New tools for personalised nutrition: The Food4Me project

Web-Based Dietary Intake Estimation to Assess the Reproducibility and Relative Validity of the EatWellQ8 Food Frequency Questionnaire: Validation Study

BACKGROUND

The web-based EatWellQ8 food frequency questionnaire (FFQ) was developed as a dietary assessment tool for healthy adults in Kuwait. Validation against reliable instruments and assessment of its reproducibility are required to ensure the accuracy of the EatWellQ8 FFQ in computing nutrient intake.

OBJECTIVE

This study aims to assess the reproducibility and relative validity of the EatWellQ8 146-item FFQ, which included images of food portion sizes based on The Composition of Foods by McCance and Widdowson and food composition tables from Kuwait and the Kingdom of Bahrain, against a paper-based FFQ (PFFQ) and a 4-day weighed food record (WFR).

METHODS

Reproducibility of the EatWellQ8 FFQ was assessed using a test-retest methodology. Participants were required to complete the FFQ at 2 time points, 4 weeks apart. To assess the relative validity of the EatWellQ8 FFQ, a subset of the participants were asked to complete a PFFQ or a 4-day WFR 1 week after the administration of the EatWellQ8 FFQ. The level of agreement between nutrient and food group intakes was estimated by repeated EatWellQ8 FFQ administration. The EatWellQ8 FFQ, PFFQ, and 4-day WFR were also evaluated using the Bland-Altman methodology and classified into quartiles of daily intake. Crude unadjusted correlation coefficients were also calculated for nutrients and food groups.

RESULTS

A total of 99 Kuwaiti participants (64/99, 65% female and 35/99, 35% male) completed the study-53 participated in the reproducibility study and the 4-day WFR validity study (mean age 37.1 years, SD 9.9) and 46 participated in the PFFQ validity study (mean age 36.2 years, SD 8.3). Crude unadjusted correlations for repeated EatWellQ8 FFQs ranged from 0.37 to 0.93 (mean r=0.67, SD 0.14; 95% CI 0.11-0.95) for nutrients and food groups (P=.01). Mean cross-classification into exact agreement plus adjacent was 88% for nutrient intakes and 86% for food groups, and Bland-Altman plots showed good agreement for energy-adjusted macronutrient intakes. The association between the EatWellQ8 FFQ and PFFQ varied, with crude unadjusted correlations ranging from 0.42 to 0.73 (mean r=0.46, SD 0.12; 95% CI -0.02 to 0.84; P=.046). Mean cross-classification into exact agreement plus adjacent was 84% for nutrient intake and 74% for food groups. Bland-Altman plots showed moderate agreement for both energy and energy-controlled nutrient intakes. Crude unadjusted correlations for the EatWellQ8 FFQ and the 4-day WFR ranged from 0.40 to 0.88 (mean r=0.58, SD 0.13; 95% CI 0.01-0.58; P=.01). Mean cross-classification into exact agreement plus adjacent was 85% for nutrient intake and 83% for food groups. Bland-Altman plots showed moderate agreement for energy-adjusted macronutrient intakes.

CONCLUSIONS

The results indicate that the web-based EatWellQ8 FFQ is reproducible for assessing nutrient and food group intake and has moderate agreement compared with a PFFQ and a 4-day WFR for measuring energy and nutrient intakes.

Predictors of stakeholders’ intention to adopt nutrigenomics

Background

Nutrigenomics is an emerging science that studies the relationship between genes, diet and nutrients that can help prevent chronic disease. The development of this science depends on whether the public accept its application; therefore, predicting their intention to adopt it is important for its successful implementation.

Objective

This study aims to analyse Malaysian stakeholders’ intentions to adopt nutrigenomics, and determines the factors that influence their intentions.

Methods

A survey was conducted based on the responses of 421 adults (aged 18 years and older) and comprising two stakeholder groups: healthcare providers (n = 221) and patients (n = 200) who were located in the Klang Valley, Malaysia. The SPSS software was used to analyse the descriptive statistics of intention to adopt nutrigenomics and the SmartPLS software was used to determine the predicting factors affecting their decisions to adopt nutrigenomics.

Results

The results show that the stakeholders perceived the benefits of nutrigenomics as outweighing its risks, suggesting that the perceived benefits represent the most important direct predictor of the intention to adopt nutrigenomics. The perceived risks of nutrigenomics, trust in key players, engagement with medical genetics and religiosity also predict the intention to adopt nutrigenomics. Additionally, the perceived benefits of nutrigenomics served as a mediator for four factors: perceived risks of nutrigenomics, engagement with medical genetics, trust in key players and religiosity, whilst the perceived risks were a mediator for engagement with medical genetics.

Conclusion

The findings of this study suggest that the intentions of Malaysian stakeholders to adopt nutrigenomics are a complex decision-making process where all the previously mentioned factors interact. Although the results showed that the stakeholders in Malaysia were highly positive towards nutrigenomics, they were also cautious about adopting it.

