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The electronic Dietary Intake Assessment (e-DIA), a digital entry food record mobile phone app, was developed to measure energy and nutrient intake prospectively. This can be used in monitoring population intakes or intervention studies in young adults.
The objective was to assess the relative validity of e-DIA as a dietary assessment tool for energy and nutrient intakes using the 24-hour dietary recall as a reference method.
University students aged 19 to 24 years recorded their food and drink intake on the e-DIA for five days consecutively and completed 24-hour dietary recalls on three random days during this 5-day study period. Mean differences in energy, macro-, and micronutrient intakes were evaluated between the methods using paired t tests or Wilcoxon signed-rank tests, and correlation coefficients were calculated on unadjusted, energy-adjusted, and deattenuated values. Bland-Altman plots and cross-classification into quartiles were used to assess agreement between the two methods.
Eighty participants completed the study (38% male). No significant differences were found between the two methods for mean intakes of energy or nutrients. Deattenuated correlation coefficients ranged from 0.55 to 0.79 (mean 0.68). Bland-Altman plots showed wide limits of agreement between the methods but without obvious bias. Cross-classification into same or adjacent quartiles ranged from 75% to 93% (mean 85%).
The e-DIA shows potential as a dietary intake assessment tool at a group level with good ranking agreement for energy and all nutrients.
The collection of accurate dietary consumption data is important in the field of nutritional epidemiology in order to establish true relationships between nutrition and health status. The food record (weighed or estimated portions) is a traditional method used to record amounts and types of foods and beverages consumed prospectively, thus limiting recall bias [
With 81% of Australians regularly using a mobile phone [
A number of commercial mobile phone apps such as MyFitnessPal and Lose It provide a platform for users to digitally record foods and beverages consumed and have these records integrated with food composition databases to calculate nutrients [
Students enrolled in a study aimed at assessing university students’ dietary intakes were invited to participate in this validation study. Recruitment methods for the larger study included email and poster advertisements on the university campus, which included a weblink to an online screening survey. Out of 313 students who completed the survey, 170 were eligible and 113 students were enrolled at an interview during which the study protocol was explained and written informed consent was obtained. From the enrolled students, 66 agreed to participate in the validation study and 57 completed both e-DIA and 24-hour dietary recalls from March to April 2014. To boost sample size, an additional 23 students were recruited in August 2014 by the same methods. This resulted in a final sample of 80 students (
Students downloaded the e-DIA app using an Android or iOS platform on their own mobile phone. To record intake, the user selects the meal occasion during which the food or beverage is consumed (breakfast, lunch, dinner, or other) which opens the Edit/Delete screen (
Flow chart of participant recruitment.
Screenshots of the electronic Dietary Intake Assessment (e-DIA) app.
At an initial clinic appointment on the university campus, anthropometric data were collected by the study investigators. Height was measured to the nearest 0.5 cm, weight to the nearest 0.1 kg (without heavy clothing or shoes), and waist circumference to the nearest 0.5 cm, according to the Anthropometry Procedures Manual from the National Health and Nutrition Examination Survey (National Center for Health Statistics, US Department of Health and Human Services) [
Participants were instructed to complete five consecutive days of food records including three weekdays and two weekend days using e-DIA. Participants practiced selecting and entering food items and weights, and written instructions were included on how to choose foods from the database, how to enter mixed recipes, and how to estimate portion sizes when eating away from home. Participants were asked to weigh foods using the scales supplied (Salter 1066WHDR); an instruction booklet was provided. If participants were unable to weigh the foods, they were instructed to estimate portion sizes using metric cups and spoons supplied. Starting days were staggered so that all days of the week were represented across the sample. Participants were sent a text message reminder prior to each collection day which encouraged them to maintain their usual diet.
As a reference measure, three 24-hour dietary recalls were collected on three random days (including weekend days) during the five-day study period. Appropriate calling times were established at the convenience of the participants. The standard 24-hour dietary recall interview multi-pass script adapted from the Five-Step Multiple-Pass Method by the US Department of Agriculture [
All entries were checked the following day by study investigators, and participants were contacted to clarify manually entered food items and obvious inconsistencies such as gross data entry errors and skipped meals.
Data collected using the e-DIA mobile web app were stored in a cloud-based database, and records were linked to food items in the AUSNUT 2007. If the nutrient composition of manually entered food items was known, study investigators added the information to the database; if unknown, investigators coded to the closest match. Food intake data from the 24-hour dietary recalls were manually entered by trained study investigators into FoodWorks 7 Premium [
Energy and nutrient intakes from the 24-hour dietary recalls and e-DIA were examined for outliers and checked against the original 24-hour dietary recall for obvious errors in data entry. Errors made by the participant in the e-DIA were left unaltered, and no outliers were removed to provide a more accurate indication of the relative validity of the e-DIA method. Vitamin and mineral supplements were excluded from analysis.
