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/m2; 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

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

Effects of a web-based personalized intervention on physical activity in European adults: a randomized controlled trial

Background: The high prevalence of physical inactivity worldwide calls for innovative and more effective ways to promote physical activity (PA). There are limited objective data on the effectiveness of Web-based personalized feedback on increasing PA in adults. Objective: It is hypothesized that providing personalized advice based on PA measured objectively alongside diet, phenotype, or genotype information would lead to larger and more sustained changes in PA, compared with nonpersonalized advice. Methods: A total of 1607 adults in seven European countries were randomized to either a control group (nonpersonalized advice, Level 0, L0) or to one of three personalized groups receiving personalized advice via the Internet based on current PA plus diet (Level 1, L1), PA plus diet and phenotype (Level 2, L2), or PA plus diet, phenotype, and genotype (Level 3, L3). PA was measured for 6 months using triaxial accelerometers, and self-reported using the Baecke questionnaire. Outcomes were objective and self-reported PA after 3 and 6 months. Results: While 1270 participants (85.81% of 1480 actual starters) completed the 6-month trial, 1233 (83.31%) self-reported PA at both baseline and month 6, but only 730 (49.32%) had sufficient objective PA data at both time points. For the total cohort after 6 months, a greater improvement in self-reported total PA (P=.02) and PA during leisure (nonsport) (P=.03) was observed in personalized groups compared with the control group. For individuals advised to increase PA, we also observed greater improvements in those two self-reported indices (P=.006 and P=.008, respectively) with increased personalization of the advice (L2 and L3 vs L1). However, there were no significant differences in accelerometer results between personalized and control groups, and no significant effect of adding phenotypic or genotypic information to the tailored feedback at month 3 or 6. After 6 months, there were small but significant improvements in the objectively measured physical activity level (P<.05), moderate PA (P<.01), and sedentary time (P<.001) for individuals advised to increase PA, but these changes were similar across all groups. Conclusions: Different levels of personalization produced similar small changes in objective PA. We found no evidence that personalized advice is more effective than conventional “one size fits all” guidelines to promote changes in PA in our Web-based intervention when PA was measured objectively. Based on self-reports, PA increased to a greater extent with more personalized advice. Thus, it is crucial to measure PA objectively in any PA intervention study

Changes in physical activity following a genetic-based internet-delivered personalized intervention: randomized controlled trial (Food4Me)

Background: There is evidence that physical activity (PA) can attenuate the influence of the fat mass- and obesity-associated (FTO) genotype on the risk to develop obesity. However, whether providing personalized information on FTO genotype leads to changes in PA is unknown. Objective: The purpose of this study was to determine if disclosing FTO risk had an impact on change in PA following a 6-month intervention. Methods: The single nucleotide polymorphism (SNP) rs9939609 in the FTO gene was genotyped in 1279 participants of the Food4Me study, a four-arm, Web-based randomized controlled trial (RCT) in 7 European countries on the effects of personalized advice on nutrition and PA. PA was measured objectively using a TracmorD accelerometer and was self-reported using the Baecke questionnaire at baseline and 6 months. Differences in baseline PA variables between risk (AA and AT genotypes) and nonrisk (TT genotype) carriers were tested using multiple linear regression. Impact of FTO risk disclosure on PA change at 6 months was assessed among participants with inadequate PA, by including an interaction term in the model: disclosure (yes/no) × FTO risk (yes/no). Results: At baseline, data on PA were available for 874 and 405 participants with the risk and nonrisk FTO genotypes, respectively. There were no significant differences in objectively measured or self-reported baseline PA between risk and nonrisk carriers. A total of 807 (72.05%) of the participants out of 1120 in the personalized groups were encouraged to increase PA at baseline. Knowledge of FTO risk had no impact on PA in either risk or nonrisk carriers after the 6-month intervention. Attrition was higher in nonrisk participants for whom genotype was disclosed (P=.01) compared with their at-risk counterparts. Conclusions: No association between baseline PA and FTO risk genotype was observed. There was no added benefit of disclosing FTO risk on changes in PA in this personalized intervention. Further RCT studies are warranted to confirm whether disclosure of nonrisk genetic test results has adverse effects on engagement in behavior change

Frequent nutritional feedback, personalized advice, and behavioral changes: findings from the European Food4Me internet-based RCT

Introduction: This study tested the hypothesis that providing personalized nutritional advice and feedback more frequently would promote larger, more appropriate, and sustained changes in dietary behavior as well as greater reduction in adiposity. Study design: A 6-month RCT (Food4Me) was conducted in seven European countries between 2012 and 2013. Setting/participants: A total of 1,125 participants were randomized to Lower- (n=562) or Higher- (n=563) Frequency Feedback groups. Participants in the Lower-Frequency group received personalized nutritional advice at baseline and at Months 3 and 6 of the intervention, whereas the Higher-Frequency group received personalized nutritional advice at baseline and at Months 1, 2, 3 and 6. Main outcome measures: The primary outcomes were change in dietary intake (at food and nutrient levels) and obesity-related traits (body weight, BMI, and waist circumference). Participants completed an online food frequency questionnaire to estimate usual dietary intake at baseline and at Months 3 and 6 of the intervention. Overall diet quality was evaluated using the 2010 Healthy Eating Index. Obesity-related traits were self-measured and reported by participant via the Internet. Statistical analyses were performed during the first quarter of 2018. Results: At 3 months, participants in the Lower- and Higher-Frequency Feedback groups showed improvements in Healthy Eating Index score; this improvement was larger in the Higher-Frequency group than the Lower-Frequency group (=1.84, 95% CI=0.79, 2.89, p=0.0001). Similarly, there were greater improvements for the Higher- versus Lower-Frequency group for body weight (= –0.73 kg, 95% CI= –1.07, –0.38, p<0.0001), BMI (= –0.24 kg, 95% CI= –0.36, –0.13, p<0.0001), and waist circumference (= –1.20 cm, 95% CI= –2.36, –0.04, p=0.039). However, only body weight and BMI remained significant at 6 months. Conclusions: At 3 months, higher-frequency feedback produced larger improvements in overall diet quality as well as in body weight and waist circumference compared with lower-frequency feedback. However, only body weight and BMI remained significant at 6 months. Trial registration: Clinicaltrials.gov, NCT01530139

