Personalised nutrition advice reduces intake of discretionary foods and beverages: findings from the Food4Me randomised controlled trial.

BACKGROUND: The effect of personalised nutrition advice on discretionary foods intake is unknown. To date, two national classifications for discretionary foods have been derived. This study examined changes in intake of discretionary foods and beverages following a personalised nutrition intervention using these two classifications. METHODS: Participants were recruited into a 6-month RCT across seven European countries (Food4Me) and were randomised to receive generalised dietary advice (control) or one of three levels of personalised nutrition advice (based on diet [L1], phenotype [L2] and genotype [L3]). Dietary intake was derived from an FFQ. An analysis of covariance was used to determine intervention effects at month 6 between personalised nutrition (overall and by levels) and control on i) percentage energy from discretionary items and ii) percentage contribution of total fat, SFA, total sugars and salt to discretionary intake, defined by Food Standards Scotland (FSS) and Australian Dietary Guidelines (ADG) classifications. RESULTS: Of the 1607 adults at baseline, n = 1270 (57% female) completed the intervention. Percentage sugars from FSS discretionary items was lower in personalised nutrition vs control (19.0 ± 0.37 vs 21.1 ± 0.65; P = 0.005). Percentage energy (31.2 ± 0.59 vs 32.7 ± 0.59; P = 0.031), percentage total fat (31.5 ± 0.37 vs 33.3 ± 0.65; P = 0.021), SFA (36.0 ± 0.43 vs 37.8 ± 0.75; P = 0.034) and sugars (31.7 ± 0.44 vs 34.7 ± 0.78; P < 0.001) from ADG discretionary items were lower in personalised nutrition vs control. There were greater reductions in ADG percentage energy and percentage total fat, SFA and salt for those randomised to L3 vs L2. CONCLUSIONS: Compared with generalised dietary advice, personalised nutrition advice achieved greater reductions in discretionary foods intake when the classification included all foods high in fat, added sugars and salt. Future personalised nutrition approaches may be used to target intake of discretionary foods. TRIAL REGISTRATION: Clinicaltrials.gov NCT01530139 . Registered 9 February 2012.

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.

Higher vegetable protein consumption, assessed by an isoenergetic macronutrient exchange model, is associated with a lower presence of overweight and obesity in the web-based Food4me European study.

The objective was to evaluate differences in macronutrient intake and to investigate the possible association between consumption of vegetable protein and the risk of overweight/obesity, within the Food4Me randomised, online intervention. Differences in macronutrient consumption among the participating countries grouped by EU Regions (Western Europe, British Isles, Eastern Europe and Southern Europe) were assessed. Relation of protein intake, within isoenergetic exchange patterns, from vegetable or animal sources with risk of overweight/obesity was assessed through the multivariate nutrient density model and a multivariate-adjusted logistic regression. A total of 2413 subjects who completed the Food4Me screening were included, with self-reported data on age, weight, height, physical activity and dietary intake. As success rates on reducing overweight/obesity are very low, form a public health perspective, the elaboration of policies for increasing intakes of vegetable protein and reducing animal protein and sugars, may be a method of combating overweight/obesity at a population level.

Food choice motives, attitude towards and intention to adopt personalised nutrition.

OBJECTIVE: The present study explored associations between food choice motives, attitudes towards and intention to adopt personalised nutrition, to inform communication strategies based on consumer priorities and concerns.Design/SettingA survey was administered online which included the Food Choice Questionnaire (FCQ) and items assessing attitudes towards and intention to adopt personalised nutrition. SUBJECTS: Nationally representative samples were recruited in nine EU countries (n 9381). RESULTS: Structural equation modelling indicated that the food choice motives 'weight control', 'mood', 'health' and 'ethical concern' had a positive association and 'price' had a negative association with attitude towards, and intention to adopt, personalised nutrition. 'Health' was positively associated and 'familiarity' negatively associated with attitude towards personalised nutrition. The effects of 'weight control', 'ethical concern', 'mood' and 'price' on intention to adopt personalised nutrition were partially mediated by attitude. The effects of 'health' and 'familiarity' were fully mediated by attitude. 'Sensory appeal' was negatively and directly associated with intention to adopt personalised nutrition. CONCLUSIONS: Personalised nutrition providers may benefit from taking into consideration the importance of underlying determinants of food choice in potential users, particularly weight control, mood and price, when promoting services and in tailoring communications that are motivationally relevant.

