TY - JOUR AU - Hu, Emily A AU - Nguyen, Viet AU - Langheier, Jason AU - Shurney, Dexter PY - 2020 DA - 2020/9/2 TI -基于数字营养和食品购买平台的肥胖用户减肥研究:纵向研究乔- J地中海互联网Res SP - e19634六世- 22 - 9千瓦数字KW -营养KW -膳食计划KW -减肥KW -肥胖KW -食品环境KW -食物订购KW -采购KW -行为经济学KW -行为改变KW -饮食行为KW - mHealth KW -应用AB -背景:数字营养应用程序监视器或提供建议的饮食可有效发现与肥胖个体行为改变和体重减少。然而，关于个性化营养建议的整合以及通过在线膳食计划和杂货配送、膳食包和杂货激励来改变食品购买环境如何影响肥胖个体的减肥的证据较少。目的:本观察性纵向研究的目的是检查肥胖个体的体重减轻和体重减轻的预测因素，这些肥胖个体是数字营养平台的用户，该平台集成了基于行为理论的营养建议和食品购买环境变化的工具。方法:我们纳入了2013年1月至2020年4月期间使用Zipongo, Inc .， DBA Foodsmart数字Foodsmart平台的8977名肥胖成年人。我们回顾性分析了用户特征及其与减肥的关系。参与者报告了年龄、性别、身高、至少两项体重和日常饮食摄入量。健康饮食评分是一个衡量整体饮食质量的评分，是根据对食物频率调查问卷的回答计算出来的。我们使用配对t检验来比较基线和最终体重以及基线和最终健康饮食评分的差异。我们使用单变量和多变量logistic回归模型，根据性别、年龄、基线BMI、健康饮食评分、健康饮食评分变化和入组时间估算体重减轻5%的比值比和95% CI。 We conducted stratified analyses to examine mean percent weight change by enrollment duration and gender, age, baseline BMI, and change in Healthy Diet Score. Results: Over a median (IQR) of 9.9 (0.03-54.7) months of enrollment, 59% of participants lost weight. Of the participants who used the Foodsmart platform for at least 24 months, 33.3% achieved 5% weight loss. In the fully adjusted logistic regression model, we found that baseline BMI (OR 1.02, 95% CI 1.02-1.03; P<.001), baseline Healthy Diet Score (OR 1.06, 95% CI 1.05-1.08; P<.001), greater change in Healthy Diet Score (OR 1.12, 95% CI 1.11-1.14; P<.001), and enrollment length (OR 1.28, 95% CI 1.23-1.32; P<.001) were all significantly associated with higher odds of achieving at least 5% weight loss. Conclusions: This study found that a digital app that provides personalized nutrition recommendations and change in one’s food purchasing environment appears to be successful in meaningfully reducing weight among individuals with obesity. SN - 1438-8871 UR - //www.mybigtv.com/2020/9/e19634/ UR - https://doi.org/10.2196/19634 UR - http://www.ncbi.nlm.nih.gov/pubmed/32792332 DO - 10.2196/19634 ID - info:doi/10.2196/19634 ER -