tax system (researchers PB, KP, AL, HM, CR, CV, RW, AB). Version 1.0 and 2.0 of the conceptual model are provided in the supplementary material: Appendix A. Workshop discussion with stakeholders were used to extend and refine the conceptual model. Contributions from stakeholders were incorporated into version 3.0 of the conceptual model.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e2.1 Evidence Reviews\u003c/p\u003e \u003cp\u003eFor stage one a synthesis of systematic reviews and discussion papers from international literature on food tax policy was conducted (Supplementary material: Appendix B) (23). This synthesis identified two useful diagrammatic representations/logic models of the food system (24, 25), which were used to structure version 1.0 of the conceptual model and inform data extraction for the review (24). This synthesis of systematic reviews aimed to identify a broad evidence base that could be used to describe and identify key characteristics relating to the food tax system. The data extraction process included collecting information across five themes informed by the logic models and team discussions. These themes include: (i) The mechanisms through which taxation translates to a change in consumption; (ii) The mechanisms linking food consumption to health; (iii) The mechanisms linking food consumption and health to non-health outcomes; (iv)The mechanisms linking household finances to the food system; (v) Contextual factors and individual characteristics.\u003c/p\u003e \u003cp\u003eA second rapid review aimed was undertaken to identify the mechanisms and outcomes used in previous economic models for food taxes. The rapid review included studies from high- and middle-income countries which included simulation studies that evaluated food taxes. We extracted data on the components, mechanisms or contextual factors included in their analyses (see supplementary material Appendix C).\u003c/p\u003e \u003cp\u003e2.2 Workshops with stakeholders\u003c/p\u003e \u003cp\u003eStakeholders were invited to attend workshop and were asked to answer the following questions: (i) What components of the system are not represented in version 2.0 of the conceptual model? (ii) What mechanisms describing how the policy impacts the outcomes are not represented by the conceptual model? (iii) What demographic and social characteristics will affect the components and mechanisms of the model?\u003c/p\u003e \u003cp\u003eWe hosted three online workshops in January-March 2022, to offer participants a choice of workshops and increase attendance. Participants who attended one of these three workshop were invited to attend a final workshop in person in October 2022. Participants were purposely selected to cover a mix of backgrounds. Participants from local authorities, national government departments, non-governmental organisations, and academia with an interest in food policy and food systems were invited to attend. Invitations purposively targeted experts with a range of expertise including health, nutrition, economics, and environment. Of 33 invitations distributed a total of 14 participants were available and consented to attend the online workshops. Participants were from non-government organisations (NGOs) (n\u0026thinsp;=\u0026thinsp;9), academia (n\u0026thinsp;=\u0026thinsp;3), the Civil Service (n\u0026thinsp;=\u0026thinsp;1) and a local authority (n\u0026thinsp;=\u0026thinsp;1). Of these 14 participants, nine also attended the in-person workshop in October. The study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Teesside University Psychology Research Ethics Sub-Committee, and all participants provided consent to participate.\u003c/p\u003e \u003cp\u003eEach participant was provided with a discussion document prior to the meeting. During the first three workshops version 2.0 of the conceptual model was displayed using interactive software to capture participants feedback and comments. The project lead (PB) presented the conceptual model, introducing the aims of the conceptual model, and provided details of how the conceptual model would be used to inform the later quantitative modelling work. Firstly, participants were asked to provide feedback on the conceptual model, through open discussion with other participants. Notes were taken to document these discussions. Secondly, all participants were asked to add comments to the online document. The conceptual model was grouped into sub-systems to aid presentation of the model and to allow participants to provide written comment at the sub-system level. The conceptual model was updated (by PB and KP) with feedback between the three online workshops to avoid duplication of comments. Finally, version 3.0 of the model was displayed in a poster on the wall at the third and final workshop. All participants were provided with post-it notes and encouraged to add written comments and feedback on a printed posted version the diagram.