Capturing health and eating status through a nutritional perception screening questionnaire (NPSQ9) in a randomised internet-based personalised nutrition intervention: the Food4Me study.

BACKGROUND: National guidelines emphasize healthy eating to promote wellbeing and prevention of non-communicable diseases. The perceived healthiness of food is determined by many factors affecting food intake. A positive perception of healthy eating has been shown to be associated with greater diet quality. Internet-based methodologies allow contact with large populations. Our present study aims to design and evaluate a short nutritional perception questionnaire, to be used as a screening tool for assessing nutritional status, and to predict an optimal level of personalisation in nutritional advice delivered via the Internet. METHODS: Data from all participants who were screened and then enrolled into the Food4Me proof-of-principle study (n = 2369) were used to determine the optimal items for inclusion in a novel screening tool, the Nutritional Perception Screening Questionnaire-9 (NPSQ9). Exploratory and confirmatory factor analyses were performed on anthropometric and biochemical data and on dietary indices acquired from participants who had completed the Food4Me dietary intervention (n = 1153). Baseline and intervention data were analysed using linear regression and linear mixed regression, respectively. RESULTS: A final model with 9 NPSQ items was validated against the dietary intervention data. NPSQ9 scores were inversely associated with BMI (ß = -0.181, p < 0.001) and waist circumference (Β = -0.155, p < 0.001), and positively associated with total carotenoids (ß = 0.198, p < 0.001), omega-3 fatty acid index (ß = 0.155, p < 0.001), Healthy Eating Index (HEI) (ß = 0.299, p < 0.001) and Mediterranean Diet Score (MDS) (ß = 0. 279, p < 0.001). Findings from the longitudinal intervention study showed a greater reduction in BMI and improved dietary indices among participants with lower NPSQ9 scores. CONCLUSIONS: Healthy eating perceptions and dietary habits captured by the NPSQ9 score, based on nine questionnaire items, were associated with reduced body weight and improved diet quality. Likewise, participants with a lower score achieved greater health improvements than those with higher scores, in response to personalised advice, suggesting that NPSQ9 may be used for early evaluation of nutritional status and to tailor nutritional advice. TRIAL REGISTRATION: NCT01530139 .

Characteristics of European adults who dropped out from the Food4Me Internet-based personalised nutrition intervention.

OBJECTIVE: To characterise participants who dropped out of the Food4Me Proof-of-Principle study. DESIGN: The Food4Me study was an Internet-based, 6-month, four-arm, randomised controlled trial. The control group received generalised dietary and lifestyle recommendations, whereas participants randomised to three different levels of personalised nutrition (PN) received advice based on dietary, phenotypic and/or genotypic data, respectively (with either more or less frequent feedback). SETTING: Seven recruitment sites: UK, Ireland, The Netherlands, Germany, Spain, Poland and Greece. SUBJECTS: Adults aged 18-79 years (n 1607). RESULTS: A total of 337 (21 %) participants dropped out during the intervention. At baseline, dropouts had higher BMI (0·5 kg/m2; P<0·001). Attrition did not differ significantly between individuals receiving generalised dietary guidelines (Control) and those randomised to PN. Participants were more likely to drop out (OR; 95 % CI) if they received more frequent feedback (1·81; 1·36, 2·41; P<0·001), were female (1·38; 1·06, 1·78; P=0·015), less than 45 years old (2·57; 1·95, 3·39; P<0·001) and obese (2·25; 1·47, 3·43; P<0·001). Attrition was more likely in participants who reported an interest in losing weight (1·53; 1·19, 1·97; P<0·001) or skipping meals (1·75; 1·16, 2·65; P=0·008), and less likely if participants claimed to eat healthily frequently (0·62; 0·45, 0·86; P=0·003). CONCLUSIONS: Attrition did not differ between participants receiving generalised or PN advice but more frequent feedback was related to attrition for those randomised to PN interventions. Better strategies are required to minimise dropouts among younger and obese individuals participating in PN interventions and more frequent feedback may be an unnecessary burden.

Application of dried blood spots to determine vitamin D status in a large nutritional study with unsupervised sampling: the Food4Me project.

