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.

Clustering of adherence to personalised dietary recommendations and changes in healthy eating index within the Food4Me study.

OBJECTIVE: To characterise clusters of individuals based on adherence to dietary recommendations and to determine whether changes in Healthy Eating Index (HEI) scores in response to a personalised nutrition (PN) intervention varied between clusters. DESIGN: Food4Me study participants were clustered according to whether their baseline dietary intakes met European dietary recommendations. Changes in HEI scores between baseline and month 6 were compared between clusters and stratified by whether individuals received generalised or PN advice. SETTING: Pan-European, Internet-based, 6-month randomised controlled trial. SUBJECTS: Adults aged 18-79 years (n 1480). RESULTS: Individuals in cluster 1 (C1) met all recommended intakes except for red meat, those in cluster 2 (C2) met two recommendations, and those in cluster 3 (C3) and cluster 4 (C4) met one recommendation each. C1 had higher intakes of white fish, beans and lentils and low-fat dairy products and lower percentage energy intake from SFA (P<0·05). C2 consumed less chips and pizza and fried foods than C3 and C4 (P<0·05). C1 were lighter, had lower BMI and waist circumference than C3 and were more physically active than C4 (P<0·05). More individuals in C4 were smokers and wanted to lose weight than in C1 (P<0·05). Individuals who received PN advice in C4 reported greater improvements in HEI compared with C3 and C1 (P<0·05). CONCLUSIONS: The cluster where the fewest recommendations were met (C4) reported greater improvements in HEI following a 6-month trial of PN whereas there was no difference between clusters for those randomised to the Control, non-personalised dietary intervention.

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. TRIAL REGISTRATION: ClinicalTrials.gov NCT01530139; http://clinicaltrials.gov/show/NCT01530139 (Archived by WebCite at: http://www.webcitation.org/6XII1QwHz).

Pretreatment fasting plasma glucose and insulin modify dietary weight loss success: results from 3 randomized clinical trials.

Background: Which diet is optimal for weight loss and maintenance remains controversial and implies that no diet fits all patients.Objective: We studied concentrations of fasting plasma glucose (FPG) and fasting insulin (FI) as prognostic markers for successful weight loss and maintenance through diets with different glycemic loads or different fiber and whole-grain content, assessed in 3 randomized trials of overweight participants.Design: After an 8-wk weight loss, participants in the DiOGenes (Diet, Obesity, and Genes) trial consumed ad libitum for 26 wk a diet with either a high or a low glycemic load. Participants in the Optimal well-being, development and health for Danish children through a healthy New Nordic Diet (OPUS) Supermarket intervention (SHOPUS) trial consumed ad libitum for 26 wk the New Nordic Diet, which is high in fiber and whole grains, or a control diet. Participants in the NUGENOB (Nutrient-Gene Interactions in Human Obesity) trial consumed a hypocaloric low-fat and high-carbohydrate or a high-fat and low-carbohydrate diet for 10 wk. On the basis of FPG before treatment, participants were categorized as normoglycemic (FPG <5.6 mmol/L), prediabetic (FPG 5.6-6.9 mmol/L), or diabetic (FPG ≥7.0 mmol/L). Modifications of the dietary effects of FPG and FI before treatment were examined with linear mixed models.Results: In the DiOGenes trial, prediabetic individuals regained a mean of 5.83 kg (95% CI: 3.34, 8.32 kg; P < 0.001) more on the high- than on the low-glycemic load diet, whereas normoglycemic individuals regained a mean of 1.44 kg (95% CI: 0.48, 2.41 kg; P = 0.003) more [mean group difference: 4.39 kg (95% CI: 1.76, 7.02 kg); P = 0.001]. In SHOPUS, prediabetic individuals lost a mean of 6.04 kg (95% CI: 4.05, 8.02 kg; P < 0.001) more on the New Nordic Diet than on the control diet, whereas normoglycemic individuals lost a mean of 2.20 kg (95% CI: 1.21, 3.18 kg; P < 0.001) more [mean group difference: 3.84 kg (95% CI: 1.62, 6.06 kg); P = 0.001]. In NUGENOB, diabetic individuals lost a mean of 2.04 kg (95% CI: -0.20, 4.28 kg; P = 0.07) more on the high-fat and low-carbohydrate diet than on the low-fat and high-carbohydrate diet, whereas normoglycemic individuals lost a mean of 0.43 kg (95% CI: 0.03, 0.83 kg; P = 0.03) more on the low-fat and high-carbohydrate diet [mean group difference: 2.47 kg (95% CI: 0.20, 4.75 kg); P = 0.03]. The addition of FI strengthened these associations.Conclusion: Elevated FPG before treatment indicates success with dietary weight loss and maintenance among overweight patients consuming diets with a low glycemic load or with large amounts of fiber and whole grains. These trials were registered at clinicaltrials.gov as NCT00390637 (DiOGenes) and NCT01195610 (SHOPUS), and at ISRNCT.com as ISRCTN25867281 (NUGENOB).

