Reliability and Validity of Digital Images to Assess Child Dietary Intake in a Quick-Service Restaurant Setting

Published:August 09, 2022DOI:



      Development of methods to accurately measure dietary intake in free-living situations—restaurants or otherwise—is critically needed to understand overall dietary patterns.


      This study aimed to develop and test reliability and validity of digital images (DI) for measuring children’s dietary intake in quick-service restaurants (QSRs), validating against weighed plate waste (PW) and bomb calorimetry (BC).


      In 2016, cross-sectional data were collected at two time points within a randomized controlled trial assessing children’s leftovers in QSRs from parents of 4- to 12-year-old children.


      Parents (n = 640; mean age = 35.9 y; 70.8% female) consented and agreed to provide their child’s PW for digital imaging, across 11 QSRs in Massachusetts in areas with low socioeconomic status and ethnically diverse populations.

      Outcome measures

      Outcome measures were interrater reliability for DIs, correspondence between methods for energy consumed and left over, and correspondence between methods across varying quantities of PW.

      Analyses performed

      Intraclass correlations, percent agreement, Spearman correlations, Wilcoxon signed rank tests, and Bland-Altman plots were used.


      Interrater reliability ratings for DIs had substantial intraclass correlations (ICC = 0.94) but not acceptable exact percent agreement (80.2%); DI and PW energy consumed were significantly correlated (r = 0.96, P < 0.001); DI slightly underestimated energy consumed compared with PW (Mdiff = −1.61 kcals, P < 0.001). Bland-Altman plots showed high DI–PW correspondence across various energy amounts and revealed few outliers. Energy left over by BC was highly correlated with DI (r = 0.87, P < 0.001) and PW (r = 0.90, P < 0.001); and mean differences were not significantly different from DI (Mdiff = 9.77 kcal, P = 0.06) or PW (Mdiff = −2.84 kcal, P = 0.20).


      Correspondence was high between PW and DI assessments of energy consumed, and high with BC energy left over. Results demonstrate reliability and practical validity of digital images for assessing child meal consumption in QSR settings.


