Assessing daily energy intake in adult women: validity of a food-recognition mobile application compared to doubly labelled water

Michele Serra, Daniela Alceste, Florian Hauser, Paul J.M. Hulshof, Harro A.J. Meijer, Andreas Thalheimer, Robert E. Steinert, Philipp A. Gerber, Alan C. Spector, Daniel Gero, Marco Bueter*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Accurate dietary assessment is crucial for nutrition and health research. Traditional methods, such as food records, food frequency questionnaires, and 24-hour dietary recalls (24HR), have limitations, such as the need for trained interviewers, time-consuming procedures, and inaccuracies in estimations. Novel technologies, such as image-based dietary assessment apps, have been developed to overcome these limitations. SNAQ is a novel image-based food-recognition app which, based on computer vision, assesses food type and volume, and provides nutritional information about dietary intake. This cross-sectional observational study aimed to investigate the validity of SNAQ as a dietary assessment tool for measuring energy and macronutrient intake in adult women with normal body weight (n = 30), compared to doubly labeled water (DLW), a reference method for total daily energy expenditure (TDEE). Energy intake was also estimated using a one-day 24HR for direct comparison. Bland–Altman plots, paired difference tests, and Pearson’s correlation coefficient were used to assess agreement and relationships between the methods. SNAQ showed a slightly higher agreement (bias = −329.6 kcal/day) with DLW for total daily energy intake (TDEI) compared to 24HR (bias = −543.0 kcal/day). While both SNAQ and 24HR tended to underestimate TDEI, only 24HR significantly differed from DLW in this regard (p < 0.001). There was no significant relationship between estimated TDEI and TDEE using SNAQ (R2 = 27%, p = 0.50) or 24HR (R2 = 34%, p = 0.20) and there were no significant differences in energy and macronutrient intake estimates between SNAQ and 24HR (Δ = 213.4 kcal/day). In conclusion, these results indicate that SNAQ provides a closer representation of energy intake in adult women with normal body weight than 24HR when compared to DLW, but no relationship was found between the energy estimates of DLW and of the two dietary assessment tools. Further research is needed to determine the clinical relevance and support the implementation of SNAQ in research and clinical settings. Clinical trial registration: This study is registered on ClinicalTrials.gov with the unique identifier NCT04600596 (https://clinicaltrials.gov/ct2/show/NCT04600596).

Original languageEnglish
Article number1255499
JournalFrontiers in Nutrition
Volume10
DOIs
Publication statusPublished - 2023

Keywords

  • artificial intelligence
  • dietary assessment
  • dietary intake
  • doubly labelled water
  • energy intake
  • image-based food recognition
  • mHealth

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