Automatic Food Documentation and Volume Computation Using Digital Imaging and Electronic Transmission

Abstract

Capturing accurate food intake data from participants enrolled in nutrition studies is essential for understanding relationships between diet and chronic disease. Numerous methods are used to assess dietary intake, such as food records, 24-hour recalls, or food frequency questionnaires. Although each of these techniques is valuable, the error associated with each is unique. The food record requires a motivated participant, is tedious for some, places attention on the act of eating (thus possibly altering intake), and is difficult for subjects with low literacy skills. Interviewing subjects about the previous day’s intake avoids the reactivity involved when recording current intake, but also requires the individual reporting intake to have good recall skills, knowledge of food names, and ability to estimate amounts eaten. A well-trained interviewer is required, which makes this a costly process. Food frequency questionnaires are limited by food lists and lack of detail regarding food preparation, and require respondents to summarize past intake over many months or the past year. Such instruments are known to contain significant measurement error. All of these methods provide valuable information about dietary intake, but improving methodology even modestly would advance our knowledge about the influence of food intake on health.