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In the broad literature on the effects of ingredients, foods and diets on appetite and energy intake (EI), most trials involve a single acute intervention. It is unclear whether these acute results are generally sustained over longer periods. Researchers and regulators therefore lack an objective basis to judge the appropriate duration of efficacy trials in appetite control, to have confidence that acute effects are likely to be maintained. This gap creates uncertainty in requirements and study designs for the substantiation of satiety-enhancing approaches to help in controlling eating behaviour.
Materials and Methods:
A systematic search of literature (Prospero registration number CRD42015023686) identified studies testing both the acute and chronic effects of food-based interventions aimed at reducing appetite or EI. From 9680 unique records identified from titles and abstracts, 178 papers were selected for full screening. Twenty-six trials met the inclusion criteria and provided data sufficient for use in this analysis, and were also scored for risk of bias (RoB) indicators.
Most of these trials (21/26) measured appetite outcomes and over half (14/26) had objective measures of EI. A significant acute effect of the intervention was retained in 10 of 12 trials for appetite outcomes, and six of nine studies for EI. Initial effects were most likely retained where these were more robust and studies adequately powered. Where the initial, acute effect was not statistically significant, a significant effect was later observed in only two of nine studies for appetite and none of five studies for EI. The main sources of RoB were lack of a priori power calculations and failure to report analyses based on intention-to-treat. Furthermore, 12/26 studies were not adequately powered to detect a meaningful reduction in appetite (~10%).
Maintenance of acute intervention effects on appetite or EI need to be confirmed, but seems likely where the initially observed effects are robust and replicable in adequately powered studies.
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.
Traditionally, personalised nutrition was delivered at an individual level. However, the concept of delivering tailored dietary advice at a group level through the identification of metabotypes or groups of metabolically similar individuals has emerged. Although this approach to personalised nutrition looks promising, further work is needed to examine this concept across a wider population group. Therefore, the objectives of this study are to: (1) identify metabotypes in a European population and (2) develop targeted dietary advice solutions for these metabotypes. Using data from the Food4Me study (n 1607), k-means cluster analysis revealed the presence of three metabolically distinct clusters based on twenty-seven metabolic markers including cholesterol, individual fatty acids and carotenoids. Cluster 2 was identified as a metabolically healthy metabotype as these individuals had the highest Omega-3 Index (6·56 (sd 1·29) %), carotenoids (2·15 (sd 0·71) µm) and lowest total saturated fat levels. On the basis of its fatty acid profile, cluster 1 was characterised as a metabolically unhealthy cluster. Targeted dietary advice solutions were developed per cluster using a decision tree approach. Testing of the approach was performed by comparison with the personalised dietary advice, delivered by nutritionists to Food4Me study participants (n 180). Excellent agreement was observed between the targeted and individualised approaches with an average match of 82 % at the level of delivery of the same dietary message. Future work should ascertain whether this proposed method could be utilised in a healthcare setting, for the rapid and efficient delivery of tailored dietary advice solutions.
Individual response to dietary interventions can be highly variable. The phenotypic characteristics of those who will respond positively to personalised dietary advice are largely unknown. The objective of this study was to compare the phenotypic profiles of differential responders to personalised dietary intervention, with a focus on total circulating cholesterol. Subjects from the Food4Me multi-centre study were classified as responders or non-responders to dietary advice on the basis of the change in cholesterol level from baseline to month 6, with lower and upper quartiles defined as responder and non-responder groups, respectively. There were no significant differences between demographic and anthropometric profiles of the groups. Furthermore, with the exception of alcohol, there was no significant difference in reported dietary intake, at baseline. However, there were marked differences in baseline fatty acid profiles. The responder group had significantly higher levels of stearic acid (18 : 0, P=0·034) and lower levels of palmitic acid (16 : 0, P=0·009). Total MUFA (P=0·016) and total PUFA (P=0·008) also differed between the groups. In a step-wise logistic regression model, age, baseline total cholesterol, glucose, five fatty acids and alcohol intakes were selected as factors that successfully discriminated responders from non-responders, with sensitivity of 82 % and specificity of 83 %. The successful delivery of personalised dietary advice may depend on our ability to identify phenotypes that are responsive. The results demonstrate the potential use of metabolic profiles in identifying response to an intervention and could play an important role in the development of precision nutrition.
The interplay between the fat mass- and obesity-associated (FTO) gene variants and diet has been implicated in the development of obesity. The aim of the present analysis was to investigate associations between FTO genotype, dietary intakes and anthropometrics among European adults. Participants in the Food4Me randomised controlled trial were genotyped for FTO genotype (rs9939609) and their dietary intakes, and diet quality scores (Healthy Eating Index and PREDIMED-based Mediterranean diet score) were estimated from FFQ. Relationships between FTO genotype, diet and anthropometrics (weight, waist circumference (WC) and BMI) were evaluated at baseline. European adults with the FTO risk genotype had greater WC (AAv. TT: +1·4 cm; P=0·003) and BMI (+0·9 kg/m2; P=0·001) than individuals with no risk alleles. Subjects with the lowest fried food consumption and two copies of the FTO risk variant had on average 1·4 kg/m2 greater BMI (Ptrend=0·028) and 3·1 cm greater WC (Ptrend=0·045) compared with individuals with no copies of the risk allele and with the lowest fried food consumption. However, there was no evidence of interactions between FTO genotype and dietary intakes on BMI and WC, and thus further research is required to confirm or refute these findings.
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.
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