An efficient and robust method to measure vitamin D (25-hydroxy vitamin D3 (25(OH)D3) and 25-hydroxy vitamin D2 in dried blood spots (DBS) has been developed and applied in the pan-European multi-centre, internet-based, personalised nutrition intervention study Food4Me. The method includes calibration with blood containing endogenous 25(OH)D3, spotted as DBS and corrected for haematocrit content. The methodology was validated following international standards. The performance characteristics did not reach those of the current gold standard liquid chromatography-MS/MS in plasma for all parameters, but were found to be very suitable for status-level determination under field conditions. DBS sample quality was very high, and 3778 measurements of 25(OH)D3 were obtained from 1465 participants. The study centre and the season within the study centre were very good predictors of 25(OH)D3 levels (P<0·001 for each case). Seasonal effects were modelled by fitting a sine function with a minimum 25(OH)D3 level on 20 January and a maximum on 21 July. The seasonal amplitude varied from centre to centre. The largest difference between winter and summer levels was found in Germany and the smallest in Poland. The model was cross-validated to determine the consistency of the predictions and the performance of the DBS method. The Pearson's correlation between the measured values and the predicted values was r 0·65, and the sd of their differences was 21·2 nmol/l. This includes the analytical variation and the biological variation within subjects. Overall, DBS obtained by unsupervised sampling of the participants at home was a viable methodology for obtaining vitamin D status information in a large nutritional study.

A Dietary Feedback System for the Delivery of Consistent Personalized Dietary Advice in the Web-Based Multicenter Food4Me Study.

BACKGROUND: Despite numerous healthy eating campaigns, the prevalence of diets high in saturated fatty acids, sugar, and salt and low in fiber, fruit, and vegetables remains high. With more people than ever accessing the Internet, Web-based dietary assessment instruments have the potential to promote healthier dietary behaviors via personalized dietary advice. OBJECTIVE: The objectives of this study were to develop a dietary feedback system for the delivery of consistent personalized dietary advice in a multicenter study and to examine the impact of automating the advice system. METHODS: The development of the dietary feedback system included 4 components: (1) designing a system for categorizing nutritional intakes; (2) creating a method for prioritizing 3 nutrient-related goals for subsequent targeted dietary advice; (3) constructing decision tree algorithms linking data on nutritional intake to feedback messages; and (4) developing personal feedback reports. The system was used manually by researchers to provide personalized nutrition advice based on dietary assessment to 369 participants during the Food4Me randomized controlled trial, with an automated version developed on completion of the study. RESULTS: Saturated fatty acid, salt, and dietary fiber were most frequently selected as nutrient-related goals across the 7 centers. Average agreement between the manual and automated systems, in selecting 3 nutrient-related goals for personalized dietary advice across the centers, was highest for nutrient-related goals 1 and 2 and lower for goal 3, averaging at 92%, 87%, and 63%, respectively. Complete agreement between the 2 systems for feedback advice message selection averaged at 87% across the centers. CONCLUSIONS: The dietary feedback system was used to deliver personalized dietary advice within a multi-country study. Overall, there was good agreement between the manual and automated feedback systems, giving promise to the use of automated systems for personalizing dietary advice. TRIAL REGISTRATION: Clinicaltrials.gov NCT01530139; https://clinicaltrials.gov/ct2/show/NCT01530139 (Archived by WebCite at http://www.webcitation.org/6ht5Dgj8I).

Online dietary intake estimation: reproducibility and validity of the Food4Me food frequency questionnaire against a 4-day weighed food record.

