Dataset Information

Evaluation of the eNutri automated personalised nutrition advice by users and nutrition professionals in the UK.

ABSTRACT: Nutrition apps have great potential to support people to improve their diets, but few apps give automated validated personalised nutrition advice. A web app capable of delivering automated personalised food-based nutrition advice (eNutri) was developed. The aims of this study were to i) evaluate and optimise the personalised nutrition report provided by the app and ii) compare the personalised food-based advice with nutrition professionals' standards to aid validation. A study with nutrition professionals (NP) compared the advice provided by the app against professional Registered Dietitians (RD) (n = 16) and Registered Nutritionists (RN) (n = 16) standards. Each NP received two pre-defined scenarios, comprising an individual's characteristics and dietary intake based on an analysis of a food frequency questionnaire, along with the nutrition food-based advice that was automatically generated by the app for that individual. NPs were asked to use their professional judgment to consider the scenario, provide their three most relevant recommendations for that individual, then consider the app's advice and rate their level of agreement via 5-star scales (with 5 as complete agreement). NPs were also asked to comment on the eNutri recommendations, scores generated and overall impression. The mean scores for the appropriateness, relevance and suitability of the eNutri diet messages were 3.5, 3.3 and 3.3 respectively.

SUBMITTER: Fallaize R

PROVIDER: S-EPMC6447217 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Evaluation of the eNutri automated personalised nutrition advice by users and nutrition professionals in the UK.

Fallaize Rosalind R Franco Rodrigo Zenun RZ Hwang Faustina F Lovegrove Julie A JA

PloS one 20190403 4

Nutrition apps have great potential to support people to improve their diets, but few apps give automated validated personalised nutrition advice. A web app capable of delivering automated personalised food-based nutrition advice (eNutri) was developed. The aims of this study were to i) evaluate and optimise the personalised nutrition report provided by the app and ii) compare the personalised food-based advice with nutrition professionals' standards to aid validation. A study with nutrition pro ...[more]

PMID: 30943252

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Project description:BackgroundThe 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.MethodsParticipants 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 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.ResultsOf 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 ± 0.37 vs 21.1 ± 0.65; P = 0.005). Percentage energy (31.2 ± 0.59 vs 32.7 ± 0.59; P = 0.031), percentage total fat (31.5 ± 0.37 vs 33.3 ± 0.65; P = 0.021), SFA (36.0 ± 0.43 vs 37.8 ± 0.75; P = 0.034) and sugars (31.7 ± 0.44 vs 34.7 ± 0.78; P < 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.ConclusionsCompared 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 used to target intake of discretionary foods.Trial registrationClinicaltrials.gov NCT01530139 . Registered 9 February 2012.

Project description:OBJECTIVES:To examine knowledge and beliefs about the biological roles of dietary inorganic nitrate in UK-based nutrition professionals, and to explore potential differences by participants' education level. SETTING:An online questionnaire was administered to UK-based nutrition professionals, exploring knowledge and/or beliefs across five areas: (1) health and performance effects of nitrate; (2) current and recommended intake values for nitrate; (3) dietary sources of nitrate; (4) methods of evaluating nitrate intake and (5) nitrate metabolism. PARTICIPANTS:One hundred and twenty-five nutrition professionals. PRIMARY OUTCOME:Knowledge and beliefs about inorganic nitrate. RESULTS:Most nutrition professionals taking part in the survey had previously heard of inorganic nitrate (71%) and perceived it to be primarily beneficial (51%). The majority believed that nitrate consumption can improve sports performance (59%) and reduce blood pressure (54%), but were unsure about effects on cognitive function (71%), kidney function (80%) and cancer risk (70%). Knowledge of dietary sources of nitrate and factors affecting its content in food were generally good (41%-79% of participants providing correct answers). However, most participants were unsure of the average population intake (65%) and the acceptable daily intake (64%) of nitrate. Most participants (65%) recognised at least one compound (ie, nitric oxide or nitrosamines) that is derived from dietary nitrate in the body. Knowledge of nitrate, quantified by a 23-point index created by summing correct responses, was greater in individuals with a PhD (p=0.01; median (IQR)=13 (9-17)) and tended to be better in respondents with a masters degree (p=0.054; 13 (8-15)) compared with undergraduate-level qualifications (10 (2-14)). CONCLUSIONS:UK-based nutrition professionals demonstrated mixed knowledge about the physiology of dietary nitrate, which was better in participants with higher education. More efficient dissemination of current knowledge about inorganic nitrate and its effects on health to nutrition professionals will support them to make more informed recommendations about consumption of this compound.

Dataset Information

Evaluation of the eNutri automated personalised nutrition advice by users and nutrition professionals in the UK.

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Evaluation of the eNutri automated personalised nutrition advice by users and nutrition professionals in the UK.

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