Preference, Expected Burden, and Willingness to Use Digital and Traditional Methods to Assess Food and Alcohol Intake

We conducted an online survey to examine the preference, expected burden, and willingness of people to use four different methods of assessing food and alcohol intake such as food/drink record, 24-h recall, Remote Food Photography Method© (RFPM, via SmartIntake® app), and a novel app (PortionSize®) that allows the in-app portion size estimation of foods/drinks by the user. For food (N = 1959) and alcohol (N = 466) intake assessment, 67.3% and 63.3%, respectively, preferred the RFPM/SmartIntake®, 51.9% and 53.4% preferred PortionSize®, 48.0% and 49.3% the food records, and 32.9% and 33.9% the 24-h recalls (difference in preference across all methods was p < 0.001 for food and alcohol intake). Ratings of burden and preference of methods were virtually superimposable, and we found strong correlations between high preference and low expected burden for all methods (all ρ ≥ 0.82; all p < 0.001). Willingness (mean (SD)) to use the RFPM/SmartIntake® (food: 6.6 (2.0); alcohol: 6.4 (2.4)) was greater than PortionSize® (food: 6.0 (2.2); alcohol: 6.0 (2.4); all p < 0.001) and 24-h recalls (food: 6.1 (2.2); alcohol: 5.7 (2.7); p < 0.001), but not different from food records (food: 6.6 (2.0); alcohol: 6.5 (2.3); all p ≥ 0.33). Our results can be used in conjunction with existing data on the reliability and validity of these methods in order to inform the selection of methods for the assessment of food and alcohol intake.

Development and evaluation of image-series for portion size estimation in dietary assessment among adults

Portion size images are advantageous in dietary assessment. The aim of the present study was to develop and validate new culturally specific image-series for portion size estimation to be used in a new Norwegian version of a British web-based dietary assessment tool (myfood24). Twenty-three image-series of different foods, each containing seven portion size images, were created and validated in a group of adults (n 41, 58 % female) aged 19–44 (median 23), out of which 63 % had higher (tertiary) education. The participants compared 46 portions of pre-weighed foods to the portion size images (1886 comparisons in total). Portion size estimations were either classified as correct, adjacent or misclassified. The weight discrepancy in percentage between the chosen and the correct portion size image was also calculated. Mann–Whitney U tests were used to explore if portion size estimation accuracy differed across sample characteristics, or if it depended on how the foods were presented. For thirty-eight of the forty-six presented food items, the participants selected the correct or adjacent portion size image 98 % on average. The remaining eight food items were on average misclassified by 27 % of the participants. Overall, a mean weight discrepancy of 2⋅5 % was observed between the chosen and the correct portion size images. Females estimated portion size more accurately than males (P = 0⋅019). No other significant differences in estimation accuracy were observed. In conclusion, the new image-series performed satisfactorily, except for the image-series depicting bread, caviar spread and marzipan cake, which will be altered. The present study demonstrates the importance of validating portion size estimation tools.

Integrating nutrition into the mathematics curriculum in Australian primary schools: protocol for a randomised controlled trial

Background Nutrition education programs in schools have been effective in improving children’s knowledge and behaviours related to food and nutrition. However, teachers find it challenging to implement such programs due to overcrowded curricula. Integrating nutrition with core subjects such as mathematics could potentially address time constraints and improve the learning of both. The primary aim of this randomized controlled trial (RCT) is to evaluate the impact of a cross-curricular nutrition and mathematics program on primary school students’ portion size estimation skills. Secondary aims include impact on their nutrition knowledge, attitudes towards mathematics and evaluating the quality of the lessons. Methods Twelve Year 3–4 classes from Catholic schools in New South Wales, Australia will be randomised to intervention (n = 6) or control (n = 6) groups. Teachers in the intervention group will receive a professional development workshop and resources to teach 4–5 lessons on portion size and measurements across 1–4 weeks. Outcome measures include portion size estimation skills, nutrition knowledge and attitudes towards mathematics, with data collected during three school visits (pre-intervention, immediately post-intervention, 4 weeks post-intervention). Additionally, teaching quality will be assessed in both intervention and control groups and process evaluation undertaken using teacher interviews and student focus groups. Discussion This RCT uses an innovative approach to improve both nutrition and mathematics related learning outcomes among primary school children. It has the potential to impact teaching practices regarding integration of nutrition into curricula and enhance the implementation of nutrition education interventions. Trial registration Australian and New Zealand Clinical Trials Register ACTRN12619001071112 31/07/2019.