BACKGROUND: Advances in nutritional assessment are continuing to embrace developments in computer technology. The online Food4Me food frequency questionnaire (FFQ) was created as an electronic system for the collection of nutrient intake data. To ensure its accuracy in assessing both nutrient and food group intake, further validation against data obtained using a reliable, but independent, instrument and assessment of its reproducibility are required. OBJECTIVE: The aim was to assess the reproducibility and validity of the Food4Me FFQ against a 4-day weighed food record (WFR). METHODS: Reproducibility of the Food4Me FFQ was assessed using test-retest methodology by asking participants to complete the FFQ on 2 occasions 4 weeks apart. To assess the validity of the Food4Me FFQ against the 4-day WFR, half the participants were also asked to complete a 4-day WFR 1 week after the first administration of the Food4Me FFQ. Level of agreement between nutrient and food group intakes estimated by the repeated Food4Me FFQ and the Food4Me FFQ and 4-day WFR were evaluated using Bland-Altman methodology and classification into quartiles of daily intake. Crude unadjusted correlation coefficients were also calculated for nutrient and food group intakes. RESULTS: In total, 100 people participated in the assessment of reproducibility (mean age 32, SD 12 years), and 49 of these (mean age 27, SD 8 years) also took part in the assessment of validity. Crude unadjusted correlations for repeated Food4Me FFQ ranged from .65 (vitamin D) to .90 (alcohol). The mean cross-classification into "exact agreement plus adjacent" was 92% for both nutrient and food group intakes, and Bland-Altman plots showed good agreement for energy-adjusted macronutrient intakes. Agreement between the Food4Me FFQ and 4-day WFR varied, with crude unadjusted correlations ranging from .23 (vitamin D) to .65 (protein, % total energy) for nutrient intakes and .11 (soups, sauces and miscellaneous foods) to .73 (yogurts) for food group intake. The mean cross-classification into "exact agreement plus adjacent" was 80% and 78% for nutrient and food group intake, respectively. There were no significant differences between energy intakes estimated using the Food4Me FFQ and 4-day WFR, and Bland-Altman plots showed good agreement for both energy and energy-controlled nutrient intakes. CONCLUSIONS: The results demonstrate that the online Food4Me FFQ is reproducible for assessing nutrient and food group intake and has moderate agreement with the 4-day WFR for assessing energy and energy-adjusted nutrient intakes. The Food4Me FFQ is a suitable online tool for assessing dietary intake in healthy adults.

Online dietary intake estimation: the Food4Me food frequency questionnaire.

BACKGROUND: Dietary assessment methods are important tools for nutrition research. Online dietary assessment tools have the potential to become invaluable methods of assessing dietary intake because, compared with traditional methods, they have many advantages including the automatic storage of input data and the immediate generation of nutritional outputs. OBJECTIVE: The aim of this study was to develop an online food frequency questionnaire (FFQ) for dietary data collection in the "Food4Me" study and to compare this with the validated European Prospective Investigation of Cancer (EPIC) Norfolk printed FFQ. METHODS: The Food4Me FFQ used in this analysis was developed to consist of 157 food items. Standardized color photographs were incorporated in the development of the Food4Me FFQ to facilitate accurate quantification of the portion size of each food item. Participants were recruited in two centers (Dublin, Ireland and Reading, United Kingdom) and each received the online Food4Me FFQ and the printed EPIC-Norfolk FFQ in random order. Participants completed the Food4Me FFQ online and, for most food items, participants were requested to choose their usual serving size among seven possibilities from a range of portion size pictures. The level of agreement between the two methods was evaluated for both nutrient and food group intakes using the Bland and Altman method and classification into quartiles of daily intake. Correlations were calculated for nutrient and food group intakes. RESULTS: A total of 113 participants were recruited with a mean age of 30 (SD 10) years (40.7% male, 46/113; 59.3%, 67/113 female). Cross-classification into exact plus adjacent quartiles ranged from 77% to 97% at the nutrient level and 77% to 99% at the food group level. Agreement at the nutrient level was highest for alcohol (97%) and lowest for percent energy from polyunsaturated fatty acids (77%). Crude unadjusted correlations for nutrients ranged between .43 and .86. Agreement at the food group level was highest for "other fruits" (eg, apples, pears, oranges) and lowest for "cakes, pastries, and buns". For food groups, correlations ranged between .41 and .90. CONCLUSIONS: The results demonstrate that the online Food4Me FFQ has good agreement with the validated printed EPIC-Norfolk FFQ for assessing both nutrient and food group intakes, rendering it a useful tool for ranking individuals based on nutrient and food group intakes.

Paving the way to better population health through personalised nutrition.

