Recent technology advancements are aiding the development of scientific discoveries and changing the methods by which we perform research. In order to gain full benefits for human health, it will be important to embrace these new technologies in nutrition research while also acknowledging their limitations. The present issue covers a range of technological approaches that impact on public health nutrition and molecular nutrition. The critical appraisal of these approaches in the context of nutrition research makes this issue a timely and pertinent addition to the scientific literature.

In vitro techniques are essential in elucidating biochemical mechanisms and for screening a wide range of possible bioactive candidates. The number of papers published reporting in vitro bioavailability and bioactivity of flavonoids and flavonoid-rich plant extracts is numerous and still increasing. However, even with the present knowledge on the bioavailability and metabolism of flavonoids after oral ingestion, certain inaccuracies still persist in the literature, such as the use of plant extracts to study bioactivity towards vascular cells. There is therefore a need to revisit, even question, these approaches in terms of their biological relevance. In this review, the bioavailability of flavonoid glycosides, the use of cell models for intestinal absorption and the use of flavonoid aglycones and flavonoid-rich plant extracts in in vitro bioactivity studies will be discussed. Here, we focus on the limitations of current in vitro systems and revisit the validity of some in vitro approaches, and not on the detailed mechanism of flavonoid absorption and bioactivity. Based on the results in the review, there is an apparent need for stricter guidelines on publishing data on in vitro data relating to the bioavailability and bioactivity of flavonoids and flavonoid-rich plant extracts.

It is postulated that knowledge of genotype may be more powerful than other types of personalised information in terms of motivating behaviour change. However, there is also a danger that disclosure of genetic risk may promote a fatalistic attitude and demotivate individuals. The original concept of personalised nutrition (PN) focused on genotype-based tailored dietary advice; however, PN can also be delivered based on assessment of dietary intake and phenotypic measures. Whilst dietitians currently provide PN advice based on diet and phenotype, genotype-based PN advice is not so readily available. The aim of this review is to examine the evidence for genotype-based personalised information on motivating behaviour change, and factors which may affect the impact of genotype-based personalised advice. Recent findings in PN will also be discussed, with respect to a large European study, Food4Me, which investigated the impact of varying levels of PN advice on motivating behaviour change. The researchers reported that PN advice resulted in greater dietary changes compared with general healthy eating advice, but no additional benefit was observed for PN advice based on phenotype and genotype information. Within Food4Me, work from our group revealed that knowledge of MTHFR genotype did not significantly improve intakes of dietary folate. In general, evidence is weak with regard to genotype-based PN advice. For future work, studies should test the impact of PN advice developed on a strong nutrigenetic evidence base, ensure an appropriate study design for the research question asked, and incorporate behaviour change techniques into the intervention.

In addition to their well-known function as dietary lipid detergents, bile acids have emerged as important signalling molecules that regulate energy homeostasis. Recent studies have highlighted that disrupted bile acid metabolism is associated with metabolism disorders such as dyslipidaemia, intestinal chronic inflammatory diseases and obesity. In particular, type 2 diabetes (T2D) is associated with quantitative and qualitative modifications in bile acid metabolism. Bile acids bind and modulate the activity of transmembrane and nuclear receptors (NR). Among these receptors, the G-protein-coupled bile acid receptor 1 (TGR5) and the NR farnesoid X receptor (FXR) are implicated in the regulation of bile acid, lipid, glucose and energy homeostasis. The role of these receptors in the intestine in energy metabolism regulation has been recently highlighted. More precisely, recent studies have shown that FXR is important for glucose homeostasis in particular in metabolic disorders such as T2D and obesity. This review highlights the growing importance of the bile acid receptors TGR5 and FXR in the intestine as key regulators of glucose metabolism and their potential as therapeutic targets.

