Paving the way to better population health through personalised nutrition

The effectiveness of personalised food choice advice tailored to an individual's socio-demographic, cognitive characteristics, and sensory preferences

Personalised dietary advice has become increasingly popular, currently however most approaches are based on an individual's genetic and phenotypic profile whilst largely ignoring other determinants such as socio economic and cognitive variables. This paper provides novel insights by testing the effectiveness of personalised healthy eating advice concurrently tailored to an individual's socio-demographic group, cognitive characteristics, and sensory preferences. We first used existing data to build a synthetic dataset based on information from 3654 households (Study 1a), and then developed a cluster model to identify individuals characterised by similar socio-demographic, cognitive, and sensory aspects (Study 1b). Finally, in Study 2 we used the characteristics of 8 clusters to build 8 separate personalised food choice advice and assess their ability to motivate the increased consumption of fruit and vegetables and decreased intakes of saturated fat and sugar. We presented 218 participants with either generic UK Government "EatWell" advice, advice that was tailored to their allocated cluster (matched personalised), or advice tailored to a different cluster (unmatched personalised). Results showed that, when compared to generic advice, participants that received matched personalised advice were significantly more likely to indicate they would change their diet. Participants were similarly motivated to increase vegetable consumption and decrease saturated fat intake when they received unmatched personalised advice, potentially highlighting the power of providing alternative food choices. Overall, this study demonstrated that the power of personalizing food choice advice, based on a combination of individual characteristics, can be more effective than current approaches in motivating dietary change. Our study also emphasizes the viability of addressing population health through automatically delivered web-based personalised advice.

A single-blinded, randomized, parallel intervention to evaluate genetics and omics-based personalized nutrition in general population via an e-commerce tool: The PREVENTOMICS e-commerce study

BACKGROUND

Personalized nutrition (PN) has been proposed as a strategy to increase the effectiveness of dietary recommendations and ultimately improve health status.

OBJECTIVES

We aimed to assess whether including omics-based PN in an e-commerce tool improves dietary behavior and metabolic profile in general population.

METHODS

A 21-wk parallel, single-blinded, randomized intervention involved 193 adults assigned to a control group following Mediterranean diet recommendations (n = 57, completers = 36), PN (n = 70, completers = 45), or personalized plan (PP, n = 68, completers = 53) integrating a behavioral change program with PN recommendations. The intervention used metabolomics, proteomics, and genetic data to assist participants in creating personalized shopping lists in a simulated e-commerce retailer portal. The primary outcome was the Mediterranean diet adherence screener (MEDAS) score; secondary outcomes included biometric and metabolic markers and dietary habits.

RESULTS

Volunteers were categorized with a scoring system based on biomarkers of lipid, carbohydrate metabolism, inflammation, oxidative stress, and microbiota, and dietary recommendations delivered accordingly in the PN and PP groups. The intervention significantly increased MEDAS scores in all volunteers (control-3 points; 95% confidence interval [CI]: 2.2, 3.8; PN-2.7 points; 95% CI: 2.0, 3.3; and PP-2.8 points; 95% CI: 2.1, 3.4; q < 0.001). No significant differences were observed in dietary habits or health parameters between PN and control groups after adjustment for multiple comparisons. Nevertheless, personalized recommendations significantly (false discovery rate < 0.05) and selectively enhanced the scores calculated with biomarkers of carbohydrate metabolism (β: -0.37; 95% CI: -0.56, -0.18), oxidative stress (β: -0.37; 95% CI: -0.60, -0.15), microbiota (β: -0.38; 95% CI: -0.63, -0.15), and inflammation (β: -0.78; 95% CI: -1.24, -0.31) compared with control diet.

CONCLUSIONS

Integration of personalized strategies within an e-commerce-like tool did not enhance adherence to Mediterranean diet or improved health markers compared with general recommendations. The metabotyping approach showed promising results and more research is guaranteed to further promote its application in PN. This trial was registered at clinicaltrials.gov as NCT04641559 (https://clinicaltrials.gov/study/NCT04641559?cond=NCT04641559&rank=1).

