Hostname: page-component-77c89778f8-9q27g Total loading time: 0 Render date: 2024-07-18T15:20:20.527Z Has data issue: false hasContentIssue false

Beyond ultra-processed: considering the future role of food processing in human health

Published online by Cambridge University Press:  01 June 2023

Ciarán G. Forde*
Affiliation:
Sensory Science and Eating Behaviour, Division of Human Nutrition and Health, Wageningen University and Research, P.O. Box 17, 6700 AA Wageningen, The Netherlands
*
Corresponding author: Ciarán G. Forde, email Ciaran.forde@wur.nl
Rights & Permissions [Opens in a new window]

Abstract

Food-based dietary guidelines have been the basis of public health recommendations for over half a century, but more recently, there has been a trend to classify the health properties of food not by its nutrient composition, but by the degree to which it has been processed. This concept has been supported by many association studies, narrative reviews and the findings from one randomised controlled feeding trial, which demonstrated the sustained effect of ultra-processed diets on increasing both energy intake and body weight. This has led to widespread speculation as to specific features of ultra-processed foods that promote increased energy intakes. Rising interest in the ultra-processed topic has led to proposals to include guidance and restrictions on the consumption of processed foods in national dietary guidelines, with some countries encouraging consumers to avoid highly processed foods completely, and only choose minimally processed foods. However, there remains a lack of consensus on the role of processed foods in human health when faced with the challenges of securing the food supply for a growing global population, that is, healthy, affordable and sustainable. There has also been criticism of the subjective nature of definitions used to differentiate foods by their degree of processing, and there is currently a lack of empirical data to support a clear mechanism by which highly processed foods promote greater energy intakes. Recommendations to avoid all highly processed foods are potentially harmful if they remove affordable sources of nutrients and will be impractical for most when an estimated two-thirds of current energy purchased are from processed or ultra-processed foods. The current review highlights some considerations when interpreting the dietary association studies that link processed food intake to health and offers a critique on some of the mechanisms proposed to explain the link between ultra-processed food and poor health. Recent research suggests a combination of higher energy density and faster meal eating rates are likely to influence meal size and energy intakes from processed foods and offers new perspectives on how to manage this in the future. In going beyond the ultra-processed debate, the aim is to summarise some important considerations when interpreting existing data and identify the important gaps for future research on the role of processed food in health.

Type
Conference on ‘Food and nutrition: Pathways to a sustainable future’
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of The Nutrition Society

What are (ultra)processed foods?

There is widespread agreement that we need to change the way we produce the foods we consume, with rising levels of diet-related chronic disease matched by global concerns on the environmental impact of food production and distribution. Food-based dietary recommendations are supported by scientific evidence that underpins population guidance on healthy eating, with the goal of minimising diet-related chronic disease and enhancing nutritional well-being across the lifespan. These guidelines are informed by the highest quality scientific research from longitudinal observation studies and randomised controlled trials (RCT) within target and general populations. In recent years, dietary recommendation has moved away from nutrient-specific guidance (e.g. increase calcium and vitamin D for bone health), to emphasise the contribution of whole foods (i.e. milk) and food groups (i.e. dairy) in promoting nutrient adequacy. In 2009, a group in Brazil proposed the ‘NOVA’ approach to classify foods, not by their nutrient content, but by the degree to which they have been processed(Reference Monteiro, Cannon and Lawrence1). This approach proposes that it is not the nutrients in a food that predict its health properties, but the degree of processing that is most important for health. The NOVA approach advises the complete avoidance of highly processed foods to maximise health(Reference Lawrence2), and although quite subjective, the approach has a simplicity that is appealing when compared to more complex systems to code processed food or detailed dietary guidance based on nutrients or food groups.

There are currently at least six different systems that are used to classify foods by their degree of processing including the European Prospective Investigation into Cancer(Reference Slimani, Deharveng and Southgate3), the International Food Information Council(Reference Eicher-Miller, Fulgoni and Keast4), the Siga classification(Reference Davidou, Christodoulou and Fardet5), the University of North Carolina(Reference Bleiweiss-Sande, Chui and Evans6), NOVA and more recently the Food Compass system(Reference Mozaffarian, El-Abbadi and O'Hearn7). The NOVA system has evolved considerably since its initial introduction, initially focusing on number of ingredients and processes and more recently evolving to include the ‘purpose of processing’ as a central component of the definition(Reference Gibney8). There is little cohesion between these different systems of processing classification, and this becomes apparent when the same dietary data set is compared using different processing classification approaches, resulting in wide variation in the reported associations between processed food consumption and health. When data from the PREDIMED trial were classified using four of these different processing classifications (NOVA, the European Prospective Investigation into Cancer, the International Food Information Council, the University of North Carolina), the resulting associations with health varied considerably across systems, with most significant associations either attenuated or lost completely(Reference Martinez-Perez, San-Cristobal and Guallar-Castillon9). The NOVA scheme is the simplest and by far the most widely used approach to classify foods and diets by their degree of processing, but it's worth noting that there is a lack of consensus on its formulation and its application in dietary epidemiology(Reference Gibney, Forde and Mullally10Reference Monteiro and Astrup12). The aim of the current review is to provide a critique of available evidence and mechanisms and to highlight some important considerations for future research priorities on the topic of food processing and health.

The purpose of food processing and the objectivity of a definition

The NOVA system classifies foods based on (i) the extent and (ii) purpose of their processing into four categories from minimally processed (1), processed culinary ingredients (fats/oils, salt) (2), processed foods (3) and ultra-processed foods (UPF) (4)(Reference Monteiro, Cannon and Levy13). Minimally processed foods are the original whole food with no additives which undergo only mild or minimal processing and include fresh meats, fruits, vegetables and dairy. Processed culinary ingredients include salt, sugar and refined oils and other ingredients that are derived from the original whole food. When processed culinary ingredients are added to minimally processed foods, they join the processed food category, which also includes salting, canning, fermenting, freezing and prepared food that has undergone several processing steps. The UPF category is distinct from other processed foods and describes foods as ‘industrial formulations that are made entirely from food derivatives, chemical substances and sequence of processes, that bears little resemblance to the original food material(Reference Monteiro, Cannon and Levy13). In addition to degree of processing and formulation described earlier, the definition extends further to include the motivation behind specific formulations, such as ‘the use of additives whose function is to make the final product palatable and more appealing(Reference Monteiro, Cannon and Lawrence1). The NOVA system overlaps with many existing nutrient indices(Reference Drewnowski, Gupta and Darmon14), but is unique among classification approaches in that NOVA 4 (ultra-processed) category is the least discriminating, offering the broadest grouping of packaged foods available for consumption in the modern food environment. As such, when correlations are made with health markers or diet-related chronic disease, this category of foods is more likely to yield significant associations between processed food consumption and negative health outcomes. The popularity of the NOVA system has grown slowly since its inception, originally only used by small groups of researchers in specific regions(Reference Ivens15), but has since grown to become the most popular and widely used classification in the published literature and is increasingly referred to in FAO and WHO recommendations(Reference Monteiro, Cannon and Lawrence1).

This concept that the ‘purpose of food processing’ should be included as part of an objective definition of processed food is a unique element of the NOVA classification scheme, when compared to the other approaches. Here the NOVA definition goes beyond a product's composition or even degree of processing to include the motivation or reason behind the processing or formulation. These reasons have been listed in the definition as processing materials ‘to drive profitability, affordability, (hyper)palatability, convenience and ubiquity, where processed products are available everywhere, are affordable, and are widely marketed(Reference Scrinis and Monteiro16). The ultra-processed definition highlights further links with purpose, where ingredients that are added to ‘mimic the sensorial quality of unprocessed or minimally processed foods and their culinary preparations or to disguise undesirable qualities of the final product(Reference Scrinis and Monteiro16). Here the emphasis is not on the specific chemical or nutrient properties of the ingredient per se, but rather the intention behind its addition, suggesting the motivation for why a food is formulated this way is part of what qualifies it as (ultra)processed, and thus linked to a negative health impact. This is a clear departure from traditional nutrient-based dietary guidelines where the NOVA scheme describes ‘purpose’ of processing and formulation as part of the problem, and where product elements such as profitability, convenience, palatability or affordability are seen to play a role in the health or nutrient quality of the product(Reference Visioli, Marangoni and Fogliano17).

Food processing is a broad term that encompasses many different unit operations that are applied for a variety of different reasons, and although primarily used to increase the safety and digestibility of raw materials, they cannot all be described or defined as a single formulation or ‘process’(Reference Forde and Decker18). These approaches are applied to enhance sensory properties, ensure safety, extend shelf-life and improve nutrient (bio)availability among other reasons. Including ‘purpose of processing’ in the NOVA definition opens the classification to subjective interpretations of the intended purpose, increasing the risk of a biased interpretation and misclassification of processes and related health outcomes. This creates a separate, but related, debate on the potential to conflate the healthfulness of a food with an individual's own ideological bias against the modern food production system, or preconceptions towards the economic success of large food producers. Importantly, to date, there is no evidence that foods that are unprofitable, unpalatable, expensive or inconvenient to eat are necessarily better for your health. Moreover, producing foods that are unappealing and more expensive may reduce their intake in the short-term, but is unlikely to be a popular approach among consumers or food producers, and hardly seems a strong basis for public health strategies that aim to combat diet-related chronic disease(Reference Mela19). It is unlikely that company size, profitability or the ‘purpose’ of processing will inform dietary guidance in the future, and recommendations will continue to be firmly grounded in the evidence related to an objective appraisal of a foods nutritive value, and its potential to support healthy dietary patterns.