Transcriptome profiling from adipose tissue during a low-calorie diet reveals predictors of weight and glycemic outcomes in obese, nondiabetic subjects.

Background: A low-calorie diet (LCD) reduces fat mass excess, improves insulin sensitivity, and alters adipose tissue (AT) gene expression, yet the relation with clinical outcomes remains unclear.Objective: We evaluated AT transcriptome alterations during an LCD and the association with weight and glycemic outcomes both at LCD termination and 6 mo after the LCD.Design: Using RNA sequencing (RNAseq), we analyzed transcriptome changes in AT from 191 obese, nondiabetic patients within a multicenter, controlled dietary intervention. Expression changes were associated with outcomes after an 8-wk LCD (800-1000 kcal/d) and 6 mo after the LCD. Results were validated by using quantitative reverse transcriptase-polymerase chain reaction in 350 subjects from the same cohort. Statistical models were constructed to classify weight maintainers or glycemic improvers.Results: With RNAseq analyses, we identified 1173 genes that were differentially expressed after the LCD, of which 350 and 33 were associated with changes in body mass index (BMI; in kg/m2) and Matsuda index values, respectively, whereas 29 genes were associated with both endpoints. Pathway analyses highlighted enrichment in lipid and glucose metabolism. Classification models were constructed to identify weight maintainers. A model based on clinical baseline variables could not achieve any classification (validation AUC: 0.50; 95% CI: 0.36, 0.64). However, clinical changes during the LCD yielded better performance of the model (AUC: 0.73; 95% CI: 0.60, 0.87]). Adding baseline expression to this model improved the performance significantly (AUC: 0.87; 95% CI: 0.77, 0.96; Delong's P = 0.012). Similar analyses were performed to classify subjects with good glycemic improvements. Baseline- and LCD-based clinical models yielded similar performance (best AUC: 0.73; 95% CI: 0.60, 0.86). The addition of expression changes during the LCD improved the performance substantially (AUC: 0.80; 95% CI: 0.69, 0.92; P = 0.058).Conclusions: This study investigated AT transcriptome alterations after an LCD in a large cohort of obese, nondiabetic patients. Gene expression combined with clinical variables enabled us to distinguish weight and glycemic responders from nonresponders. These potential biomarkers may help clinicians understand intersubject variability and better predict the success of dietary interventions. This trial was registered at clinicaltrials.gov as NCT00390637.

Can genetic-based advice help you lose weight? Findings from the Food4Me European randomized controlled trial.

Background: There has been limited evidence about whether genotype-tailored advice provides extra benefits in reducing obesity-related traits compared with the benefits of conventional one-size-fits-all advice.Objective: We determined whether the disclosure of information on fat-mass and obesity-associated (FTO) genotype risk had a greater effect on a reduction of obesity-related traits in risk carriers than in nonrisk carriers across different levels of personalized nutrition.Design: A total of 683 participants (women: 51%; age range: 18-73 y) from the Food4Me randomized controlled trial were included in this analysis. Participants were randomly assigned to 4 intervention arms as follows: level 0, control group; level 1, dietary group; level 2, phenotype group; and level 3, genetic group. FTO (single nucleotide polymorphism rs9939609) was genotyped at baseline in all participants, but only subjects who were randomly assigned to level 3 were informed about their genotypes. Level 3 participants were stratified into risk carriers (AA/AT) and nonrisk carriers (TT) of the FTO gene for analyses. Height, weight, and waist circumference (WC) were self-measured and reported at baseline and months 3 and 6.Results: Changes in adiposity markers were greater in participants who were informed that they carried the FTO risk allele (level 3 AT/AA carriers) than in the nonpersonalized group (level 0) but not in the other personalized groups (level 1 and 2). Mean reductions in weight and WC at month 6 were greater for FTO risk carriers than for noncarriers in the level 3 group [-2.28 kg (95% CI: -3.06, -1.48 kg) compared with -1.99 kg (-2.19, -0.19 kg), respectively (P = 0.037); and -4.34 cm (-5.63, -3.08 cm) compared with -1.99 cm (-4.04, -0.05 cm), respectively, (P = 0.048)].Conclusions: There are greater body weight and WC reductions in risk carriers than in nonrisk carriers of the FTO gene. This trial was registered at clinicaltrials.gov as NCT01530139.

