The workplace is a key environmental determinant of health and well-being. Food choices can be influenced by several workplace-related factors including, but not limited to, working hours, the workplace food environment, job roles and workplace culture. Therefore, the workplace is increasingly viewed as an important place for public health nutrition interventions. However, research in this area is fragmented and heterogeneous due to the wide range of workplace settings and occupational groups. This editorial summarises the research presented at The Nutrition Society Workplace Diet and Health Special Interest Group Satellite Symposium in July 2024 as part of the inaugural Nutrition Society Congress.

The current review will examine the field of food intake biomarkers and the potential use of such biomarkers. Biomarkers of food intake have the potential to be objective measures of intake thus addressing some of the limitations associated with self-reported dietary assessment methods. They are typically food-derived biomarkers present in biological samples and distinct from endogenous metabolites. To date, metabolomic profiling has been successful in identifying several putative food intake biomarkers. With respect to food intake biomarkers, there has been a proliferation of publications in this field. However, caution is needed when interpreting these as food intake biomarkers. Many have not been validated thus hampering their use. While much of the focus to date is on discovery of food intake biomarkers there are excellent examples of how to utilise these biomarkers in nutrition research. Applications include but are not limited to: (1) measurement of adherence to diets in intervention studies (2) objectively predicting intake with no reliance on self-reported data and (3) calibrating self-reported data in large epidemiological studies. Examples of these applications will be covered in this review. While significant progress is achieved to date in the food intake biomarkers field there are a number of key challenges that remain. Examples include lack of databases focused on food-derived metabolites thus hindering the discovery of new biomarkers and the need for new statistical approaches to deal with multiple biomarkers for single foods. Addressing these and other key challenges will be key to development of future opportunities.

Food insecurity (also known as food poverty) is the inability to afford or access a healthy diet. It has become recognised as a public health emergency and is a priority in the context of the environmental, geopolitical and socio-economic implications on businesses, households and civic society. This review paper aims to discuss the merits of collecting food insecurity data and its importance in informing cross-sectoral government and others’ understanding, policymaking and action on hunger. The review paper’s key findings are that concerted action on measuring and mapping food insecurity with the aim of eliminating or reducing its prevalence represents a triple win for government, business and citizens. However, measurement does not provide solutions to food insecurity but contributes importantly to understanding its extent and severity to inform and evaluate proffered solutions. Government, business and food insecurity researchers and commentators cannot merely continue to simply describe food poverty - but must effect meaningful change amidst our communities to improve life quality in a timely way for those experiencing acute and chronic hunger. This is best done by addressing the structural causes of food insecurity through economically, socially and culturally fair and appropriate policy levers, requiring cross-sectoral collaboration. Ultimately, food insecurity requires a long-term, sustainable solution that addresses the policy issues under focus: low income, under/unemployment, rising food prices and Welfare Reform, informed by routine, Government-supported monitoring and reporting of the extent of food poverty among our citizens.

Randomised controlled trials are the ‘gold standard’ approach in nutrition research to show a causal relationship between a dietary intervention and clinically relevant outcomes at the population level. Here we review why different study designs are needed to establish the efficacy of dietary interventions at the individual level and to better account for relevant factors that can also influence the outcomes. Over the past decade, precision nutrition approaches have been developed as a new way to measure the effectiveness of dietary interventions at the individual and population level. Precision nutrition aims to determine the individual factors that are associated with differences in responses to dietary interventions. This is complex, typically needing studies with a large number of participants and using advanced statistical approaches and machine-learning algorithms to identify predictors that can explain why individuals do or do not respond to consuming specific foods, meals or diets, for a given outcome. N-of-1 study designs, which are new to nutrition science, offer a robust alternative approach to assess how an intervention and everyday behaviours affect individual health outcomes. They utilise repeated measures within individuals, rather than baseline and end measures in a larger number of participants, to provide the statistical power required to determine an individual’s responsiveness to an intervention. The adoption of new study designs and modelling approaches, particularly the N-of-1 approach, to examine responses to interventions within individuals, will help to further the understanding of the relationships between diet and health within individuals more effectively and accurately.

By involving stakeholders to identify issues, co-design facilitates the creation of solutions aligned with the community’s unique needs and values. However, genuine co-design with consumers across all stages of nutrition intervention research remains uncommon. The aim of this review was to examine notable examples of interventions to improve diets in rural settings that have been co-designed by rural communities. Six studies were identified reporting on community-based and digital interventions to improve diets in rural settings that have been co-designed by rural communities. The level of co-design used varied, with two interventions describing co-design workshops and focus groups over a period of between 6 and 11 months, and others not reporting details on the co-design process. Collectively, most interventions demonstrated positive impacts on dietary markers, including an increase in purchase of fruit and vegetable, an increase in percentage energy from nutrient dense foods and a decrease in intake of high fat meats. While these interventions show promise for improving diets in these under-served communities, it is widely recognised that there is a lack of dietary interventions genuinely co-designed with and for rural communities. Future research should build on these studies to co-design dietary interventions that integrate the benefits of both community-based and digital interventions.