High-quality placebo-controlled evidence for food, nutrient or dietary advice interventions is vital for verifying the role of diet in optimising health or for the management of disease. This could be argued to be especially important where the benefits of dietary intervention are coupled with potential risks such as compromising nutrient intake, particularly in the case of exclusion diets. The objective of the present paper is to explore the challenges associated with clinical trials in dietary research, review the types of controls used and present the advantages and disadvantages of each, including issues regarding placebos and blinding. Placebo-controlled trials in nutrient interventions are relatively straightforward, as in general placebos can be easily produced. However, the challenges associated with conducting placebo-controlled food interventions and dietary advice interventions are protean, and this has led to a paucity of placebo-controlled food and dietary advice trials compared with drug trials. This review appraises the types of controls used in dietary intervention trials and provides recommendations and nine essential criteria for the design and development of sham diets for use in studies evaluating the effect of dietary advice, along with practical guidance regarding their evaluation. The rationale for these criteria predominantly relate to avoiding altering the outcome of interest in those delivered the sham intervention in these types of studies, while not compromising blinding.

Valid estimation of usual dietary intake in epidemiological studies is a topic of present interest. The aim of the present paper is to review recent literature on innovative approaches focussing on: (1) the requirements to assess usual intake and (2) the application in large-scale settings. Recently, a number of technology-based self-administered tools have been developed, including short-term instruments such as web-based 24-h recalls, mobile food records or simple closed-ended questionnaires that assess the food intake of the previous 24 h. Due to their advantages in terms of feasibility and cost-effectiveness these tools may be superior to conventional assessment methods in large-scale settings. New statistical methods have been developed to combine dietary information from repeated 24-h dietary recalls and FFQ. Conceptually, these statistical methods presume that the usual food intake of a subject equals the probability of consuming a food on a given day, multiplied by the average amount of intake of that food on a typical consumption day. Repeated 24-h recalls from the same individual provide information on consumption probability and amount. In addition, the FFQ can add information on intake frequency of rarely consumed foods. It has been suggested that this combined approach may provide high-quality dietary information. A promising direction for estimation of usual intake in large-scale settings is the integration of both statistical methods and new technologies. Studies are warranted to assess the validity of estimated usual intake in comparison with biomarkers.

Nutrient profiling (NP) models rate the nutritional quality of individual foods, based on their nutrient composition. Their goal is to identify nutrient-rich foods, generally defined as those that contain more nutrients than calories and are low in fat, sugar and salt. NP models have provided the scientific basis for evaluating nutrition and health claims and regulating marketing and advertising to children. The food industry has used NP methods to reformulate product portfolios. To help define what we mean by healthy foods, NP models need to be based on published nutrition standards, mandated serving sizes and open-source nutrient composition databases. Specifically, the development and testing of NP models for public health should follow the seven decision steps outlined by the European Food Safety Authority. Consistent with this scheme, the nutrient-rich food (NRF) family of indices was based on a variable number of qualifying nutrients (from six to fifteen) and on three disqualifying nutrients (saturated fat, added sugar, sodium). The selection of nutrients and daily reference amounts followed nutrient standards for the USA. The base of calculation was 418·4 kJ (100 kcal), in preference to 100 g, or serving sizes. The NRF algorithms, based on unweighted sums of percent daily values, subtracted negative (LIM) from positive (NRn) subscores (NRn – LIM). NRF model performance was tested with respect to energy density and independent measures of a healthy diet. Whereas past uses of NP modelling have been regulatory or educational, voluntary product reformulation by the food industry may have most impact on public health.

In this paper, I first provide definitions of nutrient profiling and of a nutrient profile model. I set out the purposes of nutrient profiling: both general and specific. I give two examples of nutrient profile models that have been developed for regulatory purposes by the Food Standards Agency (FSA) in the UK and the WHO for its European Region – the UK FSA/Ofcom and the WHO-Euro models – and compare the way the models are constructed and function, how they have been developed, the extent to which they have been tested and validated and their use in regulation. Finally I draw some conclusions about the future use of nutrient profiling for regulatory purposes. I argue that its full potential has yet to be realised and give some reasons why. I pose some urgent research questions with respect to nutrient profiling.