A critique of the observational evidence on the impact of processed food on health

Challenges with inferences made from observational studies using the NOVA classification

The NOVA classification has been widely applied to observational dietary epidemiological studies to establish links between the consumption of processed foods and a wide range of health outcomes. This includes cardio-metabolic disease, obesity and mortality (see(Reference Pagliai, Dinu and Madarena20) for a meta-analysis of observational studies). Insights from observational trials are limited by the nature of the dietary database, and the available details on food composition and processing steps for each item. It is widely recognised that observational comparisons cannot establish causality(Reference Brown, Aslibekyan and Bier21), but rather these approaches are often used to generate research hypotheses that should later be tested in randomised controlled diet trials. The exponential growth of publications linking processed food consumption to health research is based largely on repetitive observational studies that have shown similar associations between NOVA 4 UPF intake and health outcomes using dietary data sets from around the world(Reference Martini, Godos and Bonaccio22).

Within dietary association studies, it is important to control for known covariates that may bias a comparison or lead to an unfair attribution of influence to factors assumed to drive an observed association with health outcomes(Reference Brown, Aslibekyan and Bier21). Few studies to date have accounted for many of the known covariates that can influence the strength of relationships reported when comparing the processed food intake and health, with only a handful controlling for diet quality, energy density or other known lifestyle covariates. In addition to diet quality and energy density, other confounders with established links to obesity and poor health are often overlooked including physical (in)activity, smoking, alcohol consumption, stress, depression, poor sleep quality and duration, lower socio-economic status. When known dietary covariates are not controlled, it makes it unclear whether the impact of food processing has a distinct impact on health beyond established links between low diet quality and an increased risk of diet-related chronic disease. These findings are therefore susceptible to confounding where exposure to higher processed food intakes is associated with poor health outcomes without eliminating other known and measured factors(Reference Ioannidis23).

Recent studies have begun to adjust for diet quality (i.e. correcting for health eating index) in comparisons linking processed food intake to health outcomes and in some cases the link with processed food intake and chronic conditions is maintained(Reference Fiolet, Srour and Sellem24,Reference Du, Kim and Rebholz25) . However, other studies have demonstrated that the relationship between UPF intake and poor health is mediated by diet quality(Reference Griffin, Albaloul and Kopytek26), suggesting no additional unique contribution of processing on health when poor diet quality is controlled. Future research will be needed to establish the strength of the relationship between UPF intake and health when all known covariates have been accounted for in the analysis. There is now a need to supplement the outcomes of these observational data comparisons, with controlled feeding studies to establish whether the relationship between UPF consumption and health is independent of its relationship with poor diet quality.

Coder agreement on ultra-processed categorisation of dietary data sets

The NOVA definition of processing has continued to evolve since originally introduced to clarify what is regarded as ultra-processed, and many have been critical of the vague nature of the definitions which can be easily misinterpreted(Reference Gibney8,Reference Monteiro and Astrup12) . Currently, the NOVA definition includes elements of processing, formulation and processing ‘purpose’, and in recent years has further incorporated subjective terms such as ‘home-made’ or ‘natural’. Several studies have shown large discrepancies in agreement when foods are coded using different classification schemes. For example, when the 100 most commonly consumed foods were coded, there were large discrepancies between NOVA, the University of North Carolina and the International Food Information Council, and poor agreement on which classification system is best to identify foods with high nutrient quality(Reference Bleiweiss-Sande, Chui and Evans6). This creates issues when nutrition experts can easily misinterpret the same definitions and classify foods in different ways. Furthermore, the shifting nature of the UPF definition has led to confusion and ambiguity, which questions the stability and inter-rater reliability of the classifications used in the many observational epidemiological studies that seek to link UPF intake to health. A recent French study highlighted this and asked over 300 nutrition professionals to classify 231 different food items into their NOVA categories and found that 98 % of foods were placed in different processing categories by all assessors and there was agreement for only four of the 231 foods(Reference Braesco, Souchon and Sauvant27). Importantly, many of the foods that were classified as ultra-processed are defined as having an acceptable or high nutrient quality by conventional nutrient standards. Such a striking lack of consensus has been echoed by others(Reference Bleiweiss-Sande, Chui and Evans6,Reference Sadler, Grassby and Hart28) , and highlights how easily this seemingly simple classification scheme can be misinterpreted and could produce spurious associations, or create confusion among consumers when making dietary recommendations. In the rapidly expanding observational literature linking UPF consumption with health, few studies to date report either the process used or the level of agreement between coders when classifying foods into their respective processing classification level (i.e. inter-class correlations or other established measures of agreement between subjective attributions). The implication is that a researcher's own subjective interpretation of the NOVA classification or their beliefs about the healthfulness of processed food may shape their classification, and could potentially contribute to varied reported findings linked to health outcomes.

Future dietary associations between UPF intake and health should implement more rigorous approaches to measure inter-rater agreement by reporting the consistency of blinded processing classification attributions, using established metrics to demonstrate coder agreement. In addition, to further enhance the credibility of UPF designations and the self-report nature of the dietary intake measures, consumption patterns should be paired where possible with biomarkers of processed food intake. Emerging research has begun to propose novel bio-markers such as an industrial trans-fatty acid and the flavour marker 4-methyl syringol sulphate, a flavour marker of artificial ‘smoke’ flavour(Reference Huybrechts, Rauber and Nicolas29). These biomarkers of UPF consumption can be linked to diet records of foods deemed to be highly or ultra-processed to enhance the objectivity of comparisons in the future. Taken together, these measures will help improve approaches and enhance the credibility of dietary epidemiological studies reporting associations between food processing and health.

Contribution of specific food groups to the NOVA 4 (ultra-processed) category

Epidemiological research categorises foods and beverages into ‘food groups’ to move beyond single foods and nutrients and inform a better understanding of the specific dietary patterns that link to specific health outcomes. In this way, we can conclude that regular consumption of a given food group is associated with positive or negative health outcomes. For example, ‘dairy’ describes a wide range of products including different milks, butter, yogurts or cheeses and regular consumption of this broad ‘food group’ has been shown to be positively associated with improved bone-health and reduced risk of fracture(Reference Rizzoli30). By contrast, the NOVA 4 category (UPF) currently covers a broad spectrum of different foods united only by the definition of ‘foods of industrial creation’, as described previously. The broad nature of this definition means the NOVA 4 category covers approximately 60 % of energy sold in many developed countries, although this prevalence varies between countries(Reference Zhang, Jackson and Martinez31,Reference Zhang, Jackson and Steele32) . Importantly, unlike the example of dairy foods and bone health, where consumption of a single food group can be linked to specific health outcome, the diversity of the NOVA 4 category encompasses between ten and twelve different food groups, and includes everything from ambient dairy to extruded breakfast cereals and frozen meals(Reference Gibney33,Reference Pereira34) . Recent findings highlight the trouble with such a broad range of different food groups under the same ultra-processed umbrella. Across two studies from the Dutch Life-Lines cohort, UPF consumption was linked to all-cause mortality in a group of renal transplant patients(Reference Osté, Duan and Gomes-Neto35), and separately to the incidence of type-2 diabetes among Dutch adults(Reference Duan, Vinke and Navis36). Among renal transplant patients, the NOVA 4 category corresponded to ten distinct food groups. Closer inspection of the relationship of individual food groups revealed that only two of the ten groups remained positively associated with all-cause mortality and included sugar-sweetened beverages/desserts and processed meats(Reference Osté, Duan and Gomes-Neto35). The other food groups either had no clear association or were negatively associated with mortality (i.e. protective), including starchy foods, refined grains breakfast cereals, prepared meals, cookies, sources of fat, fried foods, salty snacks, toppings, liquors and candies. A separate comparison reported a positive association between consumption of NOVA 4 foods and increased risk of type-2 diabetes where comparison of the food's groups showed the risk was highest when the dietary pattern is defined by cold and warm savoury snacks. A pattern of NOVA 4 ‘sweet snacks and pastries’ was inversely associated with type-2 diabetes risk(Reference Duan, Vinke and Navis36). Grouping foods into the same category of NOVA 4 poses as risk when making dietary recommendations to public, as you may remove foods that are both a risk for and protective against the chronic disease outcome of interest.

The central issue is that the NOVA 4 classification assumes that most of the food processing is deleterious for health, whereas closer examination of the food groups reveals this is not the case. There is now a growing acceptance that the NOVA system is not fit for purpose if it is to be applied to guide public health strategies or provide population-level dietary guidance(Reference Tobias and Hall37). Many of the main recommendations overlap with conventional nutrient profiling approaches that offer a quantitative comparison of foods based on their nutrient and energy contents(Reference Drewnowski, Gupta and Darmon14,Reference Gupta, Hawk and Aggarwal38) . Defining UPF by the purpose, ‘number’ or ‘type’ of ingredient rather than nutrient content results in recommendations to remove or reduce many foods with an acceptable nutritional quality. Removing all UPF from the diet is likely to have a significant negative effect on population health, where alongside removing nutrient-poor/energy-dense foods, it would also result in the falling intakes of food groups that have adequate nutrition and may offer protective effects to the development of diet-related chronic disease. Uniformly, discouraging the avoidance of all processed food is impractical, unrealistic and this approach lacks the nuance needed to holistically evaluate the significant contribution made by many processed and packaged foods to daily dietary intakes(Reference Hallinan, Rose and Buszkiewicz39Reference Weaver, Dwyer and Fulgoni41).

