Two studies are reported; a pilot study to demonstrate feasibility followed by a larger validity study. Study 1’s objective was to test the effect of two ecological momentary assessment (EMA) approaches that varied in intensity on the validity/accuracy of estimating energy intake with the Remote Food Photography Method (RFPM) over six days in free-living conditions. When using the RFPM, Smartphones are used to capture images of food selection and plate waste and to send the images to a server for food intake estimation. Consistent with EMA, prompts are sent to the Smartphones reminding participants to capture food images. During Study 1, energy intake estimated with the RFPM and the gold standard, doubly labeled water (DLW), were compared. Participants were assigned to receive Standard EMA Prompts (n=24) or Customized Prompts (n=16) (the latter received more reminders delivered at personalized meal times). The RFPM differed significantly from DLW at estimating energy intake when Standard (mean±SD = −895±770 kcal/day, p<.0001), but not Customized Prompts (−270±748 kcal/day, p=.22) were used. Error (energy intake from the RFPM minus that from DLW) was significantly smaller with Customized vs. Standard Prompts. The objectives of Study 2 included testing the RFPM’s ability to accurately estimate energy intake in free-living adults (N=50) over six days, and energy and nutrient intake in laboratory-based meals. The RFPM did not differ significantly from DLW at estimating free-living energy intake (−152±694 kcal/day, p=0.16). During laboratory-based meals, estimating energy and macronutrient intake with the RFPM did not differ significantly compared to directly weighed intake.

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The Digital Photography of Foods Method accurately estimates the food intake of adults and children in cafeterias. When using this method, imags of food selection and leftovers are quickly captured in the cafeteria. These images are later compared to images of “standard” portions of food using a computer application. The amount of food selected and discarded is estimated based upon this comparison, and the application automatically calculates energy and nutrient intake. Herein, we describe this method, as well as a related method called the Remote Food Photography Method (RFPM), which relies on Smartphones 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 Smartphone and these images are wirelessly transmitted in near real-time to a server for analysis. Because data are transferred and analyzed in near real-time, the RFPM provides a platform for participants to quickly receive feedback about their food intake behavior and to receive dietary recommendations to achieve weight loss and health promotion goals. The reliability and validity of measuring food intake with the RFPM in adults and children will also be reviewed. The body of research reviewed herein 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 incorporation of computer automation to improve the accuracy, efficiency, and the cost-effectiveness of the method.