\u003c/p\u003e \u003cp\u003e2.3 Analysis\u003c/p\u003e \u003cp\u003eThe study collected data from the synthesis of systematic reviews, rapid review, notes taken in the workshops, and written comments provided by participants at the workshops. The conceptual model was developed with a cascading approach in which each stage of the research contributed to the evolving conceptual model, i.e. data from workshop 1 was used to update the diagram presented in workshop 2. We documented components, mechanisms and contextual factors in the system using a framework from Soft Systems Methodology (26) recommended by the Squires et al framework (19). In this approach the system is described as a set of interconnected components, and mechanisms as links between the components (26, 27). The data analysis was documented in a narrative analysis of the components, mechanisms and contextual factors in the system. The documentation informs a diagrammatic representation of the components and mechanisms to illustrate the conceptual model. The arrows linking components represent relationships between components such that a change in one component is expected to impact on a change in another. The direction of arrows illustrates the mechanisms through which the policy impacts the system.\u003c/p\u003e "},{"header":"Results","content":"\u003cp\u003eThe synthesis of reviews identified 2,100 articles of which 32 eligible papers were identified. The rapid review of economic evaluations identified 2274 papers in the searches of which 21 met the inclusion criteria. A summary of each review and the findings are provided in supplementary material: Appendix B and C. Key feedback from stakeholders expanded the contextual factors for the individual and system-level. The mechanisms through which consumers and industry respond to taxes were expanded to include feedback loops through marketing strategies, and consumer tastes. In addition, stakeholders highlighted the importance of reflecting the costs of food taxes within the policy infrastructure sub-system, and increased the number of environmental and macroeconomic outcomes. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the final conceptual model (version 3.0).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e3.1 Conceptual model components\u003c/p\u003e \u003cp\u003eWithin the conceptual model components were grouped into 8 sub-systems defined by PB to aid interpretation. \u003cem\u003ePolicy infrastructure\u003c/em\u003e refers to the national and local government actions to introduce and maintain food taxes and related policies. Food system: \u003cem\u003eIndustry\u003c/em\u003e refers to the behaviours and supply decisions of producers and retailers of foods. Food system: \u003cem\u003eConsumer behaviour\u003c/em\u003e, refers factors relating to the process of purchasing and consuming foods. \u003cem\u003eNutrition\u003c/em\u003e refers to the nourishment provided by the foods for health and growth. \u003cem\u003eHealth\u003c/em\u003e refers to the status of an individual including diagnosed and non-symptomatic factors that contribute to an individual\u0026rsquo;s health. \u003cem\u003eHousehold outcomes\u003c/em\u003e, refers to the consequences for a group of individuals who live together in a single dwelling. \u003cem\u003eEnvironment\u003c/em\u003e describes the effects or results of actions, policies, or processes on the natural environment. \u003cem\u003eMacroeconomy\u003c/em\u003e refers to the overall functioning and performance of an economy at the national level. Interactions between sub-systems are highlighted to identify broad interdependencies between sub-systems. A description of each component is provided in the supplementary material: Appendix D.\u003c/p\u003e\u003cp\u003e3.2 Conceptual model mechanisms\u003c/p\u003e \u003cp\u003e3.2.1 Food mechanisms\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe impact of a tax on changes in consumption is dependent on \u003cb\u003etax pass-through\u003c/b\u003e. Tax pass through refers to the amount of a tax that is passed on to customers through a change in prices. Often it is assumed that 100% of a tax is passed onto customers, whereas lessons from historical data and other industries suggests that industry behaviour is more nuanced in their response (18, 25, 28, 29). Tax pass-through may vary across food types (28). Observations from the SDIL policy suggest that only 33% of taxes were passed on to customers (9).\u003c/p\u003e \u003cp\u003e \u003cb\u003ePrice elasticity of demand\u003c/b\u003e measures consumers response after a change in a product's price (30\u0026ndash;33). Economic theory would suggest an overall rule that consumers buy less of a product when prices increase, with some exceptions. Economic theory provides a theoretical framework to understand the mechanisms in which price influences demand and estimates of the response to price are informative to understand the potential effects of taxes (33). Consumers sensitivity to price varies across food products, individual characteristics and consumer preferences (30, 34). Empirical studies of the price elasticity of demand have been used extensively in the literature to estimate the impact of taxation on food purchases in modelling studies, and is supported by real world evaluations (25, 35, 36).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCross-price elasticity of demand\u003c/b\u003e measures the responsiveness of demand for other goods and services to a change in price of another product. Economic theory can be used to understand the responses (32). Products can be described as either substitutes or compliments. Substitute products will increase in demand due to an increase in price of another good, such as replacing an apple with a pear. In this instance, if the price of apples increases demand for pears increases. Complementary products will decrease in demand in response to an increase in price for another product. Complementary products are often consumed together, such as breakfast cereal and milk, such that a price rise for cereals will decrease demand for milk. Cross-price elasticity of demand is important because preferences for substitute foods will impact on nutritional intake (31, 37\u0026ndash;39).