Psoriasis is a chronic debilitating skin disease affecting 2 % of the UK population. The aetiopathogenesis of psoriasis arises from a combination of genetic susceptibly and lifestyle patterns including stress, infections, alcohol misuse, lack of physical activity and adiposity. This unfavourable gene-lifestyle pairing triggers a series of inflammatory responses resulting in the uncontrolled proliferation of skin cells characteristic of psoriasis, which at present is an incurable disease. Concurrent with the systemic nature of the condition, psoriasis has effects beyond the skin with concomitant cardiometabolic complications, arthritis, gastrointestinal diseases and depression, emphasising the need for other strategies beyond pharmaceutical therapies to support psoriasis treatments. The role of diet in psoriasis management has not been clearly established and only two evidence-based recommendations are available for people with psoriasis. This review aims to critically appraise the research examining dietary patterns in psoriasis populations, highlight the gaps in the evidence-base, and present directions for future research.

Current food systems pose risks to both population and environmental health. Reducing the intake of animal-based foods, such as dairy products, and increasing consumption of plant-based foods align with priorities for addressing climate change and promoting overall health. Plant-based alternatives to cow’s milk can be readily substituted for cow’s milk without altering meal patterns and food habits, making them a popular choice among those reducing animal-product consumption. However, plant-based milk alternatives do not necessarily provide the same nutrients as cow’s milk, particularly essential micronutrients like iodine. While national data indicate that the UK is iodine-replete, certain population subgroups (such as pregnant women, women of reproductive age, and vegans) remain at risk of iodine deficiency. Young women are more likely than other age groups to consume plant-based milk alternatives, heightening public health concerns about iodine insufficiency in this demographic. Current consumers of plant-based milk alternatives in the UK have lower iodine intake and status compared to consumers of cow’s milk. Population-level effects of replacing milk with plant-based alternatives vary and depend on factors such as the role of plant-based milk alternatives in the diet (i.e. in addition to, or as a replacement for milk), the presence of other iodine sources in the diet, the consumer’s life stage, and whether the alternatives are fortified with iodine. This review examines the literature on plant-based milk alternatives and iodine intake, focusing on implications of this dietary shift and strategies to improve iodine intake in those opting for plant-based milk alternatives in the UK population.

The European Food Safety Authority (EFSA) provides independent scientific advice to EU risk managers on a wide range of food safety issues and communicates on existing and emerging risks in the food chain. This advice helps to protect consumers, animals and the environment. Data are essential to EFSA’s scientific assessments. EFSA collects data from various sources including scientific literature, biological and chemical monitoring programmes, as well as food consumption and composition databases. EFSA also assesses data from authorisation dossiers for regulated products submitted by the industry. To continue delivering the highest value for society, EFSA keeps abreast of new scientific, technological and societal developments. EFSA also engages in partnerships as an essential means to address the growing complexity in science and society and to better connect and integrate knowledge, data and expertise across sectors. This paper provides insights into EFSA’s data-related activities and future perspectives in the following key areas of EFSA’s 2027 strategy: one substance-one assessment, combined exposure to multiple chemicals, environmental risk assessment, new approach methodologies, antimicrobial resistance and risk–benefit assessment. EFSA’s initiatives to integrate societal insights in its risk communication are also described.

Systems thinking is deeply rooted in history, as far back as Aristotle. However, it has only relatively recently reemerged as an approach to help us understand and intervene in health and food systems. This is particularly salient, given its impact on environmental and population health. Whilst global food is abundant, many people cannot access affordable, healthy and culturally appropriate food. On the other hand, foods of low nutrient density are widely available. Food systems are complex and require complex thinking and approaches that allow us to consider the influence of multiple factors and how the might system respond to change. In turn, this enables the identification of ‘leverage’ points, where policies or interventions are most likely to have a sustained impact. The Foresight obesity map inspired others to adopt systems approaches to help understand the broader social, economic and environmental determinants of obesity to support intervention/policy development. Evaluation of these requires a consideration of complexity to explore why intervention goals may or may not have been successful and how relationships between components or approaches can be enhanced to support implementation and thereby increase the potential for effectiveness. Overall, approaches to understand, intervene, govern and evaluate food systems must themselves be sufficiently complex, or will ultimately be destroyed by the system it seeks to improve. This review paper aims to introduce readers to the application of systems approaches in research within the context of food systems and health, including its traditional/historical origins.