The good, the bad and the reformulated: the future of smarter food processing

Product reformulation is a priority of food manufacturers globally, with a focus on reducing salt, sugar, fat and energy density across products alongside efforts to enhance or improve nutrient profiles. National campaigns to reduce salt and sugar had prompted an industry-wide surge in reformulation that has led to a reduction in nutrients of concern across a broad spectrum of product categories. Often, more processed versions of the same food ingredient can be nutritionally better than less processed or home-made versions of the same item. For example, thermal treatment of milk or juices under vacuum reduces temperature-related vitamin and nutrient losses and improves the nutrient composition of the finished processed food(Reference Bozkir and Tekgül42). Evidence from multiple meta-analyses of observational, animal trials and human RCT shows that switching from sugar-sweetened beverages to non-nutritively sweetened beverages can support both energy and BMI reductions, to an extent that is more effective than switching to water alone(Reference Rogers, Hogenkamp and de Graaf43). Previous research has highlighted the power of fortification and reformulation to significantly contribute to public health interventions aimed at increasing intakes, whether it be micronutrient fortified bouillon cubes(Reference Klassen-Wigger, Geraets, Messier, Venkatesh Mannar and Hurrell44) or enhanced whole grain intakes(Reference Lourenco, Hansen and Staerk45). In Denmark, the consumer trends towards low-carbohydrate diets led to population-wide reductions in whole grain intakes. To counteract this, a public–private partnership organised a fortification campaign that produced population-wide increases in intakes of whole-grain foods. Over a 10-year period, national whole-grain intakes doubled with increases of 43 % in children and 27 % in adults, through the whole-grain fortification of industrially processed breads and breakfast cereals(Reference Suthers, Broom and Beck46). This targeted reformulation of these ‘ultra-processed’ foods resulted in a significant rise in whole-grain consumption at a national level. Industry-wide efforts to reformulate have led to population-level reductions in the availability of salt (NaCl) and trans-fatty acids, with associated improvements in cardiovascular risk(Reference Gressier, Swinburn and Frost47). Although by no means perfect, reformulation policies have been shown to be effective in shifting the availability of public health-sensitive nutrients such as salt, added sugar and saturated fat and increasingly, incentives, regulations and clear implementation strategies have been shown to support an improvement in the overall nutritional quality across product categories(Reference Gressier, Sassi and Frost48,Reference Federici, Detzel and Petracca49) .

Most industrial processes are initially applied to improve the microbial stability and shelf-life of raw materials and enhance the nutrient content, palatability, digestibility and availability of nutrients in a way that often cannot be replicated in a domestic kitchen(Reference Forde and Decker18). For example, non-thermal preservation techniques such as food irradiation, high pressure processing, cold-plasma or pulsed electric field processing are used as ‘low-impact’ processes to extend shelf-life and improve nutrient availability in a way that does not result in undesirable processing by-products or thermal destruction of temperature-sensitive nutrients(Reference Knorr, Ade-Omowaye and Heinz50). Freeze drying removes water from raw materials through sublimation at low pressure, and has been shown to enhance rather than destroy nutrient quality and availability(Reference Monteiro Cordeiro de Azeredo and Monteiro Cordeiro de Azeredo51). To naive consumers, these processes may appear intimidating(Reference Meijer, Lähteenmäki and Stadler52,Reference Siegrist and Hartmann53) , although they have clear and significant benefits in terms of shelf-life extension, reducing food loss, while enhancing sustainability and nutrient density. An emerging suite of innovative ‘mild’ processes with equally intimidating names is being pioneered to reduce energy and resource costs, and promote more sustainable food processing(Reference van der Goot, Pelgrom and Berghout54). Techniques such as electro-static fractionation will result in less refined ingredients that utilise significantly less energy and can preserve innate matrix structures within raw materials while retaining nutrients. This shift towards milder processes is motivated by cost and environmental challenges rather than concerns surrounding the negative perception of ultra-processing on health yet highlights the potential benefits of smarter and more efficient processes in meeting growing food demand on a changing planet.

Reformulation and process innovation will remain a feature of global public health policy and a priority for food manufacturers that aim to produce healthy and sustainable products. Evidence from meta-analyses shows the efficacy of product reformulation, whether its switching to non-nutritively sweetened beverages to support reductions in energy intake and BMI(Reference Rogers, Hogenkamp and de Graaf43), or product reformulation to reduce daily energy consumed(Reference Robinson, Khuttan and McFarland-Lesser55). Despite the demonstrated efficacy of reformulation and fortification efforts to enhance public health, there remains resistance among some opponents of food processing that believe that any effort to reformulate the food supply can only make a food even more ultra-processed(Reference Scrinis and Monteiro56). Similarly efforts to support the protein transition from animal to plant-based sources of meat and dairy have been criticised as promoting a UPF environment(Reference Forde and Decker18). Irrespective of these concerns, reformulation remains a fact of life, and will continue to be central to efforts to improve the nutrient density and sustainability of food production and distribution(Reference Tobias and Hall37). Understanding the mechanism(s) by which processed foods may impact health positively or negatively is therefore central to future efforts if we are to set a target for what needs to change in the way food is formulated and processed. Some of the putative mechanisms are summarised later that have been proposed to date to explain the properties of processed foods most linked to negative health outcomes.

Proposed mechanisms for the link between food processing, energy intake and health

Processing and formulation make considerable changes to a raw materials' composition and structure, and this has led to widespread speculation on the potential mechanisms by which processed foods can promote higher energy intakes and poorer health(Reference Srour, Kordahi and Bonazzi57,Reference Juul, Vaidean and Parekh58) . There follows a summary of some of the putative mechanisms linking processing and health, and the available evidence to support them including the role of additives, hyper-palatability, satiety glycaemic response, energy density and energy intake rate.

A role for food additives in diet-related chronic disease

Food additives are substances added intentionally to foodstuffs to perform certain technological functions, for example, to colour, to sweeten or to help preserve foods. Today, there are over 300 food additives approved for use in the European Union that are identified by an ‘E-number’ that is always included in the ingredient lists of foods in which they are used(59,60) . The most common additives used are antioxidants (which are added to prevent deterioration caused by oxidation), colours, emulsifiers, stabilisers, gelling agents and thickeners, preservatives and sweeteners. Their addition enhances the microbial stability, shelf-life and organoleptic properties, and their use is strictly controlled by the European Food Safety Authority in the European Union, Food and Drug Administration and globally by regulatory bodies such as the Joint FAO/WHO Expert Committee on Food Additives. Since they are added to foods, new and existing additives undergo a rigorous approval process before they can enter the food supply(60) and their potential harmful effects are tracked over time and monitored once the additive is available.

Additives become more prevalent in foods as degree of processing increases and have been shown to be higher within the NOVA 4 UPF category(Reference Chazelas, Deschasaux and Srour61,Reference Chazelas, Druesne-Pecollo and Esseddik62) . Additives are always added to foods, so if they play a role in obesity-related diseases, there should be common biochemical pathways and mechanisms through which they can affect energy intake, either by promoting intake or dysregulation of appetite(Reference Gibney and Forde63). The use of food additives has been proposed as one of the potential mechanisms by which UPF consumption may promote metabolic dysfunction. A recent comparison of additive consumption within the Nutri-Net Sante cohort in France characterised the additive intakes in a large cohort of French consumers, and summarised these intakes by cluster from low to high intakes(Reference Chazelas, Druesne-Pecollo and Esseddik62). The authors proposed associations between additive intakes and the incidence of dietary chronic conditions such as obesity and type-2 diabetes. Importantly, when the reported levels of several additives were compared to those available and consumed in nature, the natural sources tended to be significantly higher in every case(Reference Gibney and Forde63).

How such a diverse set of chemical compounds could be associated with common biochemical pathways in the aetiology of such a wide range of conditions remain unclear. Whereas there is some evidence to show emulsifiers may have a negative effect on a subset of those suffering from irritable bowel syndrome and Crohn's disease(Reference Roberts, Rushworth and Richman64,Reference Bancil, Sandall and Rossi65) , these same sensitivities have not been observed in healthy populations. To date, there is no direct evidence of widespread effects of these food additives on the gut health of a healthy human population, although further research will continue to add to our understanding of this complex area(Reference Las Heras, Melgar and MacSharry66). Studies are now proposing links between the additive content of processed foods, intakes of emulsifiers and putative links with microbiome health(Reference Karl, Armstrong and Player67Reference Atzeni, Martínez and Babio69). Whereas it is important to inform these links with controlled hypothesis-driven research, there remains inconsistencies in the approaches used to compare the effect of specific food additives on microbiome composition, metabolites and health. There are also several obvious contradictions when linking the intake of specific food ‘additives’ to health via their impact on the microbiome. Take for example inulin, which is a soluble fibre that is frequently added to foods as a gelling agent, stabiliser and emulsifier in formulated packaged goods. Inulin is also promoted for its substantiated positive effect as an efficient pre-biotic with noted health benefits(Reference Ramnani, Gaudier and Bingham70,Reference Yoshinari, Bagchi and Ohia71) . Inulin consumption has been shown to promote microbial fermentation to produce SCFA, lower gut pH that helps to inhibit pathogens, promotes the proliferation of beneficial bacteria and stimulates the production of a wide range of beneficial metabolites that positively influence health(Reference Teferra72). Evidence therefore supports the use of additives like inulin as having demonstrable health benefits that outweigh any speculative negative health outcomes linked to the use of additive more broadly.