\u003c/p\u003e \u003cp\u003eFood taxes may lead to \u003cb\u003ereformulation\u003c/b\u003e of food and product \u003cb\u003esupply\u003c/b\u003e (18). Firstly, manufacturers may use product \u0026ldquo;shrinkflation\u0026rdquo; to avoid changes in price. Secondly, manufacturers may modify existing recipes to reduce a tax burden (37, 39). This pattern was observed in response to the UK SDIL policy, in which many drinks were reformulated to reduce sugar content (9). Thirdly, manufacturers may be incentivised to increase the supply of healthier products to avoid the tax and decrease the supply of products incurring a tax (40).\u003c/p\u003e \u003cp\u003e \u003cb\u003eMarketing and advertising\u003c/b\u003e are used by companies to promote food products to consumers, and influence consumer demand. Industries may use promotions and advertisements to offset loss of sales from price increases (18). The visibility and public awareness of a tax may modify consumer responses to advertising campaigns (37).\u003c/p\u003e \u003cp\u003e3.2.2 Health mechanisms\u003c/p\u003e \u003cp\u003eThe conceptual model includes relationships for excess calorie intake and nutritional intake supported by a strong evidence base as a precursor to \u003cb\u003eweight gain, body mass index (BMI) and obesity\u003c/b\u003e (Supplementary material: Appendix C).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCardiometabolic risks\u003c/b\u003e are impacted by nutritional intake. Therefore, it is important to acknowledge the effects of dietary change beyond weight and obesity. There may complementary or competing mechanisms within the wider nutritional effects on cardiometabolic risks (28, 41). Changes to diet are complex and unhealthy foods are not necessarily substituted for healthy alternatives, for example chocolate substituted for crisps.\u003c/p\u003e \u003cp\u003e \u003cb\u003eType 2 diabetes\u003c/b\u003e and \u003cb\u003ecardiovascular diseases\u003c/b\u003e are strongly associated with BMI and cardiometabolic risks and were most commonly included as outcomes in the economic evaluations of food taxes (16, 17, 42\u0026ndash;47) (see review of modelling studies in the supplementary material: Appendix C). The literature review identified that \u003cb\u003eheart failure, osteoarthritis and cancers\u003c/b\u003e had also been linked to BMI in other economic evaluations. \u003cb\u003eDementia, non-alcoholic fatty liver disease\u003c/b\u003e, \u003cb\u003edental caries\u003c/b\u003e and \u003cb\u003edepression\u003c/b\u003e were identified in only one review of food policy economic models (24).\u003c/p\u003e \u003cp\u003e \u003cb\u003eQuality adjusted life years, healthcare costs\u003c/b\u003e and \u003cb\u003emortality\u003c/b\u003e are impacted by the health outcomes listed above. Workshop stakeholders highlighted the importance of \u003cb\u003esocial care costs\u003c/b\u003e and \u003cb\u003einformal care costs\u003c/b\u003e of many of these conditions, and the increased cost of social care in individuals with multi-morbidities.\u003c/p\u003e \u003cp\u003e3.2.3 Mechanisms to environmental and macroeconomic outcomes\u003c/p\u003e \u003cp\u003eThe conceptual model describes three main mechanisms in which macroeconomic outputs are impacted by food tax policy. Firstly, \u003cb\u003egovernment revenues\u003c/b\u003e will be raised from food taxes (48). This revenue can be used to fund health programmes or complementary food subsidies (35, 49, 50). However, revenue may be volatile and estimates are usually imprecise (37). Secondly, food purchases contribute to \u003cb\u003eGross Domestic Product (GDP)\u003c/b\u003e (8). The overall impact on GDP depends on the extent that household spending shifts to other goods and services (50). Therefore, the industries contributing to food production and supply will be impacted by any changes in purchases through changes to \u003cb\u003esales revenue\u003c/b\u003e from increases/decreases in purchases (50). Thirdly, the health status of the population is associated with labour participation and productivity, both in \u003cb\u003eemployment\u003c/b\u003e (50) and \u003cb\u003einformal caring\u003c/b\u003e responsibilities.\u003c/p\u003e \u003cp\u003eThere is a direct association between food production and environmental outcomes, such as \u003cb\u003egreenhouse gases\u003c/b\u003e (43), \u003cb\u003ewater\u003c/b\u003e and \u003cb\u003eland use\u003c/b\u003e (51). Food is a driver of greenhouse gases through respiration of plants and animals, deforestation, and requires a large amount of water and land in agricultural processes. In addition, stakeholders highlighted that \u003cb\u003efood waste\u003c/b\u003e and \u003cb\u003eplastic packaging\u003c/b\u003e are linked to food purchases (52, 53). These mechanisms vary between product types, with raw products using less plastic, but typically having shorter shelf-lives possibly leading to greater food waste (54).