All methods of dietary intake assessment, both those in use and those under development, proceed food by food, meal by meal, and/or day by day to assemble a representation of habitual diet. That representation must then be analyzed at the n-of-1 level. We are introducing a disruptive innovation, diet quality photo navigation (DQPN™), which reverse engineers this process entirely, beginning with fully assembled dietary prototypes represented in photographic images. Each prototype depicts an objectively measured (1,2) quality tier of a given diet type, displayed in a standardized quantity. Quality is determined in part by the Healthy Eating Index (HEI-2010) and Alternate Healthy Eating Index (AHEI-2010), which align with the Dietary Guidelines for Americans. These trusted, scientifically validated tools are used to accurately measure diet quality and evaluate public health interventions relating to chronic disease and mortality risk.
All image components are fully pre-analyzed for culinary accuracy, overall quality, food group representation, relative quantity, and all nutrients using the industry standard nutrition analysis software for research. A simple, automated calculation of approximate energy requirements (3) allows for personalized nutrient intake estimates. DQPN replaces reliance on recollection and recall and their intrinsic limitations with image recognition, a native and universal human aptitude.
The method constrains potential error (4-7) by precluding implausible values. Post hoc analysis of individual intake is replaced with infinite scalability. DQPN replaces minutes, hours, and days of data inputs with the establishment of dietary intake pattern (Diet ID™) in mere seconds. Additional functionality adapts the method to identification of a dietary goal (Diet IDEAL™), and coaching along the specifically mapped route between current and goal diets, with implications for both human health coaching and apps/technology-based approaches to health promotion, disease management, weight management, and even the environmental impact of diet. Face validity is established by building the tool under the constant scrutiny, and to the specifications, of a multidisciplinary panel of independent content experts. Concurrent validation against prevailing instruments, and criterion validation against biomarkers is under way.
DQPN™ introduces a potentially disruptive innovation in dietary intake assessment with an array of ostensible advantages over currently prevailing methods.
1) Wang DD, Leung CW, Li Y, Ding EL, Chiuve SE, Hu FB, Willett WC. Trends in dietary quality among adults in the United States, 1999 through 2010. JAMA Intern Med. 2014 Oct;174(10):1587-95.
2) Guenther PM, Casavale KO, Reedy J, Kirkpatrick SI, Hiza HA, Kuczynski KJ, Kahle LL, Krebs-Smith SM. Update of the Healthy Eating Index: HEI-2010. J Acad Nutr Diet. 2013 Apr;113(4):569-80.
4) Naska A, Lagiou A, Lagiou P. Dietary assessment methods in epidemiological research: current state of the art and future prospects. F1000Res. 2017;16(6):926
5) Subar AF, Freedman LS, et al. Addressing Current Criticism Regarding the Value of Self-Report Dietary Data. J Nutr. 2015;145(12):2639-2645.
6) Hébert JR, Hurley TG, Steck SE, Miller DR, Tabung FK, Peterson KE, Kushi LH, Frongillo EA. Considering the value of dietary assessment data in informing nutrition-related health policy. Adv Nutr. 2014 Jul 14;5(4):447-55.
7) Boushey CJ, Spoden M, Zhu FM, Delp EJ, Kerr DA. New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods. Proc Nutr Soc. 2017 Aug;76(3):283-294.