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: 10593785
• 负责人: Susan Schembre
• 金额: $ 71.61万
• 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/10593785
• 关键词: Address; Adult; Age; American; American diet; Back; Beverages; Car Phone; 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; Side; Sodium; Source; Surveys; Taxes; Technology; Testing; Time; Translating; Update; Visual; Woman; Work; base; 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; 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 饱和脂肪和添加的糖的过量摄入已被确定为过早的主要原因 美国成年人的死亡率每年造成约700,000人死亡。 2015-2020 美国人的饮食指南建议将这些营养物质限制为<10％的总能量摄入量以防止 疾病。实现这些公共卫生建议将需要了解饱和脂肪的模式 并增加了糖的摄入量，因此可以开发出更有效的饮食干预措施。传统上，估计 使用食物频率问卷或24小时饮食召回来测量饱和脂肪和添加的糖摄入量 （24小时）。这些方法是时间密集型，对用户的征收征税，对于研究人员来说是昂贵的。他们是 也很容易回忆起偏见和误导性相关，部分原因是对一个人的记忆的依赖 长时间的召回间隔和部分尺寸估计中的错误。拟议的饮食评估方法旨在 通过生态瞬时评估（EMA）来解决这些局限性。 EMA使用更新的技术， 可以对传统评估方法进行更新和改进的采样方法。 EMA研究经常使用 手机应用程序可以通过全天定期进行简短的自动调查来评估活动。 EMA可以缩短召回间隔，以改善报告错误并减少用户和研究人员伯恩伦 同时最大化生态有效性。迄今为止，用于饮食评估的移动EMA方法（MEMDA） 研究已经具体研究。它们尚未系统地开发或优化，以供宽度 在研究中使用。该项目将代表第一个研究质量和完全自动化的基于EMA的移动 饮食评估研究工具。在最近的试点工作中，我们证明了Memda的潜在效用。简短 移动调查还进行了24小时的网络辅助，以估计预定义零食食品的摄入量。这里， 拟议项目的目的是系统地开发和测试memda应用程序和采样方法 准确地估计潜水员种群中饱和脂肪的摄入量和添加的糖。为此，我们将得出 在文化和人口统计学上代表食物和卧室的清单，贡献了多数（> 70％） 使用最近的NHANES数据（AIM 1），在美国饮食中饱和脂肪和添加的糖；用 以用户为中心的设计MEMDA应用程序和分析平台，带有视觉食品图像，用于份量估计 和营养分析能力（AIM 2）；确定最佳的MEMDA采样方法（事件 - 持有人VS。 间隔示意图）（AIM 3）;并比较从饱和脂肪中估计能量摄入的准确性 并使用优化的MEMDA应用程序和采样方法与访调员辅助24小时添加糖 对照喂养研究。 MEMDA应用程序的未来应用包括：（1）可靠地评估瞬间 其他食物或养分的摄入量（例如水果和蔬菜摄入量，钠），（2）与移动 干预平台，向参与者提供实时的饮食反馈（3）并发捕获餐环境 变量（例如，社会，环境和心理社会变量），用于未来，即将到来的饮食干预措施。