Added flavours are common in packaged consumer goods and have been proposed as a marker of ultra-processing(Reference Huybrechts, Rauber and Nicolas29), and this has led to speculation that the added flavours promote overeating by increasing the hedonic appeal or by disrupting normal flavour nutrient learning to promote weight gain(Reference Neumann and Fasshauer73). The suggestion is that sensory cues from highly processed foods no longer signal a foods' underlying nutrient content, such that synthetic and cosmetic flavours disrupt normal ‘taste–nutrient’ relationships and through this facilitate over-consumption. If this were true, then foods high in mono- and di-saccharides would not have a sweet taste intensity that reflects this concentration, or foods higher in NaCl would lack a salt taste intensity that matches their salt content, due to disruption of these taste–nutrient associations(Reference van Langeveld, Gibbons and Koelliker74). Data from a nationally representative survey of Singaporean diets were pooled to compare the perceived taste of a wide range of different foods to the content of the taste substrates (i.e. NaCl) across all levels of processing(Reference Teo, Tso and van Dam75). These results highlight that taste–nutrient relationships are maintained across all levels of food processing, including among foods classified as ultra-processed. Available data currently do not support claims made on the role of flavour additives in promoting food intake, although it remains important to question and monitor the safety of food additives and their potential impact on health. Ongoing research is further exploring the role of additives in promoting palatability and energy intake from processed foods (i.e. NCT05290064; NCT05550818).

Researching the specific impact of individual additives is extremely challenging due to the mixed nature of our diets, and the lack of quantitative information on additive intakes or exposure from either branded food databases or dietary records(Reference Gibney and Forde63). For example, it would be wrong to use inappropriate exposure assessments such as cross-sectional data and food frequency questionnaires to construct links between a foods' additive content and health. Using this as a basis for conclusions on the effect of additives on health or to support arguments to remove additives from the food supply is both inappropriate and unrealistic. If additive use is playing a role in promoting metabolic dysfunction, then research is needed to demonstrate this and regulations adjusted accordingly.

Hyper-palatability and energy absorption kinetics

Highly appealing foods may stimulate ‘non-homoeostatic’ eating where consumption is driven by pleasure rather than a homeostatic response to hunger(Reference Liu and Kanoski76). Pleasure-driven intake may promote positive energy balance(Reference Mela77), and could potentially be a driver of larger meal size and increased intake. Beyond simply eating more of a food you ‘like’, it has been proposed that UPF promote a ‘supra-normal’ hedonic response to specific flavour and macronutrient combinations that exploits our neurobiological drive to seek and consume rewarding foods. This response has been termed ‘hyper-palatability’(Reference Fazzino, Rohde and Sullivan78) and is defined using food compositional criteria rather than subjective hedonic responses. According to the proposed definition, foods become hyper-palatable when they diverge from naturally occurring nutrient combinations to have a higher proportion of energy from combinations of three nutrient pairs (fat and sugar, fat and sodium, carbohydrates and sodium) that exceed pre-defined levels. These nutrient combinations are believed to increase the drive to eat and lead to over-eating. One issue with the term hyper-palatability is that it does not reflect the human subjective hedonic response to oro-sensory properties of the food being consumed and cannot be universally inferred from food composition alone. We would also predict a heightened hedonic response to palatable foods from individuals that go on to develop obesity, yet obesity is not reliably associated with heightened hedonic responses to specific foods. People across all weight classes consume more energy from foods they like, and less energy from foods they don't like, and this phenomenon has been studied and understood for many years(Reference Yeomans, Tepper and Yeomans79Reference Yeomans81). There is also a circularity in the definition of hyper-palatability, since certain foods are classified as hyper-palatable because they lead to over-consumption, and to explain why these foods are over-eaten, the explanation offered is because of their ‘hyper-palatability’.

Given the subjectivity of food preferences, it seems implausible that a set of predefined cut-off points for fat, sugar, sodium and carbohydrate combinations could be applied to maximise palatability and consumption for whole populations. If food producers are aware of the specific nutrient combinations that heightened product acceptance, then clearly they choose to ignore them, as 90 % of new product launches continue to fail(Reference Köster, Mojet and MacFie82). Palatability, liking and consumer preferences are human subjective and emotional responses to the sensory and structural properties of foods as perceived during consumption, and it is not possible to predict this from compositional data in isolation(Reference Forde and de Graaf83). Similarly, as a concept it is conceivable to impose the definition on individual food items, but our food environment has a rich complexity of mixed meals and dishes, comprising individual items in different combinations that are more or less palatable, which does not easily lend itself to a summary description of palatability. There has yet to be formal study that clearly demonstrates an elevated hedonic response to these nutrient combinations that is above what is already known about the influence of food liking on intake(Reference Yeomans81). By contrast, the well-established phenomenon of sensory-specific satiety clearly demonstrates that the hedonic appeal of a food starts will decease rather than increase during consumption stimulating a desire for other foods and encouraging the consumption of a varied and balanced diet(Reference Rolls, Rolls and Rowe84).

It has recently been proposed that UPF delivers energy more rapidly which may enhance food reward and reinforce dietary learning in a way that is different to equivalent energy consumed from less processed foods(Reference Small and DiFeliceantonio85). The proposed mechanism is that energy is more readily available in UPF compared to minimally processed foods, and that this in turn enhances the speed of post-ingestive signals on the gut–brain axis, wherein this change in reward kinetics stimulates a higher food reward and stronger hedonic reinforcement(Reference Kelly, Baugh and Oster86). The premise is that the ready availability of energy in easily absorbable formats in processed foods could potentially influence the kinetics of energy uptake and stimulate stronger reward learning to further promote UPF consumption(Reference Kelly, Baugh and Oster86). This is currently speculation and further research will be needed to demonstrate whether these effects are observed in controlled human feeding trials. Reserach is currently underway to test the role of the ‘hyper-palatability’ hypothesis and to better understand the role in energy intake, reward and learning (i.e. NCT05200845 and NCT05550818). In the interim, it is important to remain cautious and continue to question claims made in relation to the role of hyper-palatability in promoting energy intake, particularly when well-established phenomena such as the role of liking and sensory specific in moderating meal size and energy intake are well-supported by published data.

Are (ultra)processed foods all low in satiety and high in glycaemic response?

Another proposed mechanism is that refined carbohydrates from highly processed products derived from maize, wheat and rice promote over-eating by contributing energy, while also stimulating insulin release that clears blood glucose to adipose stores and promotes an increased hunger(Reference Ludwig and Ebbeling87). This model of obesity and metabolic dysfunction has been hotly debated in recent years(Reference Hall, Farooqi and Friedman88). The premise is that if you reduce rapidly digestible carbohydrate, blood glucose levels will not spike to promote insulin release, fat storage and greater hunger/lower satiety. However, the links to ultra-processing and poor health are tenuous and based on a small set of selective comparisons. Preliminary comparison of published glycaemic and satiety values was used to propose that all processed foods have low satiety and a high glycaemic index(Reference Fardet89). Using previously published glycaemic and satiety databases, foods were categorised by their degree of processing and compared glycaemic response and satiety ratio, resulting in a descriptive comparison that has been used to substantiate claims that UPF promote insulin release and are less satiating than minimally processed foods(Reference Fardet89). However, a recent report has highlighted that UPF may in fact have a lower glycaemic index than comparable foods that are classified as minimally processed(Reference Basile, Ruiz-Tejada and Mohr90). Furthermore, there were no observed differences in post-meal satiety or later snack intake over 2 weeks in the only direct comparison of ultra- and minimally processed diets(Reference Hall, Ayuketah and Brychta91). Indeed, some foods classified as ultra-processed can have lower fibre and protein contents than minimally processed foods, which could influence gastric emptying rate and neuro-endocrine satiety signalling, but this would need to be tested and is not the case across all (ultra)processed foods. To test this requires further research where energy and macronutrient matched meals are compared directly within the same population for potential differences in post-meal satiety. The implication is that mechanisms linking degree of processing to energy intake or satiety should be formally tested under controlled conditions to ensure mechanistic claims are supported by the appropriate data. In the absence of direct evidence, caution should be exercised when claims are made on the many of the putative mechanisms and proposed solutions that are not currently supported by published data. Future research should now focus on formally testing the role of specific nutrient and behavioural features of processed foods that may drive greater energy intakes and health outcomes.

The role of energy density (kJ (kcal)/g)

Both higher energy density and larger portion sizes have been shown to promote greater energy intakes, and this has been consistently shown across studies in adults, children, across genders, across meal occasion, food forms, macronutrient sources and in both acute and long-term studies(Reference Ello-Martin, Ledikwe and Rolls92Reference Rolls95). In an RCT that compared ultra- and minimally processed diets, energy density was matched across diets at the level of the meal, although there were large differences in beverage and non-beverage energy density(Reference Ludwig, Astrup and Bazzano96). Participants were served an equivalent energy density on both the minimally and ultra-processed ad libitum diets (4⋅27 (1⋅02) v. 4⋅30 (1⋅03) kJ (kcal)/g) and were free to eat what they wanted from each meal, resulting in a higher energy density consumed on the ultra-processed diet (4⋅56 (1⋅09) v. 5⋅69 (1⋅36) kJ (kcal)/g). This may seem like a small difference, but a variation as low as 0⋅42 (0⋅1) kJ (kcal)/g has been shown to lead to increases of up to 418⋅4 (100) kJ (kcal) daily, suggesting that these differences were likely a significant contributor to the observed differences in daily energy intakes(Reference Rolls, Cunningham and Diktas97). Energy density can often be higher in specific food categories that are classified as UPF, such as deserts or confectionary, but estimates suggest these products do not dominate daily energy intakes (i.e. <5 % of daily energy). It is important to note that reformulated UPF are often less energy-dense than comparable unprocessed products, as highlighted earlier. A recent meta-analysis highlights that efforts to reduce energy density have been successful at reducing energy intake(Reference Robinson, Khuttan and McFarland-Lesser55), through the use of low and no-energy sweetened beverages or low-fat and low-sugar culinary ingredients.