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        • Drewnowski A.
        • Rehm C.D.
        Energy intakes of US children and adults by food purchase location and by specific food source.
        Nutr J. 2013; 12: 1
        • Fryar C.
        • Carroll M.
        • Ahluwalia N.
        • Ogden C.L.
        Fast food intake among children and adolescents in the United States, 2015–2018.
        NCHS Data Brief. 2020; 375: 1-8
        • Mikkilä V.
        • Räsänen L.
        • Raitakari O.T.
        • Pietinen P.
        • Viikari J.
        Consistent dietary patterns identified from childhood to adulthood: The cardiovascular risk in Young Finns Study.
        Br J Nutr. 2005; 93: 923-931
        • Schwartz C.
        • Scholtens P.A.M.J.
        • Lalanne A.
        • Weenen H.
        • Nicklaus S.
        Development of healthy eating habits early in life: Review of recent evidence and selected guidelines.
        Appetite. 2011; 57: 796-807
        • Bowman S.A.
        • Gortmaker S.L.
        • Ebbeling C.B.
        • Pereira M.A.
        • Ludwig D.S.
        Effects of fast-food consumption on energy intake and diet quality among children in a national household survey.
        Pediatrics. 2004; 113: 112-118
        • Elbel B.
        • Gyamfi J.
        • Kersh R.
        Child and adolescent fast-food choice and the influence of calorie labeling: A natural experiment.
        Int J Obesity. 2011; 35: 493-500
        • Cohen J.F.W.
        • Roberts S.B.
        • Anzman-Frasca S.
        • et al.
        A pilot and feasibility study to assess children’s consumption in quick-service restaurants using plate waste methodology.
        BMC Public Health. 2017; 17: 259
        • Anzman-Frasca S.
        • Braun A.C.
        • Ehrenberg S.
        • et al.
        Effects of a randomized intervention promoting healthy children's meals on children's ordering and dietary intake in a quick-service restaurant.
        Physiol Behav. 2018; 192: 109-117
        • Center P.R.
        Mobile Fact Sheet.
        • Swanson M.
        Digital photography as a tool to measure school cafeteria consumption.
        J School Health. 2008; 78: 432-437
        • Williamson D.A.
        • Allen H.R.
        • Martin P.D.
        • Alfonso A.
        • Gerald B.
        • Hunt A.
        Digital photography: A new method for estimating food intake in cafeteria settings.
        Eating and Weight Disorders: Studies on Anorexia, Bulimia and Obesity. 2004; 9: 24-28
        • Gemming L.
        • Utter J.
        • Mhurchu C.N.
        Image-assisted dietary assessment: A systematic review of the evidence.
        J Acad Nutr Diet. 2015; 115: 64-77
        • Taylor J.C.
        • Yon B.A.
        • Johnson R.K.
        Reliability and validity of digital imaging as a measure of schoolchildren's fruit and vegetable consumption.
        J Acad Nutr Diet. 2014; 114: 1359-1366
        • Hinton E.C.
        • Brunstrom J.M.
        • Fay S.H.
        • et al.
        Using photography in ‘The Restaurant of the Future’: A useful way to assess portion selection and plate cleaning?.
        Appetite. 2013; 63: 31-35
        • Williamson D.A.
        • Allen H.R.
        • Martin P.D.
        • Alfonso A.J.
        • Gerald B.
        • Hunt A.
        Comparison of digital photography to weighed and visual estimation of portion sizes.
        J Am Diet Assoc. 2003; 103: 1139-1145
        • Martin C.K.
        • Newton Jr., R.L.
        • Anton S.D.
        • et al.
        Measurement of children's food intake with digital photography and the effects of second servings upon food intake.
        Eating Behaviors. 2007; 8: 148-156
        • Martin C.K.
        • Han H.
        • Coulon S.M.
        • Allen H.R.
        • Champagne C.M.
        • Anton S.D.
        A novel method to remotely measure food intake of free-living individuals in real time: The remote food photography method.
        Br J Nutr. 2009; 101: 446-456
        • Merrill A.L.
        • Watt B.K.
        • Agricultural Research Service (Agriculture Handbook No 74)
        Energy value of foods: Basis and derivation. United States Department of Agriculture, 1973
        • Urban L.E.
        • McCrory M.A.
        • Dallal G.E.
        • et al.
        Accuracy of stated energy contents of restaurant foods.
        JAMA. 2011; 306: 287-293
        • Comstock E.M.
        • St Pierre R.G.
        • Mackiernan Y.D.
        Measuring individual plate waste in school lunches: Visual estimation and children's ratings vs. actual weighing of plate waste.
        J Am Diet Assoc. 1981; 79: 290-296
        • Adams M.A.
        • Pelletier R.L.
        • Zive M.M.
        • Sallis J.F.
        Salad bars and fruit and vegetable consumption in elementary schools: A plate waste study.
        J Am Diet Assoc. 2005; 105: 1789-1792
        • Gervis J.E.
        • Hennessy E.
        • Shonkoff E.T.
        • et al.
        Weighed plate waste can accurately measure children's energy consumption from food in quick-service restaurants.
        J Nutr. 2020; 150: 404-410
        • Urban L.E.
        • Dallal G.E.
        • Robinson L.M.
        • Ausman L.M.
        • Saltzman E.
        • Roberts S.B.
        The accuracy of stated energy contents of reduced-energy, commercially prepared foods.
        J Am Diet Assoc. 2010; 110: 116-123
        • Shrout P.E.
        • Fleiss J.L.
        Intraclass correlations: uses in assessing rater reliability.
        Psychol Bull. 1979; 86: 420
        • Baglio M.L.
        • Baxter S.D.
        • Guinn C.H.
        • Thompson W.O.
        • Shaffer N.M.
        • Frye F.H.A.
        Assessment of interobserver reliability in nutrition studies that use direct observation of school meals.
        J Am Diet Assoc. 2004; 104: 1385-1392
        • Shrout P.E.
        Measurement reliability and agreement in psychiatry.
        Stat Methods Med Res. 1998; 7: 301-317
        • Hanks A.S.
        • Wansink B.
        • Just D.R.
        Reliability and accuracy of real-time visualization techniques for measuring school cafeteria tray waste: Validating the quarter-waste method.
        J Acad Nutr Diet. 2014; 114: 470-474
        • Kenney E.L.
        • Davison K.K.
        • Austin S.B.
        • et al.
        Validity and reliability of a simple, low-cost measure to quantify children's dietary intake in afterschool settings.
        J Acad Nutr Dietetics. 2015; 115: 426-432
        • Lassen A.D.
        • Ernst L.
        • Poulsen S.
        • et al.
        Effectiveness of a canteen take away concept in promoting healthy eating patterns among employees.
        Public Health Nutr. 2012; 15: 452-458
        • Martin C.K.
        • Correa J.B.
        • Han H.
        • et al.
        Validity of the Remote Food Photography Method (RFPM) for estimating energy and nutrient intake in near real-time.
        Obesity. 2012; 20: 891-899
        • Lassen A.D.
        • Beck A.
        • Leedo E.
        • et al.
        Effectiveness of offering healthy labelled meals in improving the nutritional quality of lunch meals eaten in a worksite canteen.
        Appetite. 2014; 75: 128-134


      E. T. S. is an assistant clinical professor at Merrimack College, North Andover, MA. At the time of the research, she was a postdoctoral scholar at the Friedman School of Nutrition, Tufts University, Boston.


      E. H. is an assistant professor, Friedman School of Nutrition, Tufts University, Boston, MA.


      K. C. is an assistant professor of public health and community medicine, Tufts University, Boston, MA.


      M.A.J. is a PhD Candidate, Friedman School of Nutrition, Tufts University, Boston, MA.


      E. M. is data manager and program administrator, Social & Scientific Systems, Inc. At the time of the research, she was Friedman School of Nutrition, Tufts University, Boston, MA.


      S. A. is an assistant professor, University of Rhode Island, at the time of research, she was a postdoctoral scholar at Friedman School of Nutrition, Tufts University, Boston, MA.


      P. B. is a statistical manager, Friedman School of Nutrition, Tufts University, Boston, MA.


      S. B. R. is a professor, Friedman School of Nutrition, Tufts University, Boston, MA.


      M. B. is a senior clinical data associate research assistant, Syneos Health, at the time of research she was a research assistant at Friedman School of Nutrition, Tufts University, Boston, MA.


      J. a clinical research dietitian at Massachusetts General Hospital , Friedman School of Nutrition, Tufts University, Boston, MA.


      C. D. E. is a professor, at the time of research she was a research assistant at Friedman School of Nutrition, Tufts University, Boston, MA.