Effect of personalized nutrition on health-related behaviour change: evidence from the Food4Me European randomized controlled trial.

Background: Optimal nutritional choices are linked with better health, but many current interventions to improve diet have limited effect. We tested the hypothesis that providing personalized nutrition (PN) advice based on information on individual diet and lifestyle, phenotype and/or genotype would promote larger, more appropriate, and sustained changes in dietary behaviour. Methods: : Adults from seven European countries were recruited to an internet-delivered intervention (Food4Me) and randomized to: (i) conventional dietary advice (control) or to PN advice based on: (ii) individual baseline diet; (iii) individual baseline diet plus phenotype (anthropometry and blood biomarkers); or (iv) individual baseline diet plus phenotype plus genotype (five diet-responsive genetic variants). Outcomes were dietary intake, anthropometry and blood biomarkers measured at baseline and after 3 and 6 months' intervention. Results: At baseline, mean age of participants was 39.8 years (range 18-79), 59% of participants were female and mean body mass index (BMI) was 25.5 kg/m 2 . From the enrolled participants, 1269 completed the study. Following a 6-month intervention, participants randomized to PN consumed less red meat [-5.48 g, (95% confidence interval:-10.8,-0.09), P = 0.046], salt [-0.65 g, (-1.1,-0.25), P = 0.002] and saturated fat [-1.14 % of energy, (-1.6,-0.67), P < 0.0001], increased folate [29.6 µg, (0.21,59.0), P = 0.048] intake and had higher Healthy Eating Index scores [1.27, (0.30, 2.25), P = 0.010) than those randomized to the control arm. There was no evidence that including phenotypic and phenotypic plus genotypic information enhanced the effectiveness of the PN advice. Conclusions: Among European adults, PN advice via internet-delivered intervention produced larger and more appropriate changes in dietary behaviour than a conventional approach.

Distinct lipid profiles predict improved glycemic control in obese, nondiabetic patients after a low-caloric diet intervention: the Diet, Obesity and Genes randomized trial.

BACKGROUND: An aim of weight loss is to reduce the risk of type 2 diabetes (T2D) in obese subjects. However, the relation with long-term glycemic improvement remains unknown. OBJECTIVE: We evaluated the changes in lipid composition during weight loss and their association with long-term glycemic improvement. DESIGN: We investigated the plasma lipidome of 383 obese, nondiabetic patients within a randomized, controlled dietary intervention in 8 European countries at baseline, after an 8-wk low-caloric diet (LCD) (800-1000 kcal/d), and after 6 mo of weight maintenance. RESULTS: After weight loss, a lipid signature identified 2 groups of patients who were comparable at baseline but who differed in their capacities to lose weight and improve glycemic control. Six months after the LCD, one group had significant glycemic improvement [homeostasis model assessment of insulin resistance (HOMA-IR) mean change: -0.92; 95% CI: -1.17, -0.67)]. The other group showed no improvement in glycemic control (HOMA-IR mean change: -0.26; 95% CI: -0.64, 0.13). These differences were sustained for ≥1 y after the LCD. The same conclusions were obtained with other endpoints (Matsuda index and fasting insulin and glucose concentrations). Significant differences between the 2 groups were shown in leptin gene expression in adipose tissue biopsies. Significant differences were also observed in weight-related endpoints (body mass index, weight, and fat mass). The lipid signature allowed prediction of which subjects would be considered to be insulin resistant after 6 mo of weight maintenance [validation's receiver operating characteristic (ROC) area under the curve (AUC): 71%; 95% CI: 62%, 81%]. This model outperformed a clinical data-only model (validation's ROC AUC: 61%; 95% CI: 50%, 71%; P = 0.01). CONCLUSIONS: In this study, we report a lipid signature of LCD success (for weight and glycemic outcome) in obese, nondiabetic patients. Lipid changes during an 8-wk LCD allowed us to predict insulin-resistant patients after 6 mo of weight maintenance. The determination of the lipid composition during an LCD enables the identification of nonresponders and may help clinicians manage metabolic outcomes with further intervention, thereby improving the long-term outcome and preventing T2D. This trial was registered at clinicaltrials.gov as NCT00390637.

