Mobile Ecological Momentary Diet Assessment: A Low Burden, Ecologically-Valid Approach to Measuring Dietary Intake in Near-Real Time

移动生态瞬时饮食评估：一种低负担、生态有效的近实时测量膳食摄入量的方法

• 批准号: 10550227
• 负责人: Susan Schembre
• 金额: $ 65.23万
• 依托单位: GEORGETOWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10550227
• 关键词: Address; Adult; Age; American; American diet; Beverages; Categories; Cessation of life; Cognitive; Computer software; Consumption; Cross-Over Studies; Data; Diet; Dietary Assessment; Dietary Intervention; Dietary intake; Disease; Eating; Ecological momentary assessment; Energy Intake; Environment; Ethnic Origin; Event; Fatigue; Feedback; Food; Frequencies; Future; Gender; Goals; Image; Intake; Internet; Intervention; Interviewer; Measures; Memory; Methods; Modeling; National Health and Nutrition Examination Survey; Notification; Nutrient; Outcome Measure; Participant; Pattern; Persons; Population Heterogeneity; Premature Mortality; Psychosocial Factor; Public Health; Questionnaires; Race; Randomized; Recommendation; Reporting; Research; Research Personnel; Response Latencies; Sampling; Sodium; Source; Surveys; Taxes; Technology; Testing; Time; Translating; Update; Visual; Woman; Work; assessment application; behavior change; cost; design; dietary; dietary guidelines; feeding; fruits and vegetables; improved; men; minimally invasive; mobile application; mobile computing; novel; prevent; prototype; response; satisfaction; saturated fat; smartphone application; smartphone based assessment; social; sugar; tool; usability; user centered design

ABSTRACT The excessive intake of saturated fat and added sugars has been identified as a leading cause of premature mortality among adults in the U.S. contributing to approximately 700,000 deaths each year. The 2015-2020 Dietary Guidelines for Americans recommend limiting these nutrients to <10% total energy intake to prevent disease. Achieving these public health recommendations will require understanding the patterns of saturated fat and added sugar intake so more effective dietary interventions can be developed. Traditionally, estimates of saturated fat and added sugar intake are measured using food frequency questionnaires or 24-hr dietary recalls (24HR). These methods are time-intensive and cognitively taxing for users and costly for researchers. They are also highly prone to recall bias and misreporting related due, in part, to the reliance on a person’s memory over long recall intervals and errors in portion size estimation. The proposed dietary assessment method aims to address these limitations with ecological momentary assessment (EMA). EMA uses updated technology and sampling methods that can update and improve upon traditional assessment methods. EMA studies often use mobile phone apps to assess events with brief, automated surveys delivered periodically throughout the day. EMA can, thereby, shorten recall intervals to improve reporting errors and reduce user and researcher burden while maximizing the ecological validity. To date, mobile EMA methods for diet assessment (mEMDA) used in research have been study specific. They have not been systematically developed nor optimized for widespread use in research. This project would represent the first research-quality and fully automated, EMA-based mobile dietary assessment research tool. In recent pilot work, we demonstrated the potential utility of mEMDA. A brief mobile survey performed as well as web-assisted 24HR to estimate the intake of predefined snack foods. Here, the goal of the proposed project is to systematically develop and test a mEMDA app and sampling approach to accurately estimate the intake of saturated fat and added sugars in a diverse population. To do this we will derive a culturally- and demographically representative list of foods and beverages that contribute a majority (>70%) of the saturated fat and added sugars in the American diet using recent NHANES data (Aim 1); develop with a user-centered design the mEMDA app and analysis platform with visual food images for portion size estimation and nutrient analysis capabilities (Aim 2); determine the best mEMDA sampling approach (event-contingent vs. interval-contingent sampling) (Aim 3); and compare the accuracy of estimating energy intake from saturated fat and added sugars using the optimized mEMDA app and sampling approach vs. interviewer-assisted 24HR in a controlled-feeding study. Future applications of the mEMDA app include: (1) reliably assessing momentary intakes of other foods or nutrients (e.g., fruit and vegetable intake, sodium), (2) integration with mobile intervention platforms to give real-time, dietary feedback to participants (3) concurrent-capturing meal context variables (e.g., social, environmental, and psycho-social variables) for future, just-in-time dietary interventions.

抽象的 过量摄入饱和脂肪和添加糖已被确定为早产的主要原因 2015 年至 2020 年，美国成年人每年约有 70 万人死亡。 《美国人膳食指南》建议将这些营养素限制在总能量摄入量的 10% 以下，以预防 实现这些公共卫生建议需要了解饱和脂肪的模式。 并增加糖的摄入量，以便可以制定更有效的饮食干预措施。 使用食物频率调查问卷或 24 小时饮食回忆来测量饱和脂肪和添加糖的摄入量 (24HR)。这些方法对用户来说是耗时且认知负担重的，对研究人员来说成本高昂。 也很容易出现回忆偏差和误报，部分原因是对一个人记忆的依赖 所提出的饮食评估方法的目的是长回忆间隔和份量估计错误。 通过生态瞬时评估 (EMA) 解决这些限制，并使用最新技术。 可以更新和改进 EMA 研究经常使用的抽样方法。 手机应用程序通过全天定期提供的简短、自动调查来评估事件。 因此，EMA 可以缩短召回间隔，以改善报告错误并减轻用户和研究人员的负担 迄今为止，移动 EMA 饮食评估方法 (mEMDA) 已用于最大程度地提高生态有效性。 研究尚未针对具体研究进行系统开发或优化。 该项目将代表第一个研究质量的、基于 EMA 的全自动移动设备。 在最近的试点工作中，我们展示了 mEMDA 的潜在用途。 进行移动调查以及网络辅助 24 小时来估计预定义零食的摄入量。 拟议项目的目标是系统地开发和测试 mEMDA 应用程序和采样方法 准确估计不同人群中饱和脂肪和添加糖的摄入量为此，我们将得出结论。 具有文化和人口代表性的食品和饮料清单，占大多数 (>70%) 使用最近的 NHANES 数据（目标 1）确定美国饮食中的饱和脂肪和添加糖； 以用户为中心设计 mEMDA 应用程序和分析平台，使用视觉食物图像来估计份量 和营养分析能力（目标 2）；确定最佳的 mEMDA 采样方法（事件相关与随机事件） 间隔偶然抽样）（目标 3）；并比较估计饱和脂肪能量摄入量的准确性 并使用优化的 mEMDA 应用程序和抽样方法与访谈员协助的 24 小时添加糖 mEMDA 应用程序的未来应用包括：(1) 可靠地评估瞬时情况。 其他食物或营养素的摄入量（例如，水果和蔬菜的摄入量、钠），（2）与移动相结合 向参与者提供实时饮食反馈的干预平台 (3) 同时捕获膳食背景 未来及时饮食干预的变量（例如社会、环境和心理社会变量）。