Nutrient profiling aims to classify or rank foods according to their nutritional composition to assist policies aimed at improving the nutritional quality of foods and diets. The present paper reviews a French approach of nutrient profiling by describing the SAIN,LIM system and its evolution from its early draft to the simplified nutrition labelling system (SENS) algorithm. Considered in 2010 by WHO as the ‘French model’ of nutrient profiling, SAIN,LIM classifies foods into four classes based on two scores: a nutrient density score (NDS) called SAIN and a score of nutrients to limit called LIM, and one threshold on each score. The system was first developed by the French Food Standard Agency in 2008 in response to the European regulation on nutrition and health claims (European Commission (EC) 1924/2006) to determine foods that may be eligible for bearing claims. Recently, the European regulation (EC 1169/2011) on the provision of food information to consumers allowed simplified nutrition labelling to facilitate consumer information and help them make fully informed choices. In that context, the SAIN,LIM was adapted to obtain the SENS algorithm, a system able to rank foods for simplified nutrition labelling. The implementation of the algorithm followed a step-by-step, systematic, transparent and logical process where shortcomings of the SAIN,LIM were addressed by integrating specificities of food categories in the SENS, reducing the number of nutrients, ordering the four classes and introducing European reference intakes. Through the French example, this review shows how an existing nutrient profiling system can be specifically adapted to support public health nutrition policies.

The primary goal of front of pack (FOP) labelling is to help consumers make healthier choices through communication. A secondary goal is to encourage producers to improve the nutritional composition of their products. Evidence has shown that (FOP) labelling can help consumers to make healthier food choices and has been an incentive for producers to improve product composition. As FOP labelling is seen as an important tool to improve food environments for public health purposes, the WHO supports initiatives of governments to implement an FOP labelling system. Based on the experiences of a wide range of countries over many years, possible success factors for such an FOP system have been defined, six of which are discussed in the present paper and used to evaluate the Dutch Choices Programme that was started in 2006. In the course of time a large number of producers joined the programme and the logo was recognised by more than 90 % of the consumers, but by 2016 the Dutch consumer organisation argued on the basis of their own research that a quarter of the consumers did not understand the colour coding of the logo and as a result the Dutch government decided to no longer support this logo and to introduce a nutrition app. The challenge that remains is to find a system that consumers understand well and that still encourages manufacturers of food to improve product composition. New technology-based data collecting initiatives might provide the right tools to develop such a system.

The food industry holds great potential for driving consumers to adopt healthy food choices as (re)formulation of foods can improve the nutritional quality of these foods. Reformulation has been identified as a cost-effective intervention in addressing non-communicable diseases as it does not require significant alterations of consumer behaviour and dietary habits. Nutrient profiling (NP), the science of categorizing foods based on their nutrient composition, has emerged as an essential tool and is implemented through many different profiling systems to guide reformulation and other nutrition policies. NP systems should be adapted to their specific purposes as it is not possible to design one system that can equally address all policies and purposes, e.g. reformulation and labelling. The present paper discusses some of the key principles and specificities that underlie a NP system designed for reformulation with the example of the Nestlé nutritional profiling system. Furthermore, the impact of reformulation at the level of the food product, dietary intakes and public health are reviewed. Several studies showed that food and beverage reformulation, guided by a NP system, may be effective in improving population nutritional intakes and thereby its health status. In order to achieve its maximum potential and modify the food environment in a beneficial manner, reformulation should be implemented by the entire food sector. Multi-stakeholder partnerships including governments, food industry, retailers and consumer associations that will state concrete time-bound objectives accompanied by an independent monitoring system are the potential solution.

The concept that interactions between nutrition and genetics determine phenotype was established by Garrod at the beginning of the 20th century through his ground-breaking work on inborn errors of metabolism. A century later, the science and technologies involved in sequencing of the human genome stimulated development of the scientific discipline which we now recognise as nutritional genomics (nutrigenomics). Much of the early hype around possible applications of this new science was unhelpful and raised expectations, which have not been realised as quickly as some would have hoped. However, major advances have been made in quantifying the contribution of genetic variation to a wide range of phenotypes and it is now clear that for nutrition-related phenotypes, such as obesity and common complex diseases, the genetic contribution made by SNP alone is often modest. There is much scope for innovative research to understand the roles of less well explored types of genomic structural variation, e.g. copy number variants, and of interactions between genotype and dietary factors, in phenotype determination. New tools and models, including stem cell-based approaches and genome editing, have huge potential to transform mechanistic nutrition research. Finally, the application of nutrigenomics research offers substantial potential to improve public health e.g. through the use of metabolomics approaches to identify novel biomarkers of food intake, which will lead to more objective and robust measures of dietary exposure. In addition, nutrigenomics may have applications in the development of personalised nutrition interventions, which may facilitate larger, more appropriate and sustained changes in eating (and other lifestyle) behaviours and help to reduce health inequalities.

