Nutritional adequacy and content of food bank parcels in Oxfordshire, UK: a comparative analysis of independent and organisational provision

Background: Food bank use has increased significantly in the UK. With the rise in demand, it is imperative that users are receiving food parcels that meet their requirements. The present study aimed to explore whether typical food parcels, supplied by The Trussell Trust and independent food banks, were meeting the daily nutrient and energy requirements of an adult user. Methods: The Trussell Trust (n = 2) and independent food banks (n = 9) were surveyed in Oxfordshire, UK. Data were collected on food bank use, resources, donations and parcel content. The energy and nutrient contents of a representative parcel were compared with the average dietary reference values (DRVs) for an adult. Additional comparisons were made between The Trussell Trust and independent provision. Results: Parcels provided energy, carbohydrate, sugar, protein and fibre contents that significantly exceeded the DRVs. In total, 62.2% of energy was provided as carbohydrate and 569% of the DRV was provided by sugars. The vitamin D and retinol content of the parcels was significantly lower than the DRVs, meeting 25% and 27% of users’ needs respectively; provision of all other micronutrients exceeded the DRVs. The Trussell Trust’s parcels provided significantly less vitamin D and copper than independent parcels. Conclusions: Food bank parcels distributed in Oxfordshire, UK, exceeded energy requirements and provided disproportionately high sugar and carbohydrate and inadequate vitamin A and vitamin D compared to the UK guidelines. Improved links with distributors and access to cold food storage facilities would help to address these issues, via increased fresh food provisio

Strategies for online personalised nutrition advice employed in the development of the eNutri web app

The internet has considerable potential to improve health-related food choice at low-cost. Online solutions in this field can be deployed quickly and at very low cost, especially if they are not dependent on bespoke devices or offline processes such as the provision and analysis of biological samples. One key challenge is the automated delivery of personalised dietary advice in a replicable, scalable and inexpensive way, using valid nutrition assessment methods and effective recommendations. We have developed a web-based personalised nutrition system (eNutri) which assesses dietary intake using a validated graphical FFQ and provides personalised food-based dietary advice automatically. Its effectiveness was evaluated during an online randomised controlled trial dietary intervention (EatWellUK study) in which personalised dietary advice was compared with general population recommendations (control) delivered online. The present paper presents a review of literature relevant to this work, and describes the strategies used during the development of the eNutri app. Its design and source code have been made publicly available under a permissive open source license, so that other researchers and organisations can benefit from this work. In a context where personalised diet advice has great potential for health promotion and disease prevention at-scale and yet is not currently being offered in the most popular mobile apps, the strategies and approaches described in the present paper can help to inform and advance the design and development of technologies for personalised nutrition

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 (β = -0.181, p < 0.001) and waist circumference (Β = -0.155, p < 0.001), and positively associated with total carotenoids (β = 0.198, p < 0.001), omega-3 fatty acid index (β = 0.155, p < 0.001), Healthy Eating Index (HEI) (β = 0.299, p < 0.001) and Mediterranean Diet Score (MDS) (β = 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 .Peer reviewedFinal Published versio

Application of behavior change techniques in a personalized nutrition Electronic Health intervention study: protocol for the web-based Food4Me randomized controlled trial

Background: In order to determine the efficacy of behavior change techniques (BCT) applied in dietary and physical activity intervention studies, it is first necessary to record and describe techniques which have been used during such interventions. Published frameworks used in dietary and smoking cessation interventions undergo continuous development and most are not adapted for online delivery. The Food4Me study (N=1607) provided the opportunity to use existing frameworks to describe standardized online techniques employed in a large-scale internet-based intervention to change dietary behaviour and physical activity. Objectives: To describe techniques embedded in the Food4Me study design and explain the selection rationale. To demonstrate the use of behaviour change technique taxonomies, develop standard operating procedures for training, and identify strengths and limitations of the Food4Me framework that will inform its use in future studies. Methods: The 6-month randomized controlled trial took place simultaneously in 7 European countries, with participants receiving one of 4 levels of personalized advice (generalized, intake-based, intake+phenotype-based and intake+phenotype+gene-based). A 3-phase approach was taken: (I), existing taxonomies were reviewed and techniques were identified a priori for possible inclusion in the Food4Me study; (II) a standard operating procedure was developed to maintain consistency in the use of methods and techniques across research centers; (III) the Food4Me BCT framework was reviewed and updated post intervention. An analysis of excluded techniques was also conducted. Results: Of 46 techniques identified a priori as being applicable to Food4Me, 17 were embedded in the intervention design. Eleven were from a dietary taxonomy and 6 from a smoking cessation taxonomy. In addition, the 4-category smoking cessation framework structure was adopted for clarity of communication. Smoking cessation texts were adapted for dietary use where necessary. A posteriori, a further 9 techniques were included. Examination of excluded items highlighted the distinction between techniques considered appropriate for face-to-face vs internet-based delivery. Conclusions: The use of existing taxonomies facilitated the description and standardization of techniques used in Food4Me. We recommend that for complex studies of this nature, technique analysis should be conducted a priori to develop standardized procedures and training, and reviewed a posteriori to audit the techniques actually adopted. The present framework description makes a valuable contribution to future systematic reviews and meta-analyses which explore technique efficacy and underlying psychological constructs. This was a novel application of the behavior change taxonomies, and was the first internet-based personalized nutrition intervention to use such a framework remotely