As each individual person differs from the next in multiple ways, it is a beguiling idea that our individual nutritional needs also differ. In support of this idea, findings from nutritional intervention studies provide ample evidence of considerable interindividual variation in response to the same dietary exposure. We have a limited understanding of the mechanisms responsible for this variation but, following sequencing of the human genome, the role of genes in explaining interindividual differences has been centre stage. In addition, evidence of diet-gene interactions that influence phenotype, including health, emphasises the importance of both nature and nurture. Eating patterns are major determinants of health, so public health advice to reduce the risk of common complex diseases focuses on diet. However, most dietary interventions are relatively ineffective and personalised approaches that tailor the intervention to the individual may be more acceptable and more effective. That idea was tested in the Food4Me study in which adults from seven European countries were randomised to one of four treatment groups in an internet-delivered dietary intervention. Compared with the Control (standardised healthy eating advice), those people randomised to a personalised nutrition intervention had bigger, sustained changes, in eating behaviour after 6 months. However, including more complex phenotypic and/or genotypic information in developing the personalised nutrition advice had no added benefit. Research in personalised nutrition is broadening its scope to consider effects mediated by the gut microbiome as well as multiple aspects of genotype and phenotype. Such research has the potential to explain interindividual differences in the response to specific dietary factors and may provide a scientific basis for more refined approaches to personalised nutrition. However, if this research is to make a significant contribution to improving public health, it will need to address the psychological, social, economic and cultural factors that influence eating patterns to ensure that advice is converted into action and that improved dietary habits are sustained in perpetuity.

Analysis of the National Adult Nutrition Survey (Ireland) and the Food4Me Nutrition Survey Databases to Explore the Development of Food Labelling Portion Sizes for the European Union.

The present study set out to explore the option of developing food portion size for nutritional labelling purposes using two European Union (EU) dietary surveys. The surveys were selected as they differed in (a) methodologies (food diary versus food frequency questionnaire), (b) populations (Irish National Adult Nutrition Survey (NANS) versus a seven-country survey based on the pan EU study Food4Me), (c) food quantification (multiple options versus solely photographic album) and (d) duration (4 consecutive days versus recent month). Using data from these studies, portion size was determined for 15 test foods, where portion size was defined as the median intake of a target food when consumed. The median values of the portion sizes derived from both the NANS and Food4Me surveys were correlated (r = 0.823; p < 0.00) and the mean of the two survey data sets were compared to US values from the Recognized as Customarily Consumed (RACC) database. There was very strong agreement across all food categories between the averaged EU and the US portion size (r = 0.947; p < 0.00). It is concluded that notwithstanding the variety of approaches used for dietary survey data in the EU, the present data supports using a standardized approach to food portion size quantification for food labelling in the EU.

Mediterranean Diet Adherence and Genetic Background Roles within a Web-Based Nutritional Intervention: The Food4Me Study.

Mediterranean Diet (MedDiet) adherence has been proven to produce numerous health benefits. In addition, nutrigenetic studies have explained some individual variations in the response to specific dietary patterns. The present research aimed to explore associations and potential interactions between MedDiet adherence and genetic background throughout the Food4Me web-based nutritional intervention. Dietary, anthropometrical and biochemical data from volunteers of the Food4Me study were collected at baseline and after 6 months. Several genetic variants related to metabolic risk features were also analysed. A Genetic Risk Score (GRS) was derived from risk alleles and a Mediterranean Diet Score (MDS), based on validated food intake data, was estimated. At baseline, there were no interactions between GRS and MDS categories for metabolic traits. Linear mixed model repeated measures analyses showed a significantly greater decrease in total cholesterol in participants with a low GRS after a 6-month period, compared to those with a high GRS. Meanwhile, a high baseline MDS was associated with greater decreases in Body Mass Index (BMI), waist circumference and glucose. There also was a significant interaction between GRS and the MedDiet after the follow-up period. Among subjects with a high GRS, those with a high MDS evidenced a highly significant reduction in total carotenoids, while among those with a low GRS, there was no difference associated with MDS levels. These results suggest that a higher MedDiet adherence induces beneficial effects on metabolic outcomes, which can be affected by the genetic background in some specific markers.

Public perceptions of personalised nutrition through the lens of Social Cognitive Theory.

Social Cognitive Theory has been used to explain findings derived from focus group discussions ( N = 4) held in the United Kingdom with the aim of informing best practice in personalised nutrition. Positive expectancies included weight loss and negative expectancies surrounded on-line security. Monitoring and feedback were crucial to goal setting and progress. Coaching by the service provider, family and friends was deemed important for self-efficacy. Paying for personalised nutrition symbolised commitment to behaviour change. The social context of eating, however, was perceived a problem and should be considered when designing personalised diets. Social Cognitive Theory could provide an effective framework through which to deliver personalised nutrition.