The advent of the internet and smartphone technology has allowed dietary assessment to reach the 21st century! The variety of foods available on the supermarket shelf is now greater than ever before. New approaches to measuring diet may help to reduce measurement error and advance our understanding of nutritional determinants of disease. This advance provides the potential to capture detailed dietary data on large numbers of individuals without the need for costly and time-consuming manual nutrition coding. This aim of the present paper is to review the need for new technologies to measure diet with an overview of tools available. The three main areas will be addressed: (1) development of web-based tools to measure diet; (2) use of smartphone apps to self-monitor diet; (3) improving the quality of dietary assessment through development of an online library of tools. A practical example of the development of a web-based tool to assess diet myfood24 (www.myfood24.org) will be given exploring its potential, limitations and challenges. The development of a new food composition database using back-of-pack information will be described. Smartphone apps used to measure diet with a focus on obesity will be reviewed. Many apps are unreliable in terms of tracking, and most are not evaluated. Accurate and consistent measurement of diet is needed for public health and epidemiology. The choice of the most appropriate dietary assessment method tends to rely on experience. The DIET@NET partnership has developed best practice guidelines for selection of dietary assessment tools, which aim to improve the quality, consistency and comparability of dietary data. These developments provide us with a step-change in our ability to reliably characterise food and nutrient intake in population studies. The need for high-quality, validated systems will be important to fully realise the benefits of new technologies.

For nutrition practitioners and researchers, assessing dietary intake of children and adults with a high level of accuracy continues to be a challenge. Developments in mobile technologies have created a role for images in the assessment of dietary intake. The objective of this review was to examine peer-reviewed published papers covering development, evaluation and/or validation of image-assisted or image-based dietary assessment methods from December 2013 to January 2016. Images taken with handheld devices or wearable cameras have been used to assist traditional dietary assessment methods for portion size estimations made by dietitians (image-assisted methods). Image-assisted approaches can supplement either dietary records or 24-h dietary recalls. In recent years, image-based approaches integrating application technology for mobile devices have been developed (image-based methods). Image-based approaches aim at capturing all eating occasions by images as the primary record of dietary intake, and therefore follow the methodology of food records. The present paper reviews several image-assisted and image-based methods, their benefits and challenges; followed by details on an image-based mobile food record. Mobile technology offers a wide range of feasible options for dietary assessment, which are easier to incorporate into daily routines. The presented studies illustrate that image-assisted methods can improve the accuracy of conventional dietary assessment methods by adding eating occasion detail via pictures captured by an individual (dynamic images). All of the studies reduced underreporting with the help of images compared with results with traditional assessment methods. Studies with larger sample sizes are needed to better delineate attributes with regards to age of user, degree of error and cost.

Traditional methods for the assessment of dietary intake are prone to error; in order to improve and enhance these methods increasing interest in the identification of dietary biomarkers has materialised. Metabolomics has emerged as a key tool in the area of dietary biomarker discovery and to date the use of metabolomics has identified a number of putative biomarkers. Applications to identify novel biomarkers of intake have in general taken three approaches: (1) specific acute intervention studies to identify specific biomarkers of intake; (2) searching for biomarkers in cohort studies by correlating to self-reported intake of a specific food/food group(s); (3) analysing dietary patterns in conjunction with metabolomic profiles to identify biomarkers and nutritypes. A number of analytical technologies are employed in metabolomics as currently there is no single technique capable of measuring the entire metabolome. These approaches each have their own advantages and disadvantages. The present review will provide an overview of current technologies and applications of metabolomics in the determination of new dietary biomarkers. In addition, it will address some of the current challenges in the field and future outlooks.

