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Image-based dietary records have been validated as tools to evaluate dietary intake. However, to determine meal timing, previous studies have relied primarily on image-based smartphone applications without validation. Noteworthy, the validation process is necessary to determine how accurately a test method measures meal timing compared with a reference method over the same time period. Thus, we aimed to assess the relative validity and reliability of the Remind® app as an image-based method to assess dietary intake and meal timing. For this purpose, 71 young adults (aged 20–33 years, 81.7% women) were recruited for a 3-day cross-sectional study, where they completed a 3-day image-based record using the Remind app (test method) and a 3-day handwritten food record (reference method). The relative validity of the test method versus the reference method was assessed using multiple tests including Bland–Altman, % difference, paired t-test/Wilcoxon signed-rank test, Pearson/Spearman correlation coefficients, and cross-classification. We also evaluated the reliability of the test method using an intra-class correlation (ICC) coefficient. The results showed that, compared to the reference method, the relative validity of the test method was good for assessing energy and macronutrient intake, as well as meal timing. Meanwhile, the relative validity of the test method to assess micronutrient intake was poor (p < 0.05) for some micronutrients (iron, phosphorus, potassium, zinc, vitamins B1, B2, B3, B6, C, and E, and folates) and some food groups (cereals and grains, legumes, tubers, oils, and fats). Regarding the reliability of an image-based method to assess dietary intake and meal timing, results ranged from moderate to excellent (ICC 95% confidence interval [95% CI]: 0.50–1.00) for all nutrients, food groups (except oils and fats, which had low to moderate reliability), and meal timings. Thus, the results obtained in this study provide evidence of the relative validity and reliability of image-based methods to assess dietary intake (energy, macronutrients, and most food groups) and meal timing. These results open up a new framework for chrononutrition, as these methods improve the quality of the data collected and also reduce the burden on users to accurately estimate portion size and the timing of meals.

Image-based dietary records have limited evidence evaluating their performance and use among adults with a chronic disease. This study evaluated the performance of a 3-day mobile phone image-based dietary record, the Nutricam Dietary Assessment Method (NuDAM), in adults with type 2 diabetes mellitus (T2DM). Criterion validity was determined by comparing energy intake (EI) with total energy expenditure (TEE) measured by the doubly-labelled water technique. Relative validity was established by comparison to a weighed food record (WFR). Inter-rater reliability was assessed by comparing estimates of intake from three dietitians. Ten adults (6 males, age: 61.2 ± 6.9 years old, BMI: 31.0 ± 4.5 kg/m2) participated. Compared to TEE, mean EI (MJ/day) was significantly under-reported using both methods, with a mean ratio of EI:TEE 0.76 ± 0.20 for the NuDAM and 0.76 ± 0.17 for the WFR. Correlations between the NuDAM and WFR were mostly moderate for energy (r = 0.57), carbohydrate (g/day) (r = 0.63, p < 0.05), protein (g/day) (r = 0.78, p < 0.01) and alcohol (g/day) (rs = 0.85, p < 0.01), with a weaker relationship for fat (g/day) (r = 0.24). Agreement between dietitians for nutrient intake for the 3-day NuDAM (Intra-class Correlation Coefficient (ICC) = 0.77–0.99) was lower when compared with the 3-day WFR (ICC = 0.82–0.99). These findings demonstrate the performance and feasibility of the NuDAM to assess energy and macronutrient intake in a small sample. Some modifications to the NuDAM could improve efficiency and an evaluation in a larger group of adults with T2DM is required.

Image-based dietary assessment (IBDA) may improve the accuracy of dietary assessments, but no formalized training currently exists for skills relating to IBDA. This study investigated nutrition and dietetics students’ and interns’ IBDA abilities, the training and experience factors that may contribute to food identification and quantification accuracy, and the perceived challenges to performing IBDA. An online survey containing images of known foods and serving sizes representing common American foods was used to assess the ability to identify foods and serving sizes. Nutrition and dietetics students and interns from the United States and Australia (n = 114) accurately identified foods 79.5% of the time. Quantification accuracy was lower, with only 38% of estimates within ±10% of the actual weight. Foods of amorphous shape or higher energy density had the highest percent error. Students expressed general difficulty with perceiving serving sizes, making IBDA food quantification more difficult. Experience cooking at home from a recipe, frequent measuring of portions, and having a food preparation or cooking laboratory class were associated with enhanced accuracy in IBDA. Future training of dietetics students should incorporate more food-based serving size training to improve quantification accuracy while performing IBDA, while advances in IBDA technology are also needed.

Image-based dietary records could lower participant burden associated with traditional prospective methods of dietary assessment. They have been used in children, adolescents and adults, but have not been evaluated in pregnant women. The current study evaluated relative validity of the DietBytes image-based dietary assessment method for assessing energy and nutrient intakes. Pregnant women collected image-based dietary records (via a smartphone application) of all food, drinks and supplements consumed over three non-consecutive days. Intakes from the image-based method were compared to intakes collected from three 24-h recalls, taken on random days; once per week, in the weeks following the image-based record. Data were analyzed using nutrient analysis software. Agreement between methods was ascertained using Pearson correlations and Bland-Altman plots. Twenty-five women (27 recruited, one withdrew, one incomplete), median age 29 years, 15 primiparas, eight Aboriginal Australians, completed image-based records for analysis. Significant correlations between the two methods were observed for energy, macronutrients and fiber (r = 0.58–0.84, all p < 0.05), and for micronutrients both including (r = 0.47–0.94, all p < 0.05) and excluding (r = 0.40–0.85, all p < 0.05) supplements in the analysis. Bland-Altman plots confirmed acceptable agreement with no systematic bias. The DietBytes method demonstrated acceptable relative validity for assessment of nutrient intakes of pregnant women.