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 modelling to predict levels of PUFA in whole blood, based on MHT and bolasso selected food items, anthropometric and lifestyle factors, and the rs174546 genotypes in FADS1 from 1,607 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). Amongst 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% to 43% of the variability in PUFA concentrations in the training set and 22% to 33% in the test set. CONCLUSIONS: Selecting food items using MHT 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

The perceived impact of the National Health Service on personalised nutrition service delivery among the UK public

Personalised nutrition (PN) has the potential to reduce disease risk and optimise health and performance. Although previous research has shown good acceptance of the concept of PN in the UK, preferences regarding the delivery of a PN service (e.g. online v. face-to-face) are not fully understood. It is anticipated that the presence of a free at point of delivery healthcare system, the National Health Service (NHS), in the UK may have an impact on end-user preferences for deliverances. To determine this, supplementary analysis of qualitative data obtained from focus group discussions on PN service delivery, collected as part of the Food4Me project in the UK and Ireland, was undertaken. Irish data provided comparative analysis of a healthcare system that is not provided free of charge at the point of delivery to the entire population. Analyses were conducted using the 'framework approach' described by Rabiee (Focus-group interview and data analysis. Proc Nutr Soc 63, 655-660). There was a preference for services to be led by the government and delivered face-to-face, which was perceived to increase trust and transparency, and add value. Both countries associated paying for nutritional advice with increased commitment and motivation to follow guidelines. Contrary to Ireland, however, and despite the perceived benefit of paying, UK discussants still expected PN services to be delivered free of charge by the NHS. Consideration of this unique challenge of free healthcare that is embedded in the NHS culture will be crucial when introducing PN to the UK

Profile of European adults interested in internet-based personalized nutrition: The Food4Me Study

Purpose Personalised intervention may have greater potential for reducing the global burden of non-communicable diseases and for promoting better health and wellbeing across the life-span than the conventional “one size fits all” approach. However, the characteristics of individuals interested in personalised nutrition (PN) are unclear. Therefore, the aim of this study was to describe the characteristics of European adults interested in taking part in an internet-based PN study. Methods Individuals from seven European countries (UK, Ireland, Germany, the Netherlands, Spain, Greece and Poland) were invited to participate in the study via the Food4Me website (http://www.food4me.org). Two screening questionnaires were used to collect data on socio-demographic, anthropometric and health characteristics as well as dietary intakes. Results A total of 5662 individuals expressed an interest in the study (mean age 40 ± 12.7; range 15-87 years). Of these 64.6% were female and 96.9% were Caucasian. Overall, 12.9% were smokers and 46.8% reported the presence of a clinically diagnosed disease. Furthermore, 46.9% were overweight or obese and 34.9% were sedentary during leisure time. Assessment of dietary intakes showed that 54.3% of individuals reported consuming at least 5 portions of fruit and vegetables per day, 45.9% consumed more than 3 servings of wholegrains and 37.2% limited their salt intake to less than 5.75g per day. Conclusions Our data indicate that individuals volunteering to participate in an internet-based PN study are broadly representative of the European adult population, most of whom had adequate nutrient intakes but who could benefit from improved dietary choices and greater physical activity. Future use of internet-based PN approaches is thus relevant to a wide target audience

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 10 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 \ub1 0.37 vs 21.1 \ub1 0.65; P=0.005). Percentage energy (31.2 \ub1 0.59 vs 32.7 \ub1 0.59; P=0.031), percentage total fat (31.5 \ub1 0.37 vs 33.3 \ub1 0.65; P=0.021), SFA (36.0 \ub1 0.43 vs 37.8 \ub1 0.75; P=0.034) and sugars (31.7 \ub1 0.44 vs 34.7 \ub1 0.78; P&lt;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. 21Conclusions: 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 24 used to target intakes of discretionary foods

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

©Rosalind Fallaize, Hannah Forster, Anna L Macready, Marianne C Walsh, John C Mathers, Lorraine Brennan, Eileen R Gibney, Michael J Gibney, Julie A Lovegrove. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 11.08.2014. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.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.Peer reviewedFinal Published versio

Online dietary intake estimation : The food4me food frequency questionnaire

Copyright ©Hannah Forster, Rosalind Fallaize, Caroline Gallagher, Clare B O’Donovan, Clara Woolhead, Marianne C Walsh, Anna L Macready, Julie A Lovegrove, John C Mathers, Michael J Gibney, Lorraine Brennan, Eileen R Gibney. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 09.06.2014. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.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.Peer reviewedFinal Published versio