Associations of vitamin D status with dietary intakes and physical activity levels among adults from seven European countries: the Food4Me study.

PURPOSE: To report the vitamin D status in adults from seven European countries and to identify behavioural correlates. METHODS: In total, 1075 eligible adult men and women from Ireland, Netherlands, Spain, Greece, UK, Poland and Germany, were included in the study. RESULTS: Vitamin D deficiency and insufficiency, defined as 25-hydroxy vitamin D3 (25-OHD3) concentration of <30 and 30-49.9 nmol/L, respectively, were observed in 3.3 and 30.6% of the participants. The highest prevalence of vitamin D deficiency was found in the UK and the lowest in the Netherlands (8.2 vs. 1.1%, P < 0.05). In addition, the prevalence of vitamin D insufficiency was higher in females compared with males (36.6 vs. 22.6%, P < 0.001), in winter compared with summer months (39.3 vs. 25.0%, P < 0.05) and in younger compared with older participants (36.0 vs. 24.4%, P < 0.05). Positive dose-response associations were also observed between 25-OHD3 concentrations and dietary vitamin D intake from foods and supplements, as well as with physical activity (PA) levels. Vitamin D intakes of ≥5 µg/day from foods and ≥5 µg/day from supplements, as well as engagement in ≥30 min/day of moderate- and vigorous-intensity PA were associated with higher odds (P < 0.05) for maintaining sufficient (≥50 nmol/L) 25-OHD3 concentrations. CONCLUSIONS: The prevalence of vitamin D deficiency varied considerably among European adults. Dietary intakes of ≥10 µg/day of vitamin D from foods and/or supplements and at least 30 min/day of moderate- and vigorous-intensity PA were the minimum thresholds associated with vitamin D sufficiency.

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.

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.

Physical activity attenuates the effect of the FTO genotype on obesity traits in European adults: The Food4Me study.

OBJECTIVE: To examine whether the effect of FTO loci on obesity-related traits could be modified by physical activity (PA) levels in European adults. METHODS: Of 1,607 Food4Me participants randomized, 1,280 were genotyped for FTO (rs9939609) and had available PA data. PA was measured objectively using accelerometers (TracmorD, Philips), whereas anthropometric measures [BMI and waist circumference (WC)] were self-reported via the Internet. RESULTS: FTO genotype was associated with a higher body weight [ß: 1.09 kg per risk allele, (95% CI: 0.14-2.04), P = 0.024], BMI [ß: 0.54 kg m(-2) , (0.23-0.83), P < 0.0001], and WC [ß: 1.07 cm, (0.24-1.90), P = 0.011]. Moderate-equivalent PA attenuated the effect of FTO on BMI (P[interaction] = 0.020). Among inactive individuals, FTO increased BMI by 1.06 kg m(-2) per allele (P = 0.024), whereas the increase in BMI was substantially attenuated among active individuals (0.16 kg m(-2) , P = 0.388). We observed similar effects for WC (P[interaction] = 0.005): the FTO risk allele increased WC by 2.72 cm per allele among inactive individuals but by only 0.49 cm in active individuals. CONCLUSIONS: PA attenuates the effect of FTO genotype on BMI and WC. This may have important public health implications because genetic susceptibility to obesity in the presence of FTO variants may be reduced by adopting a physically active lifestyle.

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

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 modeling to predict levels of PUFA in whole blood, based on multiple hypothesis testing and bootstrapped LASSO selected food items, anthropometric and lifestyle factors, and the rs174546 genotypes in FADS1 from 1607 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). Among 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 26-43% of the variability in PUFA concentrations in the training set and 22-33% in the test set. CONCLUSION: Selecting food items using multiple hypothesis testing 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.

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

UNLABELLED: 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. TRIAL REGISTRATION: NCT01530139 ( http://clinicaltrials.gov/show/NCT01530139 ).