\u003c/p\u003e \u003cp\u003e3.2.4 Mechanisms between household and the food system\u003c/p\u003e \u003cp\u003eThe conceptual model identifies that household finances are impacted by changes to health and the macroeconomic environment. Health outcomes impact \u003cb\u003ehousehold finances\u003c/b\u003e where illnesses require individuals to take sick leave, reduce working hours or shift to lower paid jobs. Similarly, macroeconomic output will impact household finances through wages. Changes to \u003cb\u003ehousehold income\u003c/b\u003e may further impact food consumption. Substitution between \u003cb\u003efood expenditure\u003c/b\u003e and \u003cb\u003enon-food expenditure\u003c/b\u003e (45) may further impact the system by changes to environmental outcomes, macroeconomic outcomes, and industry behaviour (55). These mechanisms introduce feedback loops through which the policy may have additional effects as the behaviour of consumers and industry iterates through incremental changes and responses which slowly emerge over time (55). The feedback loops can reinforce health benefits, for example if a healthier population have higher incomes to spend on fruit and veg. However, these loops may mitigate benefits if reduced macroeconomic output from the food sector reduces household finances leading to shifts to cheaper processed foods. The overall consequence of feedback loops are difficult to predict and will be sensitive to other dynamic factors, such as the waiting times for healthcare and inflation (37).\u003c/p\u003e \u003cp\u003e3.4 Individual and system level contextual factors\u003c/p\u003e \u003cp\u003eWe identified contextual factors to acknowledge that the mechanisms within the system are not homogenous, and that responses will vary according to these factors and characteristics (56).\u003c/p\u003e \u003cp\u003eThe system-level factors mainly focussed on those which impact the implementation and sustainability of a food tax. We identified that taxes are more likely to be implemented with robust designs when accompanied by strong \u003cb\u003epolitical leadership\u003c/b\u003e and positive support from \u003cb\u003epublic opinion\u003c/b\u003e and \u003cb\u003emedia\u003c/b\u003e (28, 37). \u003cb\u003ePublicity\u003c/b\u003e prior to the tax is important particularly if this focusses on the promotion of healthy alternatives (56\u0026ndash;58). Technical barriers to implementation can arise from legal challenges to government \u003cb\u003eregulations\u003c/b\u003e, and conflicts with \u003cb\u003eborder controls and tariffs\u003c/b\u003e. Industry responses may depend on the \u003cb\u003eindustry types\u003c/b\u003e or size of business, and on their level of preparedness for the policy. Finally, \u003cb\u003efood environment\u003c/b\u003e and \u003cb\u003efood access\u003c/b\u003e differences will influence which populations can access to healthy alternatives and their flexibility to adapt to price changes. These impacts are likely to vary across \u003cb\u003elocal areas (urban/rural/coastal)\u003c/b\u003e, and \u003cb\u003ecultural groups\u003c/b\u003e within the UK.\u003c/p\u003e \u003cp\u003eIndividual-level characteristics will influence the way that components are impacted by food taxes. Demographic factors such as \u003cb\u003eage, sex (gender), household composition, and ethnicity\u003c/b\u003e are associated with patterns of food consumption, and health (34, 37, 59). Socioeconomic factors such as \u003cb\u003eeducation and income\u003c/b\u003e provide individuals with differential resources to adapt and respond to a food tax (60).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis novel study brings together a rich and emerging field of evidence to develop a conceptual model linking food tax policy to its outcomes with contributions and validation from an engaged group of expert stakeholders. This study attempted to take a broad overview of the food system, and identify the mechanisms through which food taxes impact individuals, households, healthcare, and the wider economic and environmental systems. This work also identifies the contextual features that interact with the mechanisms to modify the effects. The conceptual model does not aim to describe the quality of evidence for the mechanisms we have identified, but rather capture a comprehensive set of system components relevant to food taxes (19). Key mechanisms within the conceptual model such as behavioural responses to price changes, and the effects of calories on weight gain, have a strong theoretical and evidence base. These mechanisms have been used extensively in modelling studies to evaluate food taxes. Other mechanisms in the conceptual model, such as linking health to unpaid care outcomes or household income, have weaker foundation in the reviewed evidence, and some mechanisms describe hypothesised causal relationships. We identified feedback loops within the system through which initial changes to the system (i.e. increase in price reduces consumption of unhealthy foods) may lead to secondary effects through further modification to industry behaviour (advertising campaigns to increase consumer demand), government revenue (financing new fruit and veg subsidies) or consumer behaviour (increased household income from health improvement increases spending on fruit and vegetables).