It is difficult to establish a distinct role for food processing separate from the established impact of higher energy density in processed foods when these factors are not controlled for in observational comparisons. The single RCT to date to compare energy intake from ultra-processed and minimally processed diets had clear differences in non-beverage energy density served and consumed(Reference Hall, Ayuketah and Brychta91,Reference Rolls, Cunningham and Diktas97) . Reducing energy density in specific categories is a reformulation target for that has been used to inform public health policy in different countries(Reference Niblett, Coyle and Little98,Reference Martin and Vargas-Garcia99) . Global efforts to reduce dietary energy density will continue. In terms of processing, to establish a focal point for action, it is first necessary to prove a distinct mechanism for the impact of processing on health that adds further to current knowledge of known elements within our food environment that promote excessive energy intake.

The role of energy intake rate in energy consumption from ultra-processed foods

A meal eating rate is described in g/min and is believed to be the product of the textural challenge posed by the food being consumed and an individual's internal drive to eat(Reference Teo, Forde and Meiselman100). Extensive evidence from observational epidemiological studies consistently shows that self-reported eating rate is a predictor of higher energy intakes, body weight, adiposity and a wide range of cardio-metabolic risk factors(Reference Ohkuma, Hirakawa and Nakamura101Reference Forde, Stieger, Chen, Wolf and Bakalis105). This is further supported by findings from a series of controlled human feeding trials, where it has been shown that increasing the eating rate by approximately 20 % (g/min) results in a 12–15 % increase in ad libitum energy intake(Reference Forde106). Previous research on the textural properties of the food environment has shown that food form and texture can strongly influence the rate of consumption, with eating speeds for solid foods as low as 10–12 g/min, and for beverages up to 500–600 g/min(Reference Viskaal-van Dongen, Kok and de Graaf107Reference Wee, Goh and Stieger112). These differences in eating speed can significantly and consistently influence ad libitum energy intakes(Reference Teo, van Dam and Whitton104,Reference Forde, van Kuijk and Thaler110,Reference McCrickerd, Lim and Leong113Reference Teo, Lim and Goh115) . A simple example of this is the comparison of energy consumed from liquids v. solids, where it has been well established that high energy-dense liquids promote passive overconsumption compared to an equivalent energy load consumed as a semi-solid or solid(Reference de Graaf116Reference Mattes and Rothacker119). Meal eating rate is driven by its texture properties(Reference Bolhuis and Forde120) and may also interact with other known meal properties of meals that result in great intake, including portion size(Reference Cunningham, Roe and Keller121) and energy density(Reference McCrickerd, Lim and Leong113).

Higher energy density can interact with food form and texture to influence the rate and extent of energy intake within a meal(Reference Teo, Tso and van Dam75,Reference Teo, Lim and Goh115,Reference Forde, Mars and De Graaf122) . Higher energy density contributes to positive energy balance but makes a smaller contribution to the onset of satiation, meaning there is little adjustment within meal in response to consuming foods with a high energy density. In the one RCT that compared energy intake from ultra- v. minimally processed diets, participants consumed the ultra-processed meals up to 50 % faster (i.e. average energy intake rate 200⋅8 (48) v. 129.7 (31) kJ (kcal)/min), reflecting a combination of both softer textures and higher energy density among the foods in the ultra-processed diet. For certain UPFs, their textural properties may facilitate easier and more rapid consumption resulting in a faster eating rate(Reference Forde, Mars and De Graaf122), such that overconsumption may occur before gut–brain signals have time to communicate satiation(Reference Tobias and Hall37). Further research into the specific question of whether food texture or degree of processing moderates energy intake led to a comparison of ad libitum energy intakes from ultra- and minimally processed meals that differed in their texture and eating rate(Reference Teo, Lim and Goh115). In the harder-texture condition, eating rates were reduced across both processing levels which produced a 21 % reduction in amount (g) and 26 % reduction in energy consumed. Research is now needed to clarify the role of food texture in moderating energy intake from processed foods, and an RCT is now underway to test whether the observed effect of food texture on intake from (ultra)-processed foods is sustained over time (https://restructureproject.org/).

Meal texture is more influential in driving intake within a meal than the degree of processing, leading to suggestions that the issue of texture and eating rate should be central in the development of new strategies to moderate energy intakes from processed food environment(Reference Gibney123). In recent years, there has been a proliferation in research on how to apply food texture changes to moderate eating rate(Reference Bolhuis and Forde120,Reference Forde and Bolhuis124) and apply this to reduce meal size and moderate the metabolic response to food consumed(Reference Forde, Stieger, Chen, Wolf and Bakalis105,Reference Choy, Goh and Chatonidi125Reference Chen, Stieger and Capuano128) . Future research should consider food texture-based strategies and manipulations to support consumers to reduce their eating speed and meal size. To achieve this, we will need further mechanistic studies to establish how these nutritive and behavioural properties differ across processed foods to better understand their contribution to higher intakes, and test whether changing these properties can help mitigate the risk of overconsumption.

Conclusions: moving ‘beyond ultra-processed’ food

The world now faces the triple threat of growing rates of diet-related chronic disease, rising food insecurity and growing concerns on the environmental impact of unsustainable food production practices. Processed and packaged food products are widely consumed and will continue to be a central component of the modern food supply and our diets in the future. The challenge now is to identify actionable ways to improve how our food is produced to reduce its impact on the environmemt, and ensure the nutritive properties of these foods meet the needs of a growing global population. The modern food system offers the necessary economies of scale and distribution channels needed to alleviate the risk of food insecurity for millions around the world. If food processing is to be considered an important element in supporting consumers to make healthier food choices, there needs to be a scientific consensus on the positive and negative contributions made by the variety of food processing techniques that includes an appraisal of its health and nutrient properties, environmental impact and the associated affordability considerations of dietary changes. Food processing utilises many different approaches that serve different functions, and it is inappropriate to define single unit processing operations as either ‘healthy’ or ‘unhealthy’, as all food production requires materials to undergo multiple diverse processing steps(Reference Forde and Decker18). Because of this complexity, it is also not appropriate to summarise such a wide category as NOVA 4 as unhealthy, or to use the term ‘processing’ as a proxy index for the health effect a food. The breadth of the foods covered by the ultra-processed NOVA 4 category makes it difficult to implement clear and actionable nutrition guidelines that can inform healthier consumer choices, and risk removing nutritional adequate foods from the diet. Future approaches to define dietary strategies will also need to move beyond simply describing the degree of processing to cover the additional aspects such as the planetary impact of food production and consumption, nutritional properties of food and factors related to consumers’ equitable access to a safe and affordable food supply. In this regard, the recently proposed sustainable-nutritious packaged foods(Reference Gustafson, Decker and Drewnowski129) approach to describing sustainability, equity and nutrient density seems more objective and balanced than the simplified 1–4 scores of NOVA.

The benefit of food processing is that it makes food affordable, accessible and appealing, and yet these are now the same features that have raised concerns about how highly processed foods can promote excess intake. Consumers should be encouraged to limit consumption of several food groups, based on their composition rather than degree of processing. Few would support a public health policy aimed at producing foods that are both less appealing and more expensive(Reference Mela19), yet increasingly there are calls for additional taxes on UPF and tighter regulation and restrictions on the production and distribution of processed food. A sole focus on limiting people's access to processed foods may give rise to inappropriate solutions, and lead to the imposition of regressive taxes that will disproportionately affect the most vulnerable in society. Nutrition policies need to consider the context of consumption and the economic realities that many encounter when trying to adhere to diets that promote long-term impact on health and wellbeing. Food processing has granted access to safe, nutritious and appealing foods to millions of consumers globally, and setting nutritional guidelines that restrict access to the majority of foods purchased and consumed is both unrealistic and underestimates consumers ability to make informed decisions about the foods they purchase and consume. Understanding the properties of specific highly processed foods that promote higher consumption is now a research priority and will create new opportunities to go beyond traditional reformulation strategies to consider how sensory cues like food texture can directly influence the rate and extent of energy intake.

Financial Support

The paper summarises an invited talk at the 2022 UK Nutrition Society meeting. The author has received funding support from the Dutch Top-Consortium for Knowledge and Innovation Agri & Food (TKI-Agri-food) Project Restructure (TKI 22⋅150).

Conflict of Interest

The author declares no conflicts of interest in relation to the current manuscript. C. G. F. is a member of the Global Scientific Advisory Committee Kerry Health and Nutrition Institute. The author has received travel expenses for speaking about processed foods at scientific meetings from the Institute Food Technology (IFT), USDA, Nutrition Society (UK), European Federation of Food Science & Technology (EFFoST), World Sugar Research Organisation (WSRO), GB Foods, Northern Irish Dairy Council, Institute for the Advancement of Food and Nutrition Science (IAFNS) and the Federation for European Nutrition Societies (FENS).

Authorship

The author is solely responsible for the content of the current manuscript.