The WHO describes micronutrient deficiencies, or hidden hunger, as a form of malnutrition that occurs due to low intake and/or absorption of minerals and vitamins, putting human development and health at risk. In many cases, emphasis, effort and even policy revolve around the prevention of deficiency of one particular micronutrient in isolation. This is understandable as that micronutrient may be among a group of nutrients of public health concern. Vitamin D is a good exemplar. This review will highlight how the actions taken to tackle low vitamin D status have been highly dependent on the generation of new data and/or new approaches to analysis of existing data, to help develop the evidence-base, inform advice/guidelines, and in some cases, translate into policy. Beyond focus on individual micronutrients, there has also been increasing international attention around hidden hunger, or deficiencies of a range of micronutrients, which can exist unaccompanied by obvious clinical signs but can adversely affect human development and health. A widely quoted estimate of the global prevalence of hidden hunger is a staggering two billion people, but this is now over 30 years old. This review will outline how strategic data sharing and generation is seeking to address this key knowledge gap in relation to the true prevalence of hidden hunger in Europe, a key starting point towards defining sustainable and cost-effective, food-based strategies for its prevention. The availability of data on prevalence and food-based strategies can help inform public policy to eradicate micronutrient deficiency in Europe.

While malnutrition (including both undernutrition and overweight/obesity and related non-communicable diseases) remains a persistent challenge in countries around the world, it is far from alone as a threat to human development and wellbeing – and is increasingly viewed as intersecting with climate change and environmental degradation. At the crossroads of these issues, animal-source foods (ASFs, including meat, fish, seafood, dairy and eggs) have attracted considerable attention in recent years, both for their role in diets and for their environmental impacts. Heated debate has focused on the potential benefits of reducing consumption of ASFs as well as the potential nutritional risks associated with this. ASF production also plays an important role in livelihoods, particularly in low- and middle-income countries. ASFs are also central to many food cultures and traditions, highly valued by many consumers. As the issues associated with ASFs are intertwined, they must be considered jointly and with nuance. Given wide global ranges in ASF consumption, environmental footprints and malnutrition rates and types, considering equity (in terms of ASF consumption and production) is also critical. This review examines these complex issues, discussing ASFs from the perspectives of nutrition and health, environmental impacts, livelihoods and society, and equity. It also examines potential future options for reducing environmental impacts of ASFs.

Nations are revising dietary guidelines to include sustainability recommendations in response to climate change concerns. Given low adherence to current guidelines, consumer inertia is a challenge. A proliferation of nutrition information providers and dietary messages contributes to confusion. All this suggests that health professionals will face considerable obstacles in facilitating a population shift towards sustainable and healthy (SuHe) diets. This review explores the role of nutrition science in shaping dietary behaviour and the challenges of shifting the nutrition narrative to encompass both health and sustainability. Societal transformation towards the ‘asks’ of a SuHe diet will rely on consumer-level transformation of food acquisition, preparation, consumption, storage and disposal behaviours. Acceptance of a higher share of plant-based food and a reduction in animal protein in the diet is likely to provoke disorientations as consumers’ previously unexamined beliefs are challenged. The challenges presented by portion size distortion, protein reduction and replacement, and the role of ultra-processed food are discussed here in terms of sources of confusion. The routes to change involve deeper understanding of responses to disorientations through processes of belief formation and transformation, which are the foundations of subjective knowledge and attitudes, likely mediated through affective factors. In tandem with introducing new potentially disorienting-to-consumers information, health professionals need to consider the environments where this information is presenting and consider how these environments are designed to support action. In doing so, reactance and backlash through belief rejection and behavioural non-adherence could be reduced.

Machine learning is increasingly being utilised across various domains of nutrition research due to its ability to analyse complex data, especially as large datasets become more readily available. However, at times, this enthusiasm has led to the adoption of machine learning techniques prior to a proper understanding of how they should be applied, leading to non-robust study designs and results of questionable validity. To ensure that research standards do not suffer, key machine learning concepts must be understood by the research community. The aim of this review is to facilitate a better understanding of machine learning in research by outlining good practices and common pitfalls in each of the steps in the machine learning process. Key themes include the importance of generating high-quality data, employing robust validation techniques, quantifying the stability of results, accurately interpreting machine learning outputs, adequately describing methodologies, and ensuring transparency when reporting findings. Achieving this aim will facilitate the implementation of robust machine learning methodologies, which will reduce false findings and make research more reliable, as well as enable researchers to critically evaluate and better interpret the findings of others using machine learning in their work.