Weekday sunlight exposure, but not vitamin D intake, influences the association between vitamin D receptor genotype and circulating concentration 25-hydroxyvitamin D in a pan-European population: the Food4Me study.

SCOPE: Little is known about diet- and environment-gene interactions on 25-hydroxyvitamin D (25(OH)D concentration. This cross-sectional study aimed to investigate (i) predictors of 25(OH)D concentration and relationships with vitamin D genotypes and (ii) whether dietary vitamin D intake and sunlight exposure modified these relationships. METHODS AND RESULTS: Participants from the Food4Me study (n = 1312; age 18-79) were genotyped for vitamin D receptor (VDR) and vitamin D binding protein at baseline and a genetic risk score was calculated. Dried blood spot samples were assayed for 25(OH)D concentration and dietary and lifestyle information collected. Circulating 25(OH)D concentration was lower with increasing genetic risk score, lower in females than males, higher in supplement users than non-users and higher in summer than winter. Carriage of the minor VDR allele was associated with lower 25(OH)D concentration in participants with the least sunlight exposure. Vitamin D genotype did not influence the relationship between vitamin D intake and 25(OH)D concentration. CONCLUSION: Age, sex, dietary vitamin D intake, country, sunlight exposure, season, and vitamin D genetic risk score were associated with circulating 25(OH)D concentration in a pan-European population. The relationship between VDR genotype and 25(OH)D concentration may be influenced by weekday sunlight exposure but not dietary vitamin D intake.

Providing Personalised Nutrition: Consumers' Trust and Preferences Regarding Sources of Information, Service Providers and Regulators, and Communication Channels.

BACKGROUND/AIMS: Personalised nutrition has potential to revolutionise dietary health promotion if accepted by the general public. We studied trust and preferences regarding personalised nutrition services, how they influence intention to adopt these services, and cultural and social differences therein. METHODS: A total of 9,381 participants were quota-sampled to be representative of each of 9 EU countries (Germany, Greece, Ireland, Poland, Portugal, Spain, the Netherlands, the UK, and Norway) and surveyed by a questionnaire assessing their intention to adopt personalised nutrition, trust in service regulators and information sources, and preferences for service providers and information channels. RESULTS: Trust and preferences significantly predicted intention to adopt personalised nutrition. Higher trust in the local department of health care was associated with lower intention to adopt personalised nutrition. General practitioners were the most trusted of service regulators, except in Portugal, where consumer organisations and universities were most trusted. In all countries, family doctors were the most trusted information providers. Trust in the National Health Service as service regulator and information source showed high variability across countries. Despite its highest variability across countries, personal meeting was the preferred communication channel, except in Spain, where an automated internet service was preferred. General practitioners were the preferred service providers, except in Poland, where dietitians and nutritionists were preferred. The preference for dietitians and nutritionists as service providers highly varied across countries. CONCLUSION: These results may assist in informing local initiatives to encourage acceptance and adoption of country-specific tailored personalised nutrition services, therefore benefiting individual and public health.

Knowing your genes: does this impact behaviour change?

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.

The effect of the apolipoprotein E genotype on response to personalized dietary advice intervention: findings from the Food4Me randomized controlled trial.