\u003c/p\u003e \u003cp\u003eThis study takes a complex systems approach to defining the conceptual model prior to economic model development. We have expanded on two existing logic models reporting the pathways through which food taxes would impact obesity (24, 25), and other health and non-health outcomes (24). In other disciplines systems mapping exercises have aimed to understand the complex system of food systems focussing on supply chains, retailers and industry (61\u0026ndash;63). These systems maps highlight the range of pathways industry could adapt to policy change (61), and identify dynamic changes in food products responding to consumer demand for choice and drive to keep costs down (63). This is consistent with our conceptual model in which we have identified multiple mechanisms through which industry could enhance or mitigate the health benefits of a tax.\u003c/p\u003e \u003cp\u003eThis study advances existing literature by capturing the dynamic interplay of factors and identify key points of change in the system that can enhance or mitigate the policy effects. The conceptual model may provide insight into assessment of current barriers and enablers to change, actions that should be taken to overcome them, and possible consequences of doing so. In addition, the conceptual model developed in this study can be used by researchers as a guide to the development of evaluations to design health economic models, inform the selection of outcomes and potential confounders for real-world evaluations. The conceptual model can be used to identify the strengths and limitations of fiscal policy evaluations across empirical and modelling study designs, which will assist policymakers in critically analysing the evidence prior to policy introduction and also for policy evaluation. The conceptual model can be used as a tool to communicate the assumptions analysts make and highlight the wider context in which the analysis sits. This model might be particularly useful to explain findings that may be mitigated by unintended consequences and highlight areas for further data collection or research. Previous policy evaluation techniques often simplifying assumptions about the wider system either due to methodological or data limitations. The novel conceptual model could be used to communicate wider system effects to policymakers and other people affected by the food tax policy.\u003c/p\u003e \u003cp\u003eThe conceptual model may not include all components of the food tax system, and consultation with a range of different stakeholders may have resulted in a different focus or presentation of the conceptual model. Recruitment to the stakeholder workshops was challenging because many participants were not available to attend. Citizens and industry stakeholders were not invited to participate and their views may have raised other factors for inclusion in the model, particularly those related to social or psychological factors. The model is focused on the UK context and may not be generalisable to other international contexts. However, a published framework was adopted to develop this conceptual model, and international literature was used to inform the early version of the model. Due to these limitations, we would not characterise this conceptual model as a fixed output, but plan to use it as an evolving resource throughout the lifecycle of this project (NIHR133927) and beyond. The evidence base for fiscal food policies is rapidly emerging and the conceptual model needs to adapt to a dynamic social context to accommodate the ongoing effects of the cost-of living crisis and wider obesity policy.\u003c/p\u003e \u003cp\u003eIn conclusion, we demonstrate the mechanisms by which individuals and industries might modify the effects of food tax policy change, and the extent to which these responses results in health and wider societal impacts. Evidence for food taxes can be interpreted in the light of the conceptual understanding of the system to interpret results from observational studies and add depth to the interpretation of modelling studies. We will use this conceptual model to inform the assumptions and data inputs to an evaluation of food taxes in the UK, set the modelling boundary, and interpret the finding of our analyses.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e \u003cp\u003eThe study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects. Ethical approval for the stakeholder workshops was obtained from the School of Social Sciences, Humanities and Law Psychology Ethics Sub-Committee at Teesside University (Ref: 2022 Dec 11124 Moore; 2023 Jan 11124 Moore; 2023 May 11124 Moore). Written informed consent was obtained from all respondents.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eCV has a non-financial research collaboration with a UK supermarket chain. CV has no other conflicting interests to declare.CR has advisory positions on boards at the Nutrition Society (Food systems theme lead) and the Institute of Food Science \u0026amp; Technology (Sustainability working group). CR is part of the Sustainable Diet Working Group, Faculty of Public Health, and the British Standards Institution/ International Organization for Standardization committee ISO/TC 34/SC 20 (Food loss and waste). CR has received payment via City, University of London for consulting for: WRAP (a UK NGO); Zero Waste Scotland; DEFRA and the FSA (UK government). CR has been paid a Speaker's Stipend by the following events: The Folger Institute (2020). CR is a member of EGEA Scientific Committee and co-chair of a session of the EGEA conference (2023). This has meant his registration and flight/accommodation have been paid by Aprifel. CR has won competitive research funding (\u0026euro;49,858) from the following independent foundation: The Alpro Foundation, (2020). All other authors have no conflicts of interest to declare.