Mean or median intakes of energy and nutrients from three days of 24-hour dietary recalls and five days of e-DIA were calculated and differences determined using paired
A sample of 80 students (30 male) completed five days of e-DIA and three days of 24-hour dietary recalls (
Mean and median intakes of energy and nutrients reported by 24-hour dietary recall and e-DIA are shown in
Mean and median daily intakes of energy and nutrients measured by three days of 24-hour dietary recall (24HR) and five days of electronic Dietary Intake Assessment (e-DIA).
Energy and |
e-DIA | 24HR | Difference | ||
Mean (SD) | Median | Mean (SD) | Median | Mean (SD) | |
Energy, kJ | 8148.2 (2495.2) | 7699.1 | 8182.2 (2575.1) | 7625.4 | −34.3 (2090.3) |
Protein, g | 88.7 (33.5) | 86.7 | 91.3 (35.0) | 85.2 | −2.5 (22.5) |
Total fat, g | 74.6 (25.6) | 70.3 | 76.0 (31.4) | 68.6 | −1.4 (23.5) |
SFAa, g | 28.8 (11.8) | 26.4 | 30.1 (16.4) | 26.8 | −1.3 (10.8) |
MUFAb, g | 28.4 (10.9) | 26.5 | 28.7 (11.7) | 25.8 | −0.3 (9.8) |
PUFAc, g | 11.6 (4.4) | 11.2 | 11.4 (4.6) | 10.5 | 0.3 (4.5) |
Carbohydrate, g | 213.3 (82.6) | 204.8 | 209.0 (67.5) | 197.4 | 4.3 (70.1) |
Sugars, g | 80.1 (41.8) | 72.9 | 88.1 (50.4) | 78.3 | −8.0 (43.7) |
Starch, g | 130.5 (57.1) | 122.6 | 120.9 (46.9) | 114.7 | 9.6 (44.6) |
Fiber, g | 22.0 (8.0) | 21.5 | 21.5 (8.5) | 20.0 | 0.5 (7.9) |
Alcohol, g | 4.8 (10.7) | 0.1 | 3.9 (10.0) | 0.0 | 0.9 (4.7) |
Vitamin A REd, μg | 812.2 (961.5) | 634.4 | 866.0 (1403.3) | 653.1 | −53.8 (574.1) |
Thiamin, mg | 1.5 (1.0) | 1.3 | 1.5 (0.8) | 1.3 | 0.1 (0.9) |
Riboflavin, mg | 1.9 (0.9) | 1.9 | 2.1 (0.9) | 1.9 | −0.2 (0.6) |
Niacin, mg | 43.5 (18.5) | 42.3 | 45.8 (21.6) | 41.3 | −2.3 (16.5) |
Folate DFEe, μg | 343.2 (212.4) | 295.2 | 365.1 (232.8) | 313.9 | −21.9 (143.4) |
Vitamin C, mg | 90.7 (57.5) | 76.9 | 106.8 (89.7) | 88.4 | −16.1 (78.1) |
Vitamin E, mg | 8.6 (4.5) | 7.7 | 8.5 (3.9) | 7.9 | 0.1 (3.8) |
Calcium, mg | 705.4 (318.0) | 686.2 | 725.6 (317.7) | 658.4 | −22.0 (230.3) |
Iron, mg | 12.7 (9.3) | 11.4 | 12.1 (5.6) | 10.8 | 0.6 (7.5) |
Zinc, mg | 11.3 (7.1) | 10.0 | 11.2 (4.6) | 10.5 | 0.2 (6.7) |
Magnesium, mg | 333.1 (133.7) | 311.4 | 323.4 (106.8) | 312.4 | 10.0 (100.2) |
Phosphorus, mg | 1403.0 (511.6) | 1388.1 | 1383.9 (470.8) | 1324.2 | 18.6 (321.9) |
Sodium, mg | 2712.3 (1480.0) | 2375.5 | 2561.5 (952.4) | 2433.3 | 151.0 (1234.7) |
Potassium, mg | 2701.1 (1003.9) | 2679.2 | 2732.1 (801.3) | 2632.6 | −31.3 (768.5) |
aSFA: saturated fatty acids
bMUFA: monounsaturated fatty acids
cPUFA: polyunsaturated fatty acids
dRE: retinol equivalents
eDFE: dietary folate equivalents
Quartile cross-classification of nutrients with the 24-hour dietary recalls and e-DIA placed 75% to 93% (mean 85%) of the participants into the same or adjacent quartile, with the highest ranking agreement for fiber and the lowest for iron. Cross-classification into extreme quartiles ranged from 0% to 9% (mean 1%) with monounsaturated fatty acids (MUFA), thiamine, and iron having the greatest proportion of extreme misclