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在PakNutriStudy中比较基于网络的和传统的自报的24小时饮食回忆数据

Afifa Tanweer¹, Mutayyabah Zia¹, Kainat Riaz¹

¹Department of Nutrition and Dietetics, School of Health Sciences, University of Management and Technology, Health Sciences Campus, Raiwind Road, Lahore, Pakistan.

Computer methods and programs in biomedicine

|July 10, 2023

概括

数字饮食评估工具,如Intake24,为改善数据准确性和减少营养研究偏见提供了一个有希望的解决方案. 这项研究发现,饮料消费的数字和传统24小时回忆方法之间存在相当的一致性.

科学领域:

营养科学营养科学
公共卫生公共卫生
数字健康数字健康

背景情况:

饮食评估方法容易出现缺陷,导致不准确的数据和潜在的错误干预.
饮食评估工具的数字化可以减轻偏见,简化数据处理.

研究的目的:

与传统版本相比,评估数字24小时召回 (24HR) 工具的数据协议和可行性.
评估Intake24系统在南亚环境下收集饮食数据的可用性.

主要方法:

一项涉及102名参与者 (18-25岁) 的横截面研究,他们完成了24HR的传统 (24HR Ver-01) 和数字 (24HR Ver-02) 版本.
数字24HR使用了Intake24系统,结合了南亚饮料食品数据库.

主要成果:

在饮料消费的数字和传统24HR之间观察到公平的协议 (平均kappa κ =0.375833).
在早餐零食,午餐和晚餐期间,两种版本之间的部分大小之间发现了统计学上显著的相关性.
虽然数据收集者发现数字版本更容易处理,但参与者表示它耗时且不那么方便.

结论:

数字24HR工具 (Intake24) 显示了准确的饮食数据收集的潜力,实现了公平协议水平.
建议进行进一步的研究,包括交叉研究和对客观措施的验证,以确定确的证据.

关键词:

24小时召回回忆饮食评估饮食评估数字化的数字化摄入 24 小时 24 小时营养评估营养评估

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