Forgetting how we ate: personalised nutrition and the strategic uses of history

Personalised nutrition (PN) has emerged over the past twenty years as a promising area of research in the postgenomic era and has been popularized as the new big thing out of molecular biology. Advocates of PN claim that previous approaches to nutrition sought general and universal guidance that applied to all people. In contrast, they contend that PN operates with the principle that "one size does not fit all" when it comes to dietary guidance. While the molecular mechanisms studied within PN are new, the notion of a personal dietary regime guided by medical advice has a much longer history that can be traced back to Galen's "On Food and Diet" or Ibn Sina's (westernized as Avicenna) "Canon of Medicine". Yet this history is either wholly ignored or misleadingly appropriated by PN proponents. This (mis)use of history, we argue helps to sustain the hype of the novelty of the proposed field and potential commodification of molecular advice that undermines longer histories of food management in premodern and non-Western cultures. Moreover, it elides how the longer history of nutritional advice always happened in a heavily moralized, gendered, and racialized context deeply entwined with collective technologies of power, not just individual advice. This article aims at offering a wider appreciation of this longer history to nuance the hype and exceptionalism surrounding contemporary claims.

A health technology assessment of personalized nutrition interventions using the EUnetHTA HTA Core Model

OBJECTIVES

Poor nutrition links to chronic diseases, emphasizing the need for optimized diets. The EU-funded project PREVENTOMICS, introduced personalized nutrition to address this. This study aims to perform a health technology assessment (HTA) comparing personalized nutrition interventions developed through this project, with non-personalized nutrition interventions (control) for people with normal weight, overweight, or obesity. The goal is to support decisions about further development and implementation of personalized nutrition.

METHODS

The PREVENTOMICS interventions were evaluated using the European Network for HTA Core Model, which includes a methodological framework that encompasses different domains for value assessment. Information was gathered via [1] different statistical analyses and modeling studies, [2] questions asked of project partners and, [3] other (un)published materials.

RESULTS

Clinical trials of PREVENTOMICS interventions demonstrated different body mass index changes compared to control; differences ranged from -0.80 to 0.20 kg/m2. Long-term outcome predictions showed generally improved health outcomes for the interventions; some appeared cost-effective (e.g., interventions in UK). Ethical concerns around health inequality and the lack of specific legal regulations for personalized nutrition interventions were identified. Choice modeling studies indicated openness to personalized nutrition interventions; decisions were primarily affected by intervention's price.

CONCLUSIONS

PREVENTOMICS clinical trials have shown promising effectiveness with no major safety concerns, although uncertainties about effectiveness exist due to small samples (n=60-264) and short follow-ups (10-16 weeks). Larger, longer trials are needed for robust evidence before implementation could be considered. Among other considerations, developers should explore financing options and collaborate with policymakers to prevent exclusion of specific groups due to information shortages.

The Future of Food

The global food systems face significant challenges driven by population growth, climate change, geopolitical conflicts, crises, and evolving consumer preferences. Intending to address these challenges, optimizing food production, adopting sustainable practices, and developing technological advancements are essential while ensuring the safety and public acceptance of innovations. This review explores the complex aspects of the future of food, encompassing sustainable food production, food security, climate-resilient and digitalized food supply chain, alternative protein sources, food processing, and food technology, the impact of biotechnology, cultural diversity and culinary trends, consumer health and personalized nutrition, and food production within the circular bioeconomy. The article offers a holistic perspective on the evolving food industry characterized by innovation, adaptability, and a shared commitment to global food system resilience. Achieving sustainable, nutritious, and environmentally friendly food production in the future involves comprehensive changes in various aspects of the food supply chain, including innovative farming practices, evolving food processing technologies, and Industry 4.0 applications, as well as approaches that redefine how we consume food.

The imprecision of micronutrient requirement values: the example of vitamin D

Food, not nutrients, is the fundamental unit in nutrition. Nutrient requirement values and recommended daily intakes have long been determined and organized in tables by several regulators. These figures, however, overlook the complexity of mixing different foods in a diet and the mediation by human gut microbiota on digestion, metabolism, and health. The microbiome molecular mechanisms and its potential influence on nutrient requirements are far from clear. Guidelines should depend on the sort of intake, along with the dietary habits, rather than focusing on single nutrients. Despite many decades of attempts to investigate the proximate nutrient composition of foods consumed by different world populations, there are still neither standardization of food composition databases nor harmonized dietary intake methods of assessment of nutrients. No all-inclusive attempt was yet made to emphasize the requirements of the various micronutrients, phytonutrients, and non-nutrients on gut microbiota and vice versa, and thereafter reflected into dietary guidelines. New multifaceted methods have been advanced to reevaluate the way nutrients and nutrient requirements are assessed within the intricate biological systems. Our main goal here was to enhance the fact that existing food guidelines hold inherent strengths and limitations but fail, in many aspects, namely, in not taking into account essential geographical, ethnic and cultural differences, and the different stages of life, infant nutrition, and the microbiota impact on several micronutrient requirements. Vitamin D is given as an illustration on present inaccuracy of its requirements. Defining dietary reference intakes is therefore an ongoing process specific for each population.

Distinct patterns of personalised dietary advice delivered by a metabotype framework similarly improve dietary quality and metabolic health parameters: secondary analysis of a randomised controlled trial

Background

In a 12-week randomised controlled trial, personalised nutrition delivered using a metabotype framework improved dietary intake, metabolic health parameters and the metabolomic profile compared to population-level dietary advice. The objective of the present work was to investigate the patterns of dietary advice delivered during the intervention and the alterations in dietary intake and metabolic and metabolomic profiles to obtain further insights into the effectiveness of the metabotype framework.

Methods

Forty-nine individuals were randomised into the intervention group and subsequently classified into metabotypes using four biomarkers (triacylglycerol, HDL-C, total cholesterol, glucose). These individuals received personalised dietary advice from decision tree algorithms containing metabotypes and individual characteristics. In a secondary analysis of the data, patterns of dietary advice were identified by clustering individuals according to the dietary messages received and clusters were compared for changes in dietary intake and metabolic health parameters. Correlations between changes in blood clinical chemistry and changes in metabolite levels were investigated.

Results

Two clusters of individuals with distinct patterns of dietary advice were identified. Cluster 1 had the highest percentage of messages delivered to increase the intake of beans and pulses and milk and dairy products. Cluster 2 had the highest percentage of messages delivered to limit the intake of foods high in added sugar, high-fat foods and alcohol. Following the intervention, both patterns improved dietary quality assessed by the Alternate Mediterranean Diet Score and the Alternative Healthy Eating Index, nutrient intakes, blood pressure, triacylglycerol and LDL-C (p ≤ 0.05). Several correlations were identified between changes in total cholesterol, LDL-C, triacylglycerol, insulin and HOMA-IR and changes in metabolites levels, including mostly lipids (sphingomyelins, lysophosphatidylcholines, glycerophosphocholines and fatty acid carnitines).

Conclusion

The findings indicate that the metabotype framework effectively personalises and delivers dietary advice to improve dietary quality and metabolic health.

Clinical trial registration

isrctn.com, identifier ISRCTN15305840.

Characterizing Precision Nutrition Discourse on Twitter: Quantitative Content Analysis

BACKGROUND

It is possible that tailoring dietary approaches to an individual's genomic profile could provide optimal dietary inputs for biological functioning and support adherence to dietary management protocols. The science required for such nutrigenetic and nutrigenomic profiling is not yet considered ready for broad application by the scientific and medical communities; however, many personalized nutrition products are available in the marketplace, creating the potential for hype and misleading information on social media. Twitter provides a unique big data source that provides real-time information. Therefore, it has the potential to disseminate evidence-based health information, as well as misinformation.

OBJECTIVE

We sought to characterize the landscape of precision nutrition content on Twitter, with a specific focus on nutrigenetics and nutrigenomics. We focused on tweet authors, types of content, and presence of misinformation.

METHODS

Twitter Archiver was used to capture tweets from September 1, 2020, to December 1, 2020, using keywords related to nutrition and genetics. A random sample of tweets was coded using quantitative content analysis by 4 trained coders. Codebook-driven, quantified information about tweet authors, content details, information quality, and engagement metrics were compiled and analyzed.