Metabolomic and microbiome profiling are promising tools to identify biomarkers of food intake and health status. The individual's genetic makeup plays a significant role on health, metabolism, gut microbes and diet and twin studies provide unique opportunities to untangle gene–environment effects on complex phenotypes. This brief review discusses the value of twin studies in nutrition research with a particular focus on metabolomics and the gut microbiome. Although, the twin model is a powerful tool to segregate the genetic component, to date, very few studies combine the twin design and metabolomics/microbiome in nutritional sciences. Moreover, since the individual's diet has a strong influence on the microbiome composition and the gut microbiome is modifiable (60 % of microbiome diversity is due to the environment), future studies should target the microbiome via dietary interventions.

A high intake of fruit and vegetables (FV) has been associated with reduced risk of a number of chronic diseases, including CVD. The aim of this review is to describe the potential use of biomarkers to assess FV intake. Traditional methods of assessing FV intake have limitations, and this is likely to impact on observed associations with disease outcomes and markers of disease risk. Nutritional biomarkers may offer a more objective and reliable method of assessing dietary FV intake. Some single blood biomarkers, such as plasma vitamin C and serum carotenoids, are well established as indicators of FV intake. Combining potential biomarkers of intake may more accurately predict overall FV intake within intervention studies than the use of any single biomarker. Another promising approach is metabolomic analysis of biological fluids using untargeted approaches to identify potential new biomarkers of FV intake. Using biomarkers to measure FV intake may improve the accuracy of dietary assessment.

Health nudge interventions to steer people into healthier lifestyles are increasingly applied by governments worldwide, and it is natural to look to such approaches to improve health by altering what people choose to eat. However, to produce policy recommendations that are likely to be effective, we need to be able to make valid predictions about the consequences of proposed interventions, and for this, we need a better understanding of the determinants of food choice. These determinants include dietary components (e.g. highly palatable foods and alcohol), but also diverse cultural and social pressures, cognitive-affective factors (perceived stress, health attitude, anxiety and depression), and familial, genetic and epigenetic influences on personality characteristics. In addition, our choices are influenced by an array of physiological mechanisms, including signals to the brain from the gastrointestinal tract and adipose tissue, which affect not only our hunger and satiety but also our motivation to eat particular nutrients, and the reward we experience from eating. Thus, to develop the evidence base necessary for effective policies, we need to build bridges across different levels of knowledge and understanding. This requires experimental models that can fill in the gaps in our understanding that are needed to inform policy, translational models that connect mechanistic understanding from laboratory studies to the real life human condition, and formal models that encapsulate scientific knowledge from diverse disciplines, and which embed understanding in a way that enables policy-relevant predictions to be made. Here we review recent developments in these areas.

Non-communicable diseases (NCD) are the leading cause of death globally. Smart health technology and innovation is a potential strategy for increasing reach and for facilitating health behaviour change. Despite rapid growth in the availability and affordability of technology there remains a paucity of published and robust research in the area as it relates to health. The objective of the present paper is to review and provide a snapshot of a variety of contemporary examples of smart health strategies with a focus on evidence and research as it relates to prevention with a CVD management lens. In the present analysis, five examples will be discussed and they include a physician-directed strategy, consumer directed strategies, a public health approach and a screening strategy that utilises external hardware that connects to a smartphone. In conclusion, NCD have common risk factors and all have an association with nutrition and health. Smart health and innovation is evolving rapidly and may help with diagnosis, treatment and management. While on-going research, development and knowledge is needed, the growth of technology development and utilisation offers opportunities to reach more people and achieve better health outcomes at local, national and international levels.

There is increasing evidence documenting gene-by-environment (G × E) interactions for CVD related traits. However, the underlying mechanisms are still unclear. DNA methylation may represent one of such potential mechanisms. The objective of this review paper is to summarise the current evidence supporting the interplay among DNA methylation, genetic variants, and environmental factors, specifically (1) the association between SNP and DNA methylation; (2) the role that DNA methylation plays in G × E interactions. The current evidence supports the notion that genotype-dependent methylation may account, in part, for the mechanisms underlying observed G × E interactions in loci such as APOE, IL6 and ATP-binding cassette A1. However, these findings should be validated using intervention studies with high level of scientific evidence. The ultimate goal is to apply the knowledge and the technology generated by this research towards genetically based strategies for the development of personalised nutrition and medicine.