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Measuring food intake with digital photography
Author(s) -
Martin C. K.,
Nicklas T.,
Gunturk B.,
Correa J. B.,
Allen H. R.,
Champagne C.
Publication year - 2014
Publication title -
journal of human nutrition and dietetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.951
H-Index - 70
eISSN - 1365-277X
pISSN - 0952-3871
DOI - 10.1111/jhn.12014
Subject(s) - cafeteria , medicine , photography , food intake , digital photography , reliability (semiconductor) , environmental health , pathology , art , power (physics) , physics , quantum mechanics , visual arts
Abstract The D igital P hotography of F oods M ethod accurately estimates the food intake of adults and children in cafeterias. When using this method, images of food selection and leftovers are quickly captured in the cafeteria. These images are later compared with images of ‘standard’ portions of food using computer software. The amount of food selected and discarded is estimated based upon this comparison, and the application automatically calculates energy and nutrient intake. In the present review, we describe this method, as well as a related method called the R emote F ood P hotography M ethod ( RFPM ), which relies on s martphones to estimate food intake in near real‐time in free‐living conditions. When using the RFPM , participants capture images of food selection and leftovers using a s martphone and these images are wirelessly transmitted in near real‐time to a server for analysis. Because data are transferred and analysed in near real‐time, the RFPM provides a platform for participants to quickly receive feedback about their food intake behaviour and to receive dietary recommendations for achieving weight loss and health promotion goals. The reliability and validity of measuring food intake with the RFPM in adults and children is also reviewed. In sum, the body of research reviewed demonstrates that digital imaging accurately estimates food intake in many environments and it has many advantages over other methods, including reduced participant burden, elimination of the need for participants to estimate portion size, and the incorporation of computer automation to improve the accuracy, efficiency and cost‐effectiveness of the method.