RESULTS

The most common categories of tweets were precision nutrition products and nutrigenomic concepts. About a quarter (132/504, 26.2%) of tweet authors presented themselves as science experts, medicine experts, or both. Nutrigenetics concepts most frequently came from authors with science and medicine expertise, and tweets about the influence of genes on weight were more likely to come from authors with neither type of expertise. A total of 14.9% (75/504) of the tweets were noted to contain untrue information; these were most likely to occur in the nutrigenomics concepts topic category.

CONCLUSIONS

By evaluating social media discourse on precision nutrition on Twitter, we made several observations about the content available in the information environment through which individuals can learn about related concepts and products. Tweet content was consistent with the indicators of medical hype, and the inclusion of potentially misleading and untrue information was common. We identified a contingent of users with scientific and medical expertise who were active in discussing nutrigenomics concepts and products and who may be encouraged to share credible expert advice on precision nutrition and tackle false information as this technology develops.

Concept of an Intervention for Sustainable Weight Loss in Postmenopausal Women with Overweight-Secondary Analysis of a Randomized Dietary Intervention Study

INTRODUCTION

The approach of an individual diet has great potential for sustainable weight reduction. Social support, participation and empowerment are also key factors for high motivation and compliance. So, the impact of an individual diet in combination with group sessions on weight loss in postmenopausal women with overweight was investigated.

METHODS

In this reanalysis of a controlled intervention study, postmenopausal women (n = 54; BMI 30.9 ± 3.4 kg/m²; 59 ± 7 years) were recruited receiving an energy restricted diet for 12 weeks, followed by a six-month follow-up phase. The women received 51 individual meal plans based on their habits and were trained in four group sessions.

RESULTS

Forty-six women completed the intervention phase, and 29 completed the follow-up. Average weight loss was -5.8 ± 3.0 kg (p < 0.001) after 12 weeks and was still significant at follow-up (-4.9 ± 5.4 kg, p < 0.001). Also, decreases in fat-free mass (-1.1 ± 1.2 kg, p < 0.001) and resting energy expenditure (-1096 ± 439 kJ/24 h, p < 0.001) were observed.

CONCLUSIONS

The individual nutrition approach with a focus on nutritype in combination with group sessions was effective for long-lasting weight loss in postmenopausal women. An important factor is close individual and group support.

The fourth industrial revolution in the food industry-part II: Emerging food trends

The food industry has recently been under unprecedented pressure due to major global challenges, such as climate change, exponential increase in world population and urbanization, and the worldwide spread of new diseases and pandemics, such as the COVID-19. The fourth industrial revolution (Industry 4.0) has been gaining momentum since 2015 and has revolutionized the way in which food is produced, transported, stored, perceived, and consumed worldwide, leading to the emergence of new food trends. After reviewing Industry 4.0 technologies (e.g. artificial intelligence, smart sensors, robotics, blockchain, and the Internet of Things) in Part I of this work (Hassoun, Aït-Kaddour, et al. 2022. The fourth industrial revolution in the food industry-Part I: Industry 4.0 technologies. Critical Reviews in Food Science and Nutrition, 1-17.), this complimentary review will focus on emerging food trends (such as fortified and functional foods, additive manufacturing technologies, cultured meat, precision fermentation, and personalized food) and their connection with Industry 4.0 innovations. Implementation of new food trends has been associated with recent advances in Industry 4.0 technologies, enabling a range of new possibilities. The results show several positive food trends that reflect increased awareness of food chain actors of the food-related health and environmental impacts of food systems. Emergence of other food trends and higher consumer interest and engagement in the transition toward sustainable food development and innovative green strategies are expected in the future.

Understanding Choline Bioavailability and Utilization: First Step Toward Personalizing Choline Nutrition

Choline is an essential macronutrient involved in neurotransmitter synthesis, cell-membrane signaling, lipid transport, and methyl-group metabolism. Nevertheless, the vast majority are not meeting the recommended intake requirement. Choline deficiency is linked to nonalcoholic fatty liver disease, skeletal muscle atrophy, and neurodegenerative diseases. The conversion of dietary choline to trimethylamine by gut microbiota is known for its association with atherosclerosis and may contribute to choline deficiency. Choline-utilizing bacteria constitutes less than 1% of the gut community and is modulated by lifestyle interventions such as dietary patterns, antibiotics, and probiotics. In addition, choline utilization is also affected by genetic factors, further complicating the impact of choline on health. This review overviews the complex interplay between dietary intakes of choline, gut microbiota and genetic factors, and the subsequent impact on health. Understanding of gut microbiota metabolism of choline substrates and interindividual variability is warranted in the development of personalized choline nutrition.

