The perceived impact of the National Health Service on personalised nutrition service delivery among the UK public

Personalised nutrition (PN) has the potential to reduce disease risk and optimise health and performance. Although previous research has shown good acceptance of the concept of PN in the UK, preferences regarding the delivery of a PN service (e.g. online v. face-to-face) are not fully understood. It is anticipated that the presence of a free at point of delivery healthcare system, the National Health Service (NHS), in the UK may have an impact on end-user preferences for deliverances. To determine this, supplementary analysis of qualitative data obtained from focus group discussions on PN service delivery, collected as part of the Food4Me project in the UK and Ireland, was undertaken. Irish data provided comparative analysis of a healthcare system that is not provided free of charge at the point of delivery to the entire population. Analyses were conducted using the 'framework approach' described by Rabiee (Focus-group interview and data analysis. Proc Nutr Soc 63, 655-660). There was a preference for services to be led by the government and delivered face-to-face, which was perceived to increase trust and transparency, and add value. Both countries associated paying for nutritional advice with increased commitment and motivation to follow guidelines. Contrary to Ireland, however, and despite the perceived benefit of paying, UK discussants still expected PN services to be delivered free of charge by the NHS. Consideration of this unique challenge of free healthcare that is embedded in the NHS culture will be crucial when introducing PN to the UK.

How reliable is internet-based self-reported identity, socio-demographic and obesity measures in European adults?

In e-health intervention studies, there are concerns about the reliability of internet-based, self-reported (SR) data and about the potential for identity fraud. This study introduced and tested a novel procedure for assessing the validity of internet-based, SR identity and validated anthropometric and demographic data via measurements performed face-to-face in a validation study (VS). Participants (n = 140) from seven European countries, participating in the Food4Me intervention study which aimed to test the efficacy of personalised nutrition approaches delivered via the internet, were invited to take part in the VS. Participants visited a research centre in each country within 2 weeks of providing SR data via the internet. Participants received detailed instructions on how to perform each measurement. Individual’s identity was checked visually and by repeated collection and analysis of buccal cell DNA for 33 genetic variants. Validation of identity using genomic information showed perfect concordance between SR and VS. Similar results were found for demographic data (age and sex verification). We observed strong intra-class correlation coefficients between SR and VS for anthropometric data (height 0.990, weight 0.994 and BMI 0.983). However, internet-based SR weight was under-reported (Δ −0.70 kg [−3.6 to 2.1], p < 0.0001) and, therefore, BMI was lower for SR data (Δ −0.29 kg m−2 [−1.5 to 1.0], p < 0.0001). BMI classification was correct in 93 % of cases. We demonstrate the utility of genotype information for detection of possible identity fraud in e-health studies and confirm the reliability of internet-based, SR anthropometric and demographic data collected in the Food4Me study.

Predicting fatty acid profiles in blood based on food intake and the FADS1 rs174546 SNP

SCOPE: A high intake of n-3 PUFA provides health benefits via changes in the n-6/n-3 ratio in blood. In addition to such dietary PUFAs, variants in the fatty acid desaturase 1 (FADS1) gene are also associated with altered PUFA profiles. METHODS AND RESULTS: We used mathematical modelling to predict levels of PUFA in whole blood, based on MHT and bolasso selected food items, anthropometric and lifestyle factors, and the rs174546 genotypes in FADS1 from 1,607 participants (Food4Me Study). The models were developed using data from the first reported time point (training set) and their predictive power was evaluated using data from the last reported time point (test set). Amongst other food items, fish, pizza, chicken and cereals were identified as being associated with the PUFA profiles. Using these food items and the rs174546 genotypes as predictors, models explained 26% to 43% of the variability in PUFA concentrations in the training set and 22% to 33% in the test set. CONCLUSIONS: Selecting food items using MHT is a valuable contribution to determine predictors, as our models' predictive power is higher compared to analogue studies. As unique feature, we additionally confirmed our models' power based on a test set.

Making personalised nutrition the easy choice: Creating policies to break down the barriers and reap the benefits

Personalised diets based on people’s existing food choices, and/or phenotypic, and/or genetic information hold potential to improve public dietary-related health. The aim of this analysis, therefore, has been to examine the degree to which factors which determine uptake of personalised nutrition vary between EU countries to better target policies to encourage uptake, and optimise the health benefits of personalised nutrition technology. A questionnaire developed from previous qualitative research was used to survey nationally representative samples from 9 EU countries (N = 9381). Perceived barriers to the uptake of personalised nutrition comprised three factors (data protection; the eating context; and, societal acceptance). Trust in sources of information comprised four factors (commerce and media; practitioners; government; family and, friends). Benefits comprised a single factor. Analysis of Variance (ANOVA) was employed to compare differences in responses between the United Kingdom; Ireland; Portugal; Poland; Norway; the Netherlands; Germany; and, Spain. The results indicated that respondents in Greece, Poland, Ireland, Portugal and Spain, rated the benefits of personalised nutrition highest, suggesting a particular readiness in these countries to adopt personalised nutrition interventions. Greek participants were more likely to perceive the social context of eating as a barrier to adoption of personalised nutrition, implying a need for support in negotiating social situations while on a prescribed diet. Those in Spain, Germany, Portugal and Poland scored highest on perceived barriers related to data protection. Government was more trusted than commerce to deliver and provide information on personalised nutrition overall. This was particularly the case in Ireland, Portugal and Greece, indicating an imperative to build trust, particularly in the ability of commercial service providers to deliver personalised dietary regimes effectively in these countries. These findings, obtained from a nationally representative sample of EU citizens, imply that a parallel, integrated, public-private delivery system would capture the needs of most potential consumers.