References

Monteiro, CA, Cannon, G, Lawrence, M et al. (2019) Ultra-processed foods, diet quality, and health using the NOVA classification system. Rome: FAO 48.Google Scholar
Lawrence, M (2022) Ultra-processed foods: a fit-for-purpose concept for nutrition policy activities to tackle unhealthy and unsustainable diets. Public Health Nutr 129, 21952198.Google ScholarPubMed
Slimani, N, Deharveng, G, Southgate, DAT et al. (2009) Contribution of highly industrially processed foods to the nutrient intakes and patterns of middle-aged populations in the European prospective investigation into cancer and nutrition study. Eur J Clin Nutr 63, S206S225.CrossRefGoogle Scholar
Eicher-Miller, HA, Fulgoni, VL III & Keast, DR (2012) Contributions of processed foods to dietary intake in the US from 2003–2008: a report of the Food and Nutrition Science Solutions Joint Task Force of the Academy of Nutrition and Dietetics, American Society for Nutrition, Institute of Food Technologists, and International Food Information Council. J Nutr 142, 2065S2072S.CrossRefGoogle Scholar
Davidou, S, Christodoulou, A, Fardet, A et al. (2020) The holistico-reductionist Siga classification according to the degree of food processing: an evaluation of ultra-processed foods in French supermarkets. Food Funct 11, 20262039.CrossRefGoogle Scholar
Bleiweiss-Sande, R, Chui, K, Evans, EW et al. (2019) Robustness of food processing classification systems. Nutrients 11, 1344.CrossRefGoogle ScholarPubMed
Mozaffarian, D, El-Abbadi, NH, O'Hearn, M et al. (2021) Food Compass is a nutrient profiling system using expanded characteristics for assessing healthfulness of foods. Nat Food 2, 809818.CrossRefGoogle ScholarPubMed
Gibney, MJ (2019) Ultra-processed foods: definitions and policy issues. Curr Dev Nutr 3, nzy077.CrossRefGoogle ScholarPubMed
Martinez-Perez, C, San-Cristobal, R, Guallar-Castillon, P et al. (2021) Use of different food classification systems to assess the association between ultra-processed food consumption and cardiometabolic health in an elderly population with metabolic syndrome (PREDIMED-Plus Cohort). Nutrients 13, 2471.CrossRefGoogle Scholar
Gibney, MJ, Forde, CG, Mullally, D et al. (2017) Ultra-processed foods in human health: a critical appraisal. Am J Clin Nutr 106, 717724.CrossRefGoogle ScholarPubMed
Astrup, A, Magkos, F, Bier, D et al. (2020) Saturated fats and health: a reassessment and proposal for food-based recommendations: JACC state-of-the-art review. J Am Coll Cardiol 76, 844857.CrossRefGoogle Scholar
Monteiro, CA & Astrup, A (2022) Does the concept of ‘ultra-processed foods’ help inform dietary guidelines, beyond conventional classification systems? Yes. Am J Clin Nutr 116, 14761481.CrossRefGoogle ScholarPubMed
Monteiro, CA, Cannon, G, Levy, RB et al. (2019) Ultra-processed foods: what they are and how to identify them. Public Health Nutr 22, 936941.CrossRefGoogle Scholar
Drewnowski, A, Gupta, S & Darmon, N (2020) An overlap between ‘ultraprocessed’ foods and the preexisting nutrient rich foods index? Nutr Today 55, 7581.CrossRefGoogle Scholar
Ivens, BJ (2020) The emergence of the term ‘ultraprocessed’ foods in nutrition research. Nutr Today 55, 1115.CrossRefGoogle Scholar
Scrinis, G & Monteiro, C (2022) From ultra-processed foods to ultra-processed dietary patterns. Nat Food 3, 671673.CrossRefGoogle ScholarPubMed
Visioli, F, Marangoni, F, Fogliano, V et al. (2022) The ultra-processed foods hypothesis: a product processed well beyond the basic ingredients in the package. Nutr Res Rev, 111.CrossRefGoogle ScholarPubMed
Forde, CG & Decker, EA (2022) The importance of food processing and eating behavior in promoting healthy and sustainable diets. Annu Rev Nutr 42, 377399.CrossRefGoogle ScholarPubMed
Mela, DJ (2022) Is there an academic bias against low-energy sweeteners? Nutrients 14, 1428.CrossRefGoogle ScholarPubMed
Pagliai, G, Dinu, M, Madarena, MP et al. (2021) Consumption of ultra-processed foods and health status: a systematic review and meta-analysis. Br J Nutr 125, 308318.CrossRefGoogle ScholarPubMed
Brown, AW, Aslibekyan, S, Bier, D et al. (2021) Toward more rigorous and informative nutritional epidemiology: the rational space between dismissal and defense of the status quo. Crit Rev Food Sci Nutr, 118.Google ScholarPubMed
Martini, D, Godos, J, Bonaccio, M et al. (2021) Ultra-processed foods and nutritional dietary profile: a meta-analysis of nationally representative samples. Nutrients 13, 3390.CrossRefGoogle ScholarPubMed
Ioannidis, JP (2016) Biases in obesity research: identify, correct, endorse, or abandon effort? Obesity 24, 767.CrossRefGoogle ScholarPubMed
Fiolet, T, Srour, B, Sellem, L et al. (2018) Consumption of ultra-processed foods and cancer risk: results from NutriNet-Santé prospective cohort. Br Med J 360.Google ScholarPubMed
Du, S, Kim, H & Rebholz, CM (2021) Higher ultra-processed food consumption is associated with increased risk of incident coronary artery disease in the atherosclerosis risk in communities study. J Nutr 151, 37463754.CrossRefGoogle ScholarPubMed
Griffin, J, Albaloul, A, Kopytek, A et al. (2021) Effect of ultraprocessed food intake on cardiometabolic risk is mediated by diet quality: a cross-sectional study. BMJ Nutr Prev Health 4, 174.CrossRefGoogle ScholarPubMed
Braesco, V, Souchon, I, Sauvant, P et al. (2022) Ultra-processed foods: how functional is the NOVA system? Eur J Clin Nutr 76, 12451253.CrossRefGoogle ScholarPubMed
Sadler, CR, Grassby, T, Hart, K et al. (2022) ‘Even we are confused’: a thematic analysis of professionals’ perceptions of processed foods and challenges for communication. Front Nutr 9, 826162.CrossRefGoogle ScholarPubMed
Huybrechts, I, Rauber, F, Nicolas, G et al. (2022) Characterization of the degree of food processing in the European prospective investigation into cancer and nutrition: application of the Nova classification and validation using selected biomarkers of food processing. Front Nutr 9, doi: 10.3389/fnut.2022.1035580CrossRefGoogle ScholarPubMed
Rizzoli, R (2014) Dairy products, yogurts, and bone health. Am J Clin Nutr 99, 1256S1262S.CrossRefGoogle ScholarPubMed
Zhang, Z, Jackson, SL, Martinez, E et al. (2021) Association between ultraprocessed food intake and cardiovascular health in US adults: a cross-sectional analysis of the NHANES 2011–2016. Am J Clin Nutr 113, 428436.CrossRefGoogle ScholarPubMed
Zhang, Z, Jackson, SL, Steele, EM et al. (2022) Relationship between ultraprocessed food intake and cardiovascular health among US adolescents: results from the national health and nutrition examination survey 2007–2018. J Adolesc Health 70, 249257.CrossRefGoogle ScholarPubMed
Gibney, MJ (2022) Ultra-processed foods in public health nutrition: the unanswered questions. Br J Nutr 129, 21912194.CrossRefGoogle ScholarPubMed
Pereira, MA (2022) Food processing in nutritional epidemiology: proceed with caution. Am J Clin Nutr 115, 14551456.CrossRefGoogle ScholarPubMed
Osté, MC, Duan, MJ, Gomes-Neto, A et al. (2022) Ultra-processed foods and risk of all-cause mortality in renal transplant recipients. Am J Clin Nutr 115, 16461657.CrossRefGoogle ScholarPubMed
Duan, M-J, Vinke, PC, Navis, G et al. Ultra-processed food and incident type 2 diabetes: studying the underlying consumption patterns to unravel the health effects of this heterogeneous food category in the prospective Lifelines cohort. BMC Med 20, 111 (2022).CrossRefGoogle ScholarPubMed
Tobias, DK & Hall, KD (2021) Eliminate or reformulate ultra-processed foods? Biological mechanisms matter. Cell Metab 33, 23142315.CrossRefGoogle ScholarPubMed
Gupta, S, Hawk, T, Aggarwal, A et al. (2019) Characterizing ultra-processed foods by energy density, nutrient density, and cost. Front Nutr 6, 70.CrossRefGoogle ScholarPubMed
Hallinan, S, Rose, C, Buszkiewicz, J et al. (2021) Some ultra-processed foods are needed for nutrient adequate diets: linear programming analyses of the Seattle obesity study. Nutrients 13, 3838.CrossRefGoogle ScholarPubMed
Dwyer, JT, Fulgoni, VL III, Clemens, RA et al. (2012) Is ‘processed’ a four-letter word? The role of processed foods in achieving dietary guidelines and nutrient recommendations. Adv Nutr 3, 536548.CrossRefGoogle ScholarPubMed
Weaver, CM, Dwyer, J, Fulgoni, VL III et al. (2014) Processed foods: contributions to nutrition. Am J Clin Nutr 99, 15251542.CrossRefGoogle ScholarPubMed
Bozkir, H & Tekgül, Y (2022) Production of orange juice concentrate using conventional and microwave vacuum evaporation: thermal degradation kinetics of bioactive compounds and color values. J Food Process Preserv 46, e15902.CrossRefGoogle Scholar