Does Personalized Nutrition Advice Improve Dietary Intake in Healthy Adults? A Systematic Review of Randomized Controlled Trials

Personalized nutrition (PN) behavior-change interventions are being used increasingly in attempts to improve dietary intake; however, the impact of PN advice on improvements in dietary intake has not been reviewed systematically. The aim of this systematic review was to evaluate the effect of PN advice on changes in dietary intake compared with generalized advice in healthy adults. Three databases (EMBASE, PubMed, and CINAHL) were searched between 2009 and 2020 for randomized controlled trials (RCTs) that tested the effect of PN and tailored advice based on diet, phenotype, or genetic information. The Evidence Analysis Library Quality Criteria checklist was used to conduct a risk-of-bias assessment. Information on intervention design and changes in nutrients, foods, and dietary patterns was extracted from the 11 studies meeting the inclusion criteria. Studies were conducted in the United States, Canada, or Europe; reported outcomes on 57 to 1488 participants; and varied in follow-up duration from 1 to 12 mo. Five studies incorporated behavior-change techniques. The risk of bias for included studies was low. Overall, the available evidence suggests that dietary intake is improved to a greater extent in participants randomly assigned to receive PN advice compared with generalized dietary advice. Additional well-designed PN RCTs are needed that incorporate behavior-change techniques, a broader range of dietary outcomes, and comparisons between personalization based on dietary, biological, and/or lifestyle information.

Development of Personalized Nutrition: Applications in Lactose Intolerance Diagnosis and Management

Recent discoveries in the “omics” field and the growing focus on preventive health have opened new avenues for personalized nutrition (PN), which is becoming an important theme in the strategic plans of organizations that are active in healthcare, food, and nutrition research. PN holds great potential for individual health optimization, disease management, public health interventions, and product innovation. However, there are still multiple challenges to overcome before PN can be truly embraced by the public and healthcare stakeholders. The diagnosis and management of lactose intolerance (LI), a common condition with a strong inter-individual component, is explored as an interesting example for the potential role of these technologies and the challenges of PN. From the development of genetic and metabolomic LI diagnostic tests that can be carried out in the home, to advances in the understanding of LI pathology and individualized treatment optimization, PN in LI care has shown substantial progress. However, there are still many research gaps to address, including the understanding of epigenetic regulation of lactase expression and how lactose is metabolized by the gut microbiota, in order to achieve better LI detection and effective therapeutic interventions to reverse the potential health consequences of LI.

Characteristics of participants who benefit most from personalised nutrition: findings from the pan-European Food4Me randomised controlled trial

Little is known about who would benefit from Internet-based personalised nutrition (PN) interventions. This study aimed to evaluate the characteristics of participants who achieved greatest improvements (i.e. benefit) in diet, adiposity and biomarkers following an Internet-based PN intervention. Adults (n 1607) from seven European countries were recruited into a 6-month, randomised controlled trial (Food4Me) and randomised to receive conventional dietary advice (control) or PN advice. Information on dietary intake, adiposity, physical activity (PA), blood biomarkers and participant characteristics was collected at baseline and month 6. Benefit from the intervention was defined as ≥5 % change in the primary outcome (Healthy Eating Index) and secondary outcomes (waist circumference and BMI, PA, sedentary time and plasma concentrations of cholesterol, carotenoids and omega-3 index) at month 6. For our primary outcome, benefit from the intervention was greater in older participants, women and participants with lower HEI scores at baseline. Benefit was greater for individuals reporting greater self-efficacy for 'sticking to healthful foods' and who 'felt weird if [they] didn't eat healthily'. Participants benefited more if they reported wanting to improve their health and well-being. The characteristics of individuals benefiting did not differ by other demographic, health-related, anthropometric or genotypic characteristics. Findings were similar for secondary outcomes. These findings have implications for the design of more effective future PN intervention studies and for tailored nutritional advice in public health and clinical settings.