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

Corrigendum : Clustering of adherence to personalised dietary recommendations and changes in healthy eating index within the Food4Me study (Public Health Nutrition 19:18 (3296-305) DOI: 10.1017/S1368980016001932)

© The Authors 2019.Original text and corrections: ORIGINAL TEXT (page 3296, Abstract) Subjects: Adults aged 18-79 years (n 1480). CORRECTION Subjects: Adults aged 18-79 years at baseline (n 1480). ORIGINAL TEXT (page 3298, Results) Of the 5562 individuals who registered on the Food4Me website, 1607 were randomised into the study and a total of 1480 provided baseline data on dietary intakes(17). CORRECTION Of the 5562 individuals who registered on the Food4Me website, 1607 were randomised into the study. A total of 1480 participants provided baseline data on dietary intakes (15). Following exclusion of missing data for covariates the baseline sample was 1285. A total of 1147 participants provided complete follow up data. ORIGINAL TEXT (page 3300, Results) There were no significant differences in changes in HEI between clusters when PN was stratified by Level 1, Level 2 or Level 3 (data not shown). CORRECTION The results for when PN was stratified by L1, L2 or L3 are presented in Supplementary Table 5. For participants in L2, there were bigger improvements in HEI for participants in C4 compared with C1 (P <0.001) and in C3 and C2 compared with C1 (<0.05). For participants in L3, there were bigger improvements in HEI for participants in C4 compared with C1 and C2 (P<0.05) (Supplementary Table 5). There were no significant differences for participants in L1. ORIGINAL TEXT (page 3300, Results) Exclusion of participants with reported intakes more than 3 SD above or below the mean dietary intakes of whole grains, oily fish, red meat and fruit and vegetables revealed similar clusters (see online supplementary material, Supplemental Table 5).CORRECTION Exclusion of participants with reported intakes more than 3 SD above or below the mean dietary intakes of wholegrain, oily fish, red meat and fruit and vegetables revealed similar clusters (Supplementary Table 6). ORIGINAL TEXT (page 3302, Discussion) We observed that individuals in the cluster where the fewest recommendations were met (C4) reported the biggest improvement in HEI following PN intervention but there were no differences between clusters in response to conventional, non-personalised dietary advice. CORRECTION We observed that individuals in the cluster where the fewest recommendations were met (C4) reported the biggest improvement in HEI following PN intervention. ORIGINAL TEXT (page 3302, Discussion) Fig. 1 Changes from baseline to month 6 in Healthy Eating Index 2010 (HEI) score by cluster of adherence to dietary recommendations at baseline among adults aged 18-79 years (n 1480), Food4Me study. CORRECTION Figure 1 Changes from baseline to month 6 in Healthy Eating Index by clusters of adherence to recommendations at baseline among adults aged 18-79 years (n 1,147), Food4Me study. ORIGINAL TEXT (page 3300, Results) Table needed CORRECTION Table 1 Food and nutrient and intakes by participants by clusters of adherence to recommendations at baseline among adults aged 18-79 years (n 1285), Food4Me study (Table Presented).Peer reviewe

Reproducibility of the Online Food4Me Food-Frequency Questionnaire for Estimating Dietary Intakes across Europe

Accurate dietary assessment is key to understanding nutrition-related outcomes and is essential for estimating dietary change in nutrition-based interventions. Objective: The objective of this study was to assess the pan-European reproducibility of the Food4Me food-frequency questionnaire (FFQ) in assessing the habitual diet of adults. Methods: Participants from the Food4Me study, a 6-mo, Internet-based, randomized controlled trial of personalized nutrition conducted in the United Kingdom, Ireland, Spain, Netherlands, Germany, Greece, and Poland, were included. Screening and baseline data (both collected before commencement of the intervention) were used in the present analyses, and participants were included only if they completed FFQs at screening and at baseline within a 1-mo timeframe before the commencement of the intervention. Sociodemographic (e.g., sex and country) and lifestyle [e.g., body mass index (BMI, in kg/m(2)) and physical activity] characteristics were collected. Linear regression, correlation coefficients, concordance (percentage) in quartile classification, and Bland-Altman plots for daily intakes were used to assess reproducibility. Results: In total, 567 participants (59% female), with a mean +/- SD age of 38.7 +/- 13.4 y and BMI of 25.4 +/- 4.8, completed both FFQs within 1 mo (mean +/- SD: 19.2 +/- 6.2 d). Exact plus adjacent classification of total energy intake in participants was highest in Ireland (94%) and lowest in Poland (81 %). Spearman correlation coefficients (p) in total energy intake between FFQs ranged from 0.50 for obese participants to 0.68 and 0.60 in normal-weight and overweight participants, respectively. Bland-Altman plots showed a mean difference between FFQs of 210 kcal/d, with the agreement deteriorating as energy intakes increased. There was little variation in reproducibility of total energy intakes between sex and age groups. Conclusions: The online Food4Me FFQ was shown to be reproducible across 7 European countries when administered within a 1-mo period to a large number of participants. The results support the utility of the online Food4Me FFQ as a reproducible tool across multiple European populations