Zenun Franco, R., Fallaize, R., Weech, M.
ORCID: https://orcid.org/0000-0003-1738-877X, Hwang, F.
ORCID: https://orcid.org/0000-0002-3243-3869 and Lovegrove, J. A.
ORCID: https://orcid.org/0000-0001-7633-9455
(2022)
Effectiveness of web-based personalized nutrition advice for adults using the eNutri web app: evidence from the EatWellUK randomized controlled trial.
Journal of Medical Internet Research, 24 (4).
ISSN 1438-8871
doi: 10.2196/29088
Abstract/Summary
Background: Evidence suggests eating behaviours and adherence to dietary guidelines can be improved using nutrition-related apps. Apps delivering personalised nutrition (PN) advice to users can provide individual support at-scale with relatively low-cost. Objective: To investigate the effectiveness of a mobile web application (eNutri) that delivers automated PN advice in improving diet quality, relative to general population food-based dietary guidelines. Methods: Non-diseased UK adults (aged >18 years) were randomised to (i) PN advice or (ii) control advice (population-based healthy eating guidelines) in a 12-week controlled, parallel, single-blinded, dietary intervention, which was delivered online. Dietary intake was assessed using the eNutri Food Frequency Questionnaire (FFQ). An 11-item modified US Alternative Healthy Eating Index (m-AHEI) aligned with UK dietary and nutritional recommendations was used to derive the automated PN advice. The primary outcome was change in diet quality (m-AHEI) at 12 weeks. Participant surveys evaluated the PN report (week 12) and longer-term impact of the PN advice (mean 5.9 months after completion of the study). Results: Following the baseline FFQ, 210 participants completed at least one additional FFQ, and n=23 outliers were excluded for unfeasible dietary intakes. The mean interval between FFQs was 10.8 weeks. 96 participants were included in the PN group (43.5 (SD 15.9) years; BMI 24.8 (4.4) kg/m2) and 91 in the control (42.8 (14.0) years; BMI 24.2 (4.4) kg/m2). Compared with the control group, the overall m-AHEI score increased by 3.5 out of 100 (CI 95%: 1.19-5.78) in the PN group, equivalent to an increase of 6.1% (P = .003). Specifically, the m-AHEI components ‘nuts and legumes’ and ‘red and processed meat’ showed significant improvements in the PN group (P’s = 0.04). At follow-up, 64% of PN participants agreed that, compared with baseline, they were still following some (‘any’) of the advice received and 31% were still motivated to improve their diet. Conclusions: These findings suggest that the eNutri app is an effective online tool for the automated delivery of PN advice. Furthermore, eNutri was demonstrated to improve short-term diet quality and increase engagement in healthy eating behaviours in UK adults, as compared with population-based healthy eating guidelines. This work represents an important landmark in the field of automatically delivered online personalised dietary interventions.
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| Item Type | Article |
| URI | https://reading-clone.eprints-hosting.org/id/eprint/102193 |
| Identification Number/DOI | 10.2196/29088 |
| Refereed | Yes |
| Divisions | Interdisciplinary centres and themes > Institute for Cardiovascular and Metabolic Research (ICMR) Life Sciences > School of Biological Sciences > Department of Bio-Engineering Life Sciences > School of Chemistry, Food and Pharmacy > Department of Food and Nutritional Sciences > Human Nutrition Research Group |
| Publisher | JMIR Publications |
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