BACKGROUND: The apolipoprotein E (APOE) risk allele (ɛ4) is associated with higher total cholesterol (TC), amplified response to saturated fatty acid (SFA) reduction, and increased cardiovascular disease. Although knowledge of gene risk may enhance dietary change, it is unclear whether ɛ4 carriers would benefit from gene-based personalized nutrition (PN). OBJECTIVES: The aims of this study were to 1) investigate interactions between APOE genotype and habitual dietary fat intake and modulations of fat intake on metabolic outcomes; 2) determine whether gene-based PN results in greater dietary change than do standard dietary advice (level 0) and nongene-based PN (levels 1-2); and 3) assess the impact of knowledge of APOE risk (risk: E4+, nonrisk: E4-) on dietary change after gene-based PN (level 3). DESIGN: Individuals (n = 1466) recruited into the Food4Me pan-European PN dietary intervention study were randomly assigned to 4 treatment arms and genotyped for APOE (rs429358 and rs7412). Diet and dried blood spot TC and ω-3 (n-3) index were determined at baseline and after a 6-mo intervention. Data were analyzed with the use of adjusted general linear models. RESULTS: Significantly higher TC concentrations were observed in E4+ participants than in E4- (P < 0.05). Although there were no significant differences in APOE response to gene-based PN (E4+ compared with E4-), both groups had a greater reduction in SFA (percentage of total energy) intake than at level 0 (mean ± SD: E4+, -0.72% ± 0.35% compared with -1.95% ± 0.45%, P = 0.035; E4-, -0.31% ± 0.20% compared with -1.68% ± 0.35%, P = 0.029). Gene-based PN was associated with a smaller reduction in SFA intake than in nongene-based PN (level 2) for E4- participants (-1.68% ± 0.35% compared with -2.56% ± 0.27%, P = 0.025). CONCLUSIONS: The APOE ɛ4 allele was associated with higher TC. Although gene-based PN targeted to APOE was more effective in reducing SFA intake than standard dietary advice, there was no difference between APOE "risk" and "nonrisk" groups. Furthermore, disclosure of APOE nonrisk may have weakened dietary response to PN. This trial was registered at clinicaltrials.gov as NCT01530139.

Effect of an Internet-based, personalized nutrition randomized trial on dietary changes associated with the Mediterranean diet: the Food4Me Study.

BACKGROUND: Little is known about the efficacy of personalized nutrition (PN) interventions for improving consumption of a Mediterranean diet (MedDiet). OBJECTIVE: The objective was to evaluate the effect of a PN intervention on dietary changes associated with the MedDiet. DESIGN: Participants (n = 1607) were recruited into a 6-mo, Internet-based, PN randomized controlled trial (Food4Me) designed to evaluate the effect of PN on dietary change. Participants were randomly assigned to receive conventional dietary advice [control; level 0 (L0)] or PN advice on the basis of current diet [level 1 (L1)], diet and phenotype [level 2 (L2)], or diet, phenotype, and genotype [level 3 (L3)]. Dietary intakes from food-frequency questionnaires at baseline and at 6 mo were converted to a MedDiet score. Linear regression compared participant characteristics between high (>5) and low (≤5) MedDiet scores. Differences in MedDiet scores between treatment arms at month 6 were evaluated by using contrast analyses. RESULTS: At baseline, high MedDiet scorers had a 0.5 lower body mass index (in kg/m(2); P = 0.007) and a 0.03 higher physical activity level (P = 0.003) than did low scorers. MedDiet scores at month 6 were greater in individuals randomly assigned to receive PN (L1, L2, and L3) than in controls (PN compared with controls: 5.20 ± 0.05 and 5.48 ± 0.07, respectively; P = 0.002). There was no significant difference in MedDiet scores at month 6 between PN advice on the basis of L1 compared with L2 and L3. However, differences in MedDiet scores at month 6 were greater in L3 than in L2 (L3 compared with L2: 5.63 ± 0.10 and 5.38 ± 0.10, respectively; P = 0.029). CONCLUSIONS: Higher MedDiet scores at baseline were associated with healthier lifestyles and lower adiposity. After the intervention, MedDiet scores were greater in individuals randomly assigned to receive PN than in controls, with the addition of DNA-based dietary advice resulting in the largest differences in MedDiet scores. Although differences were significant, their clinical relevance is modest. This trial was registered at clinicaltrials.gov as NCT01530139.

Promoting healthy dietary behaviour through personalised nutrition: technology push or technology pull?

The notion of educating the public through generic healthy eating messages has pervaded dietary health promotion efforts over the years and continues to do so through various media, despite little evidence for any enduring impact upon eating behaviour. There is growing evidence, however, that tailored interventions such as those that could be delivered online can be effective in bringing about healthy dietary behaviour change. The present paper brings together evidence from qualitative and quantitative studies that have considered the public perspective of genomics, nutrigenomics and personalised nutrition, including those conducted as part of the EU-funded Food4Me project. Such studies have consistently indicated that although the public hold positive views about nutrigenomics and personalised nutrition, they have reservations about the service providers' ability to ensure the secure handling of health data. Technological innovation has driven the concept of personalised nutrition forward and now a further technological leap is required to ensure the privacy of online service delivery systems and to protect data gathered in the process of designing personalised nutrition therapies.