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003e This study is funded by the NHIH Public health Research committee (NIHR133927) The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003ePB was responsible for the conception of the project and led the development of the conceptual model. PB, AL, HJM, NC, ABur, formed the core group who conducted the rapid review of evidence and stakeholder workshop. KP, CR,RW and ABren contributed to the design of the study and provided comment throughout the development the conceptual model. All authors contributed to and approved the submitted version of the paper.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank the participants at the stakeholder workshops for their contribution to this work.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eAll data generated or analysed during this study are included in this published article [and its\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAfshin A, Sur PJ, Fay KA, Cornaby L, Ferrara G, Salama JS, et al. Health effects of dietary risks in 195 countries, 1990\u0026ndash;2017: a systematic analysis for the Global Burden of Disease Study 2017. 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Journal of Advances in Management Research. 2013;10(2):299\u0026ndash;326.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Fiscal policy Public health, Simulation, Complex systems, Economic, Nutrition","lastPublishedDoi":"10.21203/rs.3.rs-5397071/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5397071/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFood taxes have been proposed to encourage people to choose healthier foods and reduce diet-related disease. Rising obesity in the UK has been explained through various causal mechanisms and systems. Economic evaluation of obesity interventions would benefit from a documented understanding of system complexity. We aimed to describe the parts of the system affected (components), the causal pathways through which the effects work (mechanisms), and the individual and system-level factors that impact on food tax impacts (context).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe developed the conceptual model through an iterative process to develop the diagrammatic representation of the conceptual model. We first undertook a synthesis of reviews of food taxes and a rapid review of economic evaluations of food and drink taxes. The research team synthesised these results to describe mechanisms and outcomes for inclusion in the conceptual model. Secondly, the conceptual model was validated and revised according to feedback from 14 stakeholders across academia, policy, and third sector organisations.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOur final conceptual model illustrates system components which were grouped into eight sub-systems including policy infrastructure, industry behaviour, consumer behaviour, household expenditure, nutrition outcomes, health outcomes, environmental outcomes, and macroeconomic outcomes. Food taxes will influence consumption through price changes impacting purchases of taxed food and other purchases resulting in changes to consumption. Industry may modify the effects by absorbing the tax burden, marketing and product development and reformulation. We identify health, macroeconomic and environmental outcomes linked to food, and explore complex feedback loops linking health and macroeconomic performance to household finances further modifying food purchasing. We identify individual and contextual factors that modify these mechanisms.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWhen developing a health economic individual simulation model of the impact food taxes, researchers should consider the mechanisms by which individuals and industry can modify the effects of food taxes, and the extent to which these actions can be anticipated. System-wide factors can be documented so that the modelled evidence can be interpreted considering these factors even if they are not explicitly modelled. The conceptual model v3.0 remains dynamic and can be updated as evidence and perspectives on the food tax policy system develop over time.\u003c/p\u003e","manuscriptTitle":"Developing a novel conceptual model of how UK food and drink tax policy impacts on consumption, health, environmental and economic outcomes.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-25 14:54:12","doi":"10.21203/rs.3.rs-5397071/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-11T10:11:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-07T09:05:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-11-07T09:04:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2024-11-05T16:26:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0cf8854c-0359-49e2-b8f1-e2029f49e187","owner":[],"postedDate":"November 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-22T08:54:19+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-25 14:54:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5397071","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5397071","identity":"rs-5397071","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}