Rogers, PJ, Hogenkamp, PS, de Graaf, C et al. (2016) Does low-energy sweetener consumption affect energy intake and body weight? A systematic review, including meta-analyses, of the evidence from human and animal studies. Int J Obes 40, 381394.CrossRefGoogle ScholarPubMed
Klassen-Wigger, P, Geraets, M, Messier, MC et al. (2018) Micronutrient fortification of bouillon cubes in Central and West Africa. In Food Fortification in a Globalized World, pp. 363372 [Venkatesh Mannar, MG and Hurrell, RF, editors]. Academic Press.CrossRefGoogle Scholar
Lourenco, S, Hansen, GL, Staerk, B et al. (2019) The whole grain partnership – how a public–private partnership helped increase whole grain intake in Denmark. Cereal Foods World 64, 19.Google Scholar
Suthers, R, Broom, M & Beck, E (2018) Key characteristics of public health interventions aimed at increasing whole grain intake: a systematic review. J Nutr Educ Behav 50, 813823.CrossRefGoogle ScholarPubMed
Gressier, M, Swinburn, B, Frost, G et al. (2021) What is the impact of food reformulation on individuals’ behaviour, nutrient intakes and health status? A systematic review of empirical evidence. Obes Rev 22, e13139.CrossRefGoogle ScholarPubMed
Gressier, M, Sassi, F & Frost, G (2020) Healthy foods and healthy diets. How government policies can steer food reformulation. Nutrients 12, 1992.CrossRefGoogle ScholarPubMed
Federici, C, Detzel, P, Petracca, F et al. (2019) The impact of food reformulation on nutrient intakes and health, a systematic review of modelling studies. BMC Nutr 5, 121.Google Scholar
Knorr, D, Ade-Omowaye, B & Heinz, V (2002) Nutritional improvement of plant foods by non-thermal processing. Proc Nutr Soc 61, 311318.CrossRefGoogle ScholarPubMed
Monteiro Cordeiro de Azeredo, H & Monteiro Cordeiro de Azeredo, E (2022) Ultraprocessed foods: bad nutrition or bad definition? ACS Food Sci Technol 2, 613615.CrossRefGoogle Scholar
Meijer, GW, Lähteenmäki, L, Stadler, RH et al. (2021) Issues surrounding consumer trust and acceptance of existing and emerging food processing technologies. Crit Rev Food Sci Nutr 61, 97115.CrossRefGoogle ScholarPubMed
Siegrist, M & Hartmann, C (2020) Consumer acceptance of novel food technologies. Nat Food 1, 343350.CrossRefGoogle ScholarPubMed
van der Goot, AJ, Pelgrom, PJ, Berghout, JA et al. (2016) Concepts for further sustainable production of foods. J Food Eng 168, 4251.CrossRefGoogle Scholar
Robinson, E, Khuttan, M, McFarland-Lesser, I, et al. (2022) A calorie reformulation: a systematic review and meta-analysis examining the effect of manipulating food energy density on daily energy intake. Int J Behav NutrPhys Act 19, 48.CrossRefGoogle ScholarPubMed
Scrinis, G & Monteiro, CA (2018) Ultra-processed foods and the limits of product reformulation. Public Health Nutr 21, 247252.CrossRefGoogle ScholarPubMed
Srour, B, Kordahi, MC, Bonazzi, E et al. (2022) Ultra-processed foods and human health: from epidemiological evidence to mechanistic insights. Lancet Gastroenterol Hepatol 7, 11281140.CrossRefGoogle ScholarPubMed
Juul, F, Vaidean, G & Parekh, N (2021) Ultra-processed foods and cardiovascular diseases: potential mechanisms of action. Adv Nutr 12, 16731680.CrossRefGoogle ScholarPubMed
EFSA Panel on Food Additives and Nutrient Sources added to Food (ANS) (2012) Guidance for submission for food additive evaluations. EFSA J 10, 2760.Google Scholar
EFSA Panel on Food Additives and Nutrient Sources added to Food (ANS) (2014) Statement on a conceptual framework for the risk assessment of certain food additives re-evaluated under Commission Regulation (EU) No 257/2010. EFSA J 12, 3697.Google Scholar
Chazelas, E, Deschasaux, M, Srour, B et al. (2020) Food additives: distribution and co-occurrence in 126,000 food products of the French market. Sci Rep 10, 115.CrossRefGoogle ScholarPubMed
Chazelas, E, Druesne-Pecollo, N, Esseddik, Y et al. (2021) Exposure to food additive mixtures in 106,000 French adults from the NutriNet-Santé cohort. Sci Rep 11, 19680.CrossRefGoogle ScholarPubMed
Gibney, MJ & Forde, CG (2022) Nutrition research challenges for processed food and health. Nat Food 3, 104109.CrossRefGoogle ScholarPubMed
Roberts, CL, Rushworth, SL, Richman, E et al. (2013) Hypothesis: increased consumption of emulsifiers as an explanation for the rising incidence of Crohn's disease. J Crohn's Colitis 7, 338341.CrossRefGoogle ScholarPubMed
Bancil, AS, Sandall, AM, Rossi, M et al. (2021) Food additive emulsifiers and their impact on gut microbiome, permeability, and inflammation: mechanistic insights in inflammatory bowel disease. J Crohn's Colitis 15, 10681079.CrossRefGoogle ScholarPubMed
Las Heras, V, Melgar, S, MacSharry, J et al. (2022) The influence of the western diet on microbiota and gastrointestinal immunity. Annu Rev Food Sci Technol 13, 489512.CrossRefGoogle ScholarPubMed
Karl, JP, Armstrong, NJ, Player, R et al. (2022) The fecal metabolome links diet composition, food processing and the gut microbiota to gastrointestinal health in a randomized trial of adults consuming a processed diet. J Nutr 152, 23432357.CrossRefGoogle Scholar
Zinöcker, MK & Lindseth, IA (2018) The Western diet–microbiome-host interaction and its role in metabolic disease. Nutrients 10, 365.CrossRefGoogle ScholarPubMed
Atzeni, A, Martínez, , Babio, N et al. (2022) Association between ultra-processed food consumption and gut microbiota in senior subjects with overweight/obesity and metabolic syndrome. Front Nutr 9, doi: 10.3389/fnut.2022.976547CrossRefGoogle ScholarPubMed
Ramnani, P, Gaudier, E, Bingham, M et al. (2010) Prebiotic effect of fruit and vegetable shots containing Jerusalem artichoke inulin: a human intervention study. Br J Nutr 104, 233240.CrossRefGoogle ScholarPubMed
Yoshinari, O (2022) Health benefits of inulin-type fructan on gut microbiome, digestive health, immunity, and nutrition. In Nutrition and Functional Foods in Boosting Digestion, Metabolism and Immune Health, pp. 365376 [Bagchi, D and Ohia, SE, editors]. Academic Press.CrossRefGoogle Scholar
Teferra, TF (2021) Possible actions of inulin as prebiotic polysaccharide: a review. Food Front 2, 407416.CrossRefGoogle Scholar
Neumann, NJ & Fasshauer, M (2022) Added flavors: potential contributors to body weight gain and obesity? BMC Med 20, 417.CrossRefGoogle ScholarPubMed
van Langeveld, AW, Gibbons, S, Koelliker, Y et al. (2017) The relationship between taste and nutrient content in commercially available foods from the United States. Food Qual Prefer 57, 17.CrossRefGoogle Scholar
Teo, PS, Tso, R, van Dam, RM et al. (2022) Taste of modern diets: the impact of food processing on nutrient sensing and dietary energy intake. J Nutr 152, 200210.CrossRefGoogle ScholarPubMed
Liu, CM & Kanoski, SE (2018) Homeostatic and non-homeostatic controls of feeding behavior: distinct vs. common neural systems. Physiol Behav 193, 223231.CrossRefGoogle ScholarPubMed
Mela, DJ (2006) Eating for pleasure or just wanting to eat? Reconsidering sensory hedonic responses as a driver of obesity. Appetite 47, 1017.CrossRefGoogle ScholarPubMed
Fazzino, TL, Rohde, K & Sullivan, DK (2019) Hyper-palatable foods: development of a quantitative definition and application to the US food system database. Obesity 27, 17611768.CrossRefGoogle Scholar
Yeomans, MR (2017) Introducing sensory and cognitive influences on satiation and satiety. In Flavor Satiety Food Intake, Chapter 1, pp. 112 [Tepper, BJ and Yeomans, MR, editors].Google Scholar
Center, JGB (1932) The Psychology of Pleasantness and Unpleasantness. D Van Nostrand.CrossRefGoogle Scholar
Yeomans, MR (1998) Taste, palatability and the control of appetite. Proc Nutr Soc 57, 609615.CrossRefGoogle ScholarPubMed
Köster, E & Mojet, J (2007) Boredom and the reasons why some new food products fail. In Consumer-Led Food Product Development, pp. 262280 [MacFie, HJH, editor]. Elsevier.CrossRefGoogle Scholar
Forde, CG & de Graaf, K (2022) Influence of sensory properties in moderating eating behaviors and food intake. Front Nutr 9, 841444.CrossRefGoogle ScholarPubMed
Rolls, BJ, Rolls, ET, Rowe, EA et al. (1981) Sensory specific satiety in man. Physiol Behav 27, 137142.CrossRefGoogle ScholarPubMed
Small, DM & DiFeliceantonio, AG (2019) Processed foods and food reward. Science 363, 346347.CrossRefGoogle ScholarPubMed
Kelly, AL, Baugh, ME, Oster, ME et al. (2022) The impact of caloric availability on eating behavior and ultra-processed food reward. Appetite 178, 106274.CrossRefGoogle ScholarPubMed