An evaluation of a virtual atlas of portion sizes (VAPS) mobile augmented reality for portion size estimation

Food portion size estimation is a critical yet challenging task in dietary assessment. Augmented reality technology enables the presentation of food dimensions and volume in a virtual three-dimensional object. It has the potential to improve perception and estimation of portion sizes. This study aims to develop and evaluate a novel mobile augmented reality application, namely Virtual Atlas of Portion Sizes (VAPS), as a portion size estimation aid. The development methodology of VAPS involves food photography, reconstruction of 3D models using photogrammetry method and presenting them in an AR environment. The 3D food models displayed in either semi-transparent or vivid mode for users to perform food portion estimation. Users can then resize and rotate the 3D models to fit the virtual model with the actual food. A total of thirty-six participants were involved in the evaluation and were divided into a health science and a non-health science background group. VAPS received good usability level with 76 SUS score. In terms of task completion time, unsurprisingly, the health science group performed faster. However, both groups have equivalent accuracy on the food portion estimation task using VAPS: 22.5% for non-health science group and 26.6% for health science group. The health science group liked and have better accuracy in vivid 3D food models (37.5%). Meanwhile, the non-health science group preferred semi-transparent 3D food models, but the accuracy is not significantly different between semi-transparent (25%) and vivid 3D food model (20%). Results demonstrate the potential of VAPS to aid in portion size estimation for dietary assessment, and participants’ feedback will be incorporated in the future for improvement of the app.

Progressive 24-Hour Recall: Usability Study of Short Retention Intervals in Web-Based Dietary Assessment Surveys

Background Under-reporting because of the limitations of human memory is one of the key challenges in dietary assessment surveys that use the multiple-pass 24-hour recall. Research indicates that shortening a retention interval (ie, the time between the eating event and recall) reduces the burden on memory and may increase the accuracy of the assessment. Objective This study aimed to explore the accuracy and acceptability of Web-based dietary assessment surveys based on a progressive recall, where a respondent is asked to record multiple recalls throughout a 24-hour period using the multiple-pass protocol and portion size estimation methods of the 24-hour recall. Methods The experiment was conducted with a dietary assessment system, Intake24, that typically implements the multiple-pass 24-hour recall method where respondents record all meals they had for the previous day on a single occasion. We modified the system to allow respondents to add multiple recalls throughout the day using the multiple-pass protocol and portion size estimation methods of the 24-hour recall (progressive recall). We conducted a dietary assessment survey with 33 participants, where they were asked to record dietary intake using both 24-hour and progressive recall methods for weekdays only. We compared mean retention intervals (ie, the time between eating event and recall) for the 2 methods. To examine accuracy, we compared mean energy estimates and the mean number of reported foods. Of these participants, 23 were interviewed to examine the acceptability of the progressive recall. Results Retention intervals were found to be, on average, 15.2 hours (SD 7.8) shorter during progressive recalls than those during 24-hour recalls. We found that the mean number of foods reported for evening meals for progressive recalls (5.2 foods) was significantly higher (P=.001) than that for 24-hour recalls (4.2 foods). The number of foods and the amount of energy reported for other meals remained similar across the 2 methods. In interviews, 65% (15/23) of participants said that the 24-hour recall is more convenient in terms of fitting in with their daily lifestyles, and 65% (15/23) of respondents indicated that they remembered meal content and portion sizes better with the progressive recall. Conclusions The analysis of interviews and data from our study indicate that progressive recalls provide minor improvements to the accuracy of dietary assessment in Intake24. Additional work is needed to improve the acceptability of progressive recalls in this system.