Comparing environmental and personal health impacts of individual food choices

Dietary choices affect personal health and environmental impacts, but little is known about the relation between these outcomes. Here we examine the intake-related health impacts and the food-production related impacts to ecosystems and human health by applying life cycle impact assessment methods to habitual diet data of 1457 European adults. We measured food production impacts for each individual in terms of Disability Adjusted Life Years (DALYs) as calculated by the Recipe 2016 life cycle impact assessment method using secondary production data, which were then compared with their personal health DALYs predicted from the known relationships between dietary choices and disease risk. Across this population cohort, each individual was estimated to lose on average 2.5 ± 0.9 DALYs per lifetime due to sub-optimal dietary intake (with seed and vegetable under-consumption the greatest contributors) and their food choices caused environmental human health impacts of 2.4 ± 1.3 DALYs (particularly due to the damage associated with production of meats, milk, and vegetables). Overall, there was no relationship between a healthier dietary pattern and the environmental human health impacts associated with production of its constituent foods (i.e. healthier diets did not have lower or higher production impacts). This was due to a combination of decreased meat consumption correlating with increased consumption of other foods, as well as the fact that under-consumption of some low impact foods yielded high personal health consequences. However, for specific food items synergies and tradeoffs could be identified. For example, reduced processed meat consumption benefits both personal and environmental health. Every DALY caused by higher whole grain and vegetable production and consumption would be offset by reduced disease risk that equated to an average of 7.7 (5.7 to 10.4) and 1.4 (0.9 to 2.5) lower personal health DALYs, respectively.

Strategies for online personalised nutrition advice employed in the development of the eNutri web app

The internet has considerable potential to improve health-related food choice at low-cost. Online solutions in this field can be deployed quickly and at very low cost, especially if they are not dependent on bespoke devices or offline processes such as the provision and analysis of biological samples. One key challenge is the automated delivery of personalised dietary advice in a replicable, scalable and inexpensive way, using valid nutrition assessment methods and effective recommendations. We have developed a web-based personalised nutrition system (eNutri) which assesses dietary intake using a validated graphical FFQ and provides personalised food-based dietary advice automatically. Its effectiveness was evaluated during an online randomised controlled trial dietary intervention (EatWellUK study) in which personalised dietary advice was compared with general population recommendations (control) delivered online. The present paper presents a review of literature relevant to this work, and describes the strategies used during the development of the eNutri app. Its design and source code have been made publicly available under a permissive open source license, so that other researchers and organisations can benefit from this work. In a context where personalised diet advice has great potential for health promotion and disease prevention at-scale and yet is not currently being offered in the most popular mobile apps, the strategies and approaches described in the present paper can help to inform and advance the design and development of technologies for personalised nutrition.

Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome

The translation of the growing increase of findings emerging from basic nutritional science into meaningful and clinically relevant dietary advices represents nowadays one of the main challenges of clinical nutrition. From nutrigenomics to deep phenotyping, many factors need to be taken into account in designing personalized and unbiased nutritional solutions for individuals or population sub-groups. Likewise, a concerted effort among basic, clinical scientists and health professionals will be needed to establish a comprehensive framework allowing the implementation of these new findings at the population level. In a world characterized by an overwhelming increase in the prevalence of obesity and associated metabolic disturbances, such as type 2 diabetes and cardiovascular diseases, tailored nutrition prescription represents a promising approach for both the prevention and management of metabolic syndrome. This review aims to discuss recent works in the field of precision nutrition analyzing most relevant aspects affecting an individual response to lifestyle/nutritional interventions. Latest advances in the analysis and monitoring of dietary habits, food behaviors, physical activity/exercise and deep phenotyping will be discussed, as well as the relevance of novel applications of nutrigenomics, metabolomics and microbiota profiling. Recent findings in the development of precision nutrition are highlighted. Finally, results from published studies providing examples of new avenues to successfully implement innovative precision nutrition approaches will be reviewed.

Phenotypic factors influencing the variation in response of circulating cholesterol level to personalised dietary advice in the Food4Me study

Individual response to dietary interventions can be highly variable. The phenotypic characteristics of those who will respond positively to personalised dietary advice are largely unknown. The objective of this study was to compare the phenotypic profiles of differential responders to personalised dietary intervention, with a focus on total circulating cholesterol. Subjects from the Food4Me multi-centre study were classified as responders or non-responders to dietary advice on the basis of the change in cholesterol level from baseline to month 6, with lower and upper quartiles defined as responder and non-responder groups, respectively. There were no significant differences between demographic and anthropometric profiles of the groups. Furthermore, with the exception of alcohol, there was no significant difference in reported dietary intake, at baseline. However, there were marked differences in baseline fatty acid profiles. The responder group had significantly higher levels of stearic acid (18 : 0, P=0·034) and lower levels of palmitic acid (16 : 0, P=0·009). Total MUFA (P=0·016) and total PUFA (P=0·008) also differed between the groups. In a step-wise logistic regression model, age, baseline total cholesterol, glucose, five fatty acids and alcohol intakes were selected as factors that successfully discriminated responders from non-responders, with sensitivity of 82 % and specificity of 83 %. The successful delivery of personalised dietary advice may depend on our ability to identify phenotypes that are responsive. The results demonstrate the potential use of metabolic profiles in identifying response to an intervention and could play an important role in the development of precision nutrition.

Nutrient Status Assessment in Individuals and Populations for Healthy Aging-Statement from an Expert Workshop

A workshop organized by the University Medical Center Groningen addressed various current issues regarding nutrient status of individuals and populations, tools and strategies for its assessment, and opportunities to intervene. The importance of nutrient deficiencies and information on nutrient status for health has been illustrated, in particular for elderly and specific patient groups. The nutrient profile of individuals can be connected to phenotypes, like hypertension or obesity, as well as to socio-economic data. This approach provides information on the relationship between nutrition (nutrient intake and status) and health outcomes and, for instance, allows us to use the findings to communicate and advocate a healthy lifestyle. Nutrition is complex: a broader profile of nutrients should be considered rather than focusing solely on a single nutrient. Evaluating food patterns instead of intake of individual nutrients provides better insight into relationships between nutrition and health and disease. This approach would allow us to provide feedback to individuals about their status and ways to improve their nutritional habits. In addition, it would provide tools for scientists and health authorities to update and develop public health recommendations.