Ludwig, DS & Ebbeling, CB (2018) The carbohydrate-insulin model of obesity: beyond ‘calories in, calories out’. JAMA Intern Med 178, 10981103.CrossRefGoogle ScholarPubMed
Hall, KD, Farooqi, IS, Friedman, JM et al. (2022) The energy balance model of obesity: beyond calories in, calories out. Am J Clin Nutr 115, 12431254.CrossRefGoogle ScholarPubMed
Fardet, A (2016) Minimally processed foods are more satiating and less hyperglycemic than ultra-processed foods: a preliminary study with 98 ready-to-eat foods. Food and Funct 7, 23382346.CrossRefGoogle ScholarPubMed
Basile, A, Ruiz-Tejada, A, Mohr, A et al. (2022) Ultra-processed foods have a lower glycemic index and load compared to minimally processed foods. Curr Dev Nutr 6, 504504.CrossRefGoogle Scholar
Hall, KD, Ayuketah, A, Brychta, R et al. (2019) Ultra-processed diets cause excess calorie intake and weight gain: an inpatient randomized controlled trial of ad libitum food intake. Cell Metab 30, 6777. e63.CrossRefGoogle ScholarPubMed
Ello-Martin, JA, Ledikwe, JH & Rolls, BJ (2005) The influence of food portion size and energy density on energy intake: implications for weight management. Am J Clin Nutr 82, 236S241S.CrossRefGoogle ScholarPubMed
Kral, TV, Roe, LS & Rolls, BJ (2004) Combined effects of energy density and portion size on energy intake in women. Am J Clin Nutr 79, 962968.CrossRefGoogle ScholarPubMed
Rolls, BJ, Roe, LS & Meengs, JS (2006) Reductions in portion size and energy density of foods are additive and lead to sustained decreases in energy intake. Am J Clin Nutr 83, 1117.CrossRefGoogle ScholarPubMed
Rolls, BJ (2009) The relationship between dietary energy density and energy intake. Physiol Behav 97, 609615.CrossRefGoogle ScholarPubMed
Ludwig, DS, Astrup, A, Bazzano, LA et al. (2019) Ultra-processed food and obesity: the pitfalls of extrapolation from short studies. Cell Metab 30, 34.CrossRefGoogle ScholarPubMed
Rolls, BJ, Cunningham, PM & Diktas, HE (2020) Properties of ultraprocessed foods that can drive excess intake. Nutr Today 55, 109115.CrossRefGoogle Scholar
Niblett, P, Coyle, N, Little, EA et al. (2019) Sugar reduction: report on progress between 2015 and 2018. London: Public Health England.Google Scholar
Martin, A & Vargas-Garcia, EJ (2022) Financial incentives to promote healthier diets. Trans Food Environ 6, 249262.CrossRefGoogle Scholar
Teo, PS & Forde, CG (2020) The impact of eating rate on energy intake, body composition, and health. In Handbook of Eating and Drinking: Interdisciplinary Perspectives, pp. 715740 [Meiselman, HL, editor]. Springer-Nature.CrossRefGoogle Scholar
Ohkuma, T, Hirakawa, Y, Nakamura, U et al. (2015) Association between eating rate and obesity: a systematic review and meta-analysis. Int J Obes 39, 15891596.CrossRefGoogle ScholarPubMed
Teo, PS, van Dam, RM & Forde, CG (2020) Combined impact of a faster self-reported eating rate and higher dietary energy intake rate on energy intake and adiposity. Nutrients 12, 3264.CrossRefGoogle ScholarPubMed
Teo, PS, van Dam, RM, Whitton, C et al. (2020) Association between self-reported eating rate, energy intake, and cardiovascular risk factors in a multi-ethnic Asian population. Nutrients 12, 1080.CrossRefGoogle Scholar
Teo, PS, van Dam, RM, Whitton, C et al. (2021) Consumption of foods with higher energy intake rates is associated with greater energy intake, adiposity, and cardiovascular risk factors in adults. J Nutr 151, 370378.CrossRefGoogle ScholarPubMed
Forde, CG & Stieger, M (2022) The metabolic impact of Food Oral Processing. In Oral Processing and Consumer Perception, Vol. 30, pp. 137186 [Chen, J, Wolf, B and Bakalis, S, editors]. Royal Society of Chemistry.CrossRefGoogle Scholar
Forde, CG (2018) From perception to ingestion; the role of sensory properties in energy selection, eating behaviour and food intake. Food Qual Prefer 66, 171177.CrossRefGoogle Scholar
Viskaal-van Dongen, M, Kok, FJ & de Graaf, C (2011) Eating rate of commonly consumed foods promotes food and energy intake. Appetite 56, 2531.CrossRefGoogle ScholarPubMed
Forde, C, Leong, C, Chia-Ming, E et al. (2017) Fast or slow-foods? Describing natural variations in oral processing characteristics across a wide range of Asian foods. Food and Funct 8, 595606.CrossRefGoogle ScholarPubMed
Forde, CG (2016) Flavour perception and satiation. In Flavour; From Food to Behaviour, Well-Being and Health, Vol. 1, pp. 251276 [Eteviant, P, Salle, C, Guichard, E and Voilley, A, editors], Woodhead Publishing Series in Food Science, Technology and Nutrition 2016.Google Scholar
Forde, CG, van Kuijk, N, Thaler, T et al. (2013) Texture and savoury taste influences on food intake in a realistic hot lunch time meal. Appetite 60, 180186.CrossRefGoogle Scholar
Forde, CG, van Kuijk, N, Thaler, T et al. (2013) Oral processing characteristics of solid savoury meal components, and relationship with food composition, sensory attributes and expected satiation. Appetite 60, 208219.CrossRefGoogle ScholarPubMed
Wee, MSM, Goh, AT, Stieger, M et al. (2018) Correlation of instrumental texture properties from textural profile analysis (TPA) with eating behaviours and macronutrient composition for a wide range of solid foods. Food Funct 9, 53015312.CrossRefGoogle ScholarPubMed
McCrickerd, K, Lim, CM, Leong, C et al. (2017) Texture-based differences in eating rate reduce the impact of increased energy density and large portions on meal size in adults. J Nutr 147, 12081217.CrossRefGoogle ScholarPubMed
Bolhuis, DP, Forde, CG, Cheng, Y et al. (2014) Slow food: sustained impact of harder foods on the reduction in energy intake over the course of the day. PLoS ONE 9, e93370.CrossRefGoogle ScholarPubMed
Teo, PS, Lim, AJ, Goh, AT et al. (2022) Texture-based differences in eating rate influence energy intake for minimally processed and ultra-processed meals. Am J Clin Nutr 116, 244254.CrossRefGoogle ScholarPubMed
de Graaf, C (2011) Why liquid energy results in overconsumption. Proc Nutr Soc 70, 162170.CrossRefGoogle ScholarPubMed
Mattes, RD (2005) Soup and satiety. Physiol Behav 83, 739747.CrossRefGoogle ScholarPubMed
Mattes, RD & Campbell, WW (2009) Effects of food form and timing of ingestion on appetite and energy intake in lean young adults and in young adults with obesity. J Am Diet Assoc 109, 430437.CrossRefGoogle ScholarPubMed
Mattes, RD & Rothacker, D (2001) Beverage viscosity is inversely related to postprandial hunger in humans. Physiol Behav 74, 551557.CrossRefGoogle ScholarPubMed
Bolhuis, DP & Forde, CG (2020) Application of food texture to moderate oral processing behaviors and energy intake. Trends Food Sci Technol 106, 445456.CrossRefGoogle Scholar
Cunningham, PM, Roe, LS, Keller, KL et al. (2023) Eating rate and bite size were related to food intake across meals varying in portion size: a randomized crossover trial in adults. Appetite 180, 106330.CrossRefGoogle ScholarPubMed
Forde, CG, Mars, M & De Graaf, K (2020) Ultra-processing or oral processing? A role for energy density and eating rate in moderating energy intake from processed foods. Curr Dev Nutr 4, nzaa019, doi: 10.1093/cdn/nzaa019CrossRefGoogle ScholarPubMed
Gibney, MJ (2022) Texture trumps food processing in the regulation of energy intake. Am J Clin Nutr 116, 910.CrossRefGoogle ScholarPubMed
Forde, CG & Bolhuis, D (2022) Interrelations between food form, texture, and matrix influence energy intake and metabolic responses. Curr Nutr Rep 11, 124132.CrossRefGoogle ScholarPubMed
Choy, J, Goh, AT, Chatonidi, G et al. (2021) Impact of food texture modifications on oral processing behaviour, bolus properties and postprandial glucose responses. Curr Res Food Sci 4, 891899.CrossRefGoogle ScholarPubMed
Goh, AT, Chatonidi, G, Choy, M et al. (2021) Impact of individual differences in eating rate on oral processing, bolus properties and post-meal glucose responses. Physiol Behav 238, 113495.CrossRefGoogle ScholarPubMed
Goh, AT, Choy, JYM, Chua, XH et al. (2020) Increased oral processing and a slower eating rate increase glycaemic, insulin and satiety responses to a mixed meal tolerance test. Eur J Nutr 60, 2719–2733.Google Scholar
Chen, Y, Stieger, M, Capuano, E et al. (2022) Influence of oral processing behaviour and bolus properties of brown rice and chickpeas on in vitro starch digestion and postprandial glycaemic response. Eur J Nutr 61, 39613974.CrossRefGoogle Scholar
Gustafson, DI, Decker, EA, Drewnowski, A et al. (2022) Making healthy, sustainable diets accessible and achievable: a new framework for assessing the nutrition, environmental, and equity impacts of packaged foods. Curr Dev Nutr 6, nzac136.CrossRefGoogle ScholarPubMed