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.

Gene-nutrient interactions in the metabolic syndrome: single nucleotide polymorphisms in ADIPOQ and ADIPOR1 interact with plasma saturated fatty acids to modulate insulin resistance.

BACKGROUND: Progression of the metabolic syndrome (MetS) is determined by genetic and environmental factors. Gene-environment interactions may be important in modulating the susceptibility to the development of MetS traits. OBJECTIVE: Gene-nutrient interactions were examined in MetS subjects to determine interactions between single nucleotide polymorphisms (SNPs) in the adiponectin gene (ADIPOQ) and its receptors (ADIPOR1 and ADIPOR2) and plasma fatty acid composition and their effects on MetS characteristics. DESIGN: Plasma fatty acid composition, insulin sensitivity, plasma adiponectin and lipid concentrations, and ADIPOQ, ADIPOR1, and ADIPOR2 SNP genotypes were determined in a cross-sectional analysis of 451 subjects with the MetS who participated in the LIPGENE (Diet, Genomics, and the Metabolic Syndrome: an Integrated Nutrition, Agro-food, Social, and Economic Analysis) dietary intervention study and were repeated in 1754 subjects from the LIPGENE-SU.VI.MAX (SUpplementation en VItamines et Minéraux AntioXydants) case-control study (http://www.ucd.ie/lipgene). RESULTS: Single SNP effects were detected in the cohort. Triacylglycerols, nonesterified fatty acids, and waist circumference were significantly different between genotypes for 2 SNPs (rs266729 in ADIPOQ and rs10920533 in ADIPOR1). Minor allele homozygotes for both of these SNPs were identified as having degrees of insulin resistance, as measured by the homeostasis model assessment of insulin resistance, that were highly responsive to differences in plasma saturated fatty acids (SFAs). The SFA-dependent association between ADIPOR1 rs10920533 and insulin resistance was replicated in cases with MetS from a separate independent study, which was an association not present in controls. CONCLUSIONS: A reduction in plasma SFAs could be expected to lower insulin resistance in MetS subjects who are minor allele carriers of rs266729 in ADIPOQ and rs10920533 in ADIPOR1. Personalized dietary advice to decrease SFA consumption in these individuals may be recommended as a possible therapeutic measure to improve insulin sensitivity. This trial was registered at clinicaltrials.gov as NCT00429195.

Smoking status in relation to serum folate and dietary vitamin intake.

OBJECTIVE: Cigarette smoke itself is an abundant source of free radicals and a major cause of oxidative stress, to which plasma antioxidants function as a vital protective and counterbalancing mechanism. The objective of this study was to investigate into the relationship between smoking status and serum and dietary micronutrient concentrations. DESIGN: Cross-sectional study SUBJECTS - SETTING: 502 farmers from the Valley of Messara in Crete were randomly selected and examined. Complete three-day and 24-hr recall questionnaires were collected along with anthropometrical, physical activity and clinical data from all participating subjects. RESULTS: After adjusting for age, gender and number of fasting days adhered to per year, current smokers were found to have a lower dietary intake of vitamin C (112.1 mg vs. 136.4 mg, p = 0.03), fibre (16.6 g vs. 19.1 g, p = 0.006) and fruits and vegetables (339 g vs. 412 g, p = 0.014), while dietary vitamin B1 intake was found to be higher (1.7 mg vs. 1.4 mg, p = 0.02) in comparison to non/ex smokers. Dietary intake of meat, folate and vitami A, E, B2, B6 and B12 did not differ between the groups. Controlling age, gender, fasting days and dietary micronutrient intake, serum folate levels were found to be lower among smokers (geometric mean 15.3 nmol/L vs. 17.7 nmol/L, p = 0.023), while serum iron and vitamin B12 levels were not affected by smoking status. CONCLUSION: Current smoking status affects dietary nutrient intake as well as plasma folate levels. The above coherence between antioxidant depletion and reduced antioxidant intake may predispose smokers to the premature development of tobacco related mortality and morbidity.