4.5 Article

Use of technology in children's dietary assessment

期刊

EUROPEAN JOURNAL OF CLINICAL NUTRITION
卷 63, 期 -, 页码 S50-S57

出版社

NATURE PUBLISHING GROUP
DOI: 10.1038/ejcn.2008.65

关键词

dietary assessment; food records; digital images

资金

  1. National Cancer Institute [1U01CA130784-01]
  2. National Institute of Diabetes and Digestive and Kidney Diseases [1R01DK073711-01A1]

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Background: Information on dietary intake provides some of the most valuable insights for mounting intervention programmes for the prevention of chronic diseases. With the growing concern about adolescent overweight, the need to accurately measure diet becomes imperative. Assessment among adolescents is problematic as this group has irregular eating patterns and they have less enthusiasm for recording food intake. Subjects/Methods: We used qualitative and quantitative techniques among adolescents to assess their preferences for dietary assessment methods. Results: Dietary assessment methods using technology, for example, a personal digital assistant (PDA) or a disposable camera, were preferred over the pen and paper food record. Conclusions: There was a strong preference for using methods that incorporate technology such as capturing images of food. This suggests that for adolescents, dietary methods that incorporate technology may improve cooperation and accuracy. Current computing technology includes higher resolution images, improved memory capacity and faster processors that allow small mobile devices to process information not previously possible. Our goal is to develop, implement and evaluate a mobile device (for example, PDA, mobile phone) food record that will translate to an accurate account of daily food and nutrient intake among adolescents. This mobile computing device will include digital images, a nutrient database and image analysis for identification and quantification of food consumption. Mobile computing devices provide a unique vehicle for collecting dietary information that reduces the burden on record keepers. Images of food can be marked with a variety of input methods that link the item for image processing and analysis to estimate the amount of food. Images before and after the foods are eaten can estimate the amount of food consumed. The initial stages and potential of this project will be described.

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