基于网络的个性化营养建议对使用 eNutri 网络应用程序的成年人的有效性：来自 EatWellUK 随机对照试验的证据。

Effectiveness of Web-Based Personalized Nutrition Advice for Adults Using the eNutri Web App: Evidence From the EatWellUK Randomized Controlled Trial.

机构信息

Biomedical Engineering, School of Biological Sciences, University of Reading, Reading, United Kingdom.

Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, University of Reading, Reading, United Kingdom.

出版信息

J Med Internet Res. 2022 Apr 25;24(4):e29088. doi: 10.2196/29088.

DOI:10.2196/29088

PMID:35468093

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9154737/

Abstract

BACKGROUND

Evidence suggests that eating behaviors and adherence to dietary guidelines can be improved using nutrition-related apps. Apps delivering personalized nutrition (PN) advice to users can provide individual support at scale with relatively low cost.

OBJECTIVE

This study aims to investigate the effectiveness of a mobile web app (eNutri) that delivers automated PN advice for improving diet quality, relative to general population food-based dietary guidelines.

METHODS

Nondiseased UK adults (aged >18 years) were randomized to PN advice or control advice (population-based healthy eating guidelines) in a 12-week controlled, parallel, single-blinded dietary intervention, which was delivered on the web. Dietary intake was assessed using the eNutri Food Frequency Questionnaire (FFQ). An 11-item US modified Alternative Healthy Eating Index (m-AHEI), which aligned with UK dietary and nutritional recommendations, was used to derive the automated PN advice. The primary outcome was a 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, SD 0.65 months, after completion of the study).

RESULTS

Following the baseline FFQ, 210 participants completed at least 1 additional FFQ, and 23 outliers were excluded for unfeasible dietary intakes. The mean interval between FFQs was 10.8 weeks. A total of 96 participants were included in the PN group (mean age 43.5, SD 15.9 years; mean BMI 24.8, SD 4.4 kg/m) and 91 in the control group (mean age 42.8, SD 14.0 years; mean BMI 24.2, SD 4.4 kg/m). Compared with that in the control group, the overall m-AHEI score increased by 3.5 out of 100 (95% CI 1.19-5.78) in the PN group, which was 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=.04). At follow-up, 64% (27/42) of PN participants agreed that, compared with baseline, they were still following some (any) of the advice received and 31% (13/42) were still motivated to improve their diet.

CONCLUSIONS

These findings suggest that the eNutri app is an effective web-based tool for the automated delivery of PN advice. Furthermore, eNutri was demonstrated to improve short-term diet quality and increase engagement in healthy eating behaviors in UK adults, as compared with population-based healthy eating guidelines. This work represents an important landmark in the field of automatically delivered web-based personalized dietary interventions.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03250858; https://clinicaltrials.gov/ct2/show/NCT03250858.

摘要

背景

有证据表明，通过与营养相关的应用程序可以改善饮食行为和遵循饮食指南。为用户提供个性化营养建议的应用程序可以以相对较低的成本大规模提供个性化支持。

目的

本研究旨在调查一款名为 eNutri 的移动网络应用程序（提供自动化个性化营养建议）在改善饮食质量方面的效果，与基于人群的饮食指南相比。

方法

非患病的英国成年人（年龄>18 岁）在为期 12 周的对照、平行、单盲饮食干预中随机分配到个性化营养建议组或对照组（基于人群的健康饮食指南），通过网络提供。膳食摄入量使用 eNutri 食物频率问卷（FFQ）进行评估。使用美国改良的替代健康饮食指数（m-AHEI）的 11 项指标（与英国饮食和营养建议一致）得出自动化个性化营养建议。主要结局指标是 12 周时饮食质量（m-AHEI）的变化。参与者调查评估了个性化报告（第 12 周）和个性化营养建议的长期影响（完成研究后平均 5.9 个月，SD 0.65 个月）。

结果

在基线 FFQ 之后，210 名参与者完成了至少 1 次额外的 FFQ，23 名不符合饮食摄入量要求的参与者被排除在外。FFQ 之间的平均间隔为 10.8 周。共有 96 名参与者被纳入个性化营养组（平均年龄 43.5 岁，SD 15.9 岁；平均 BMI 24.8kg/m²），91 名参与者被纳入对照组（平均年龄 42.8 岁，SD 14.0 岁；平均 BMI 24.2kg/m²）。与对照组相比，个性化营养组的整体 m-AHEI 评分增加了 3.5 分（95%置信区间 1.19-5.78），相当于增加了 6.1%（P=.003）。具体而言，坚果和豆类以及红色和加工肉类的 m-AHEI 成分显示出显著改善（P=.04）。在随访时，64%（27/42）的个性化营养组参与者表示，与基线相比，他们仍然遵循一些（任何）收到的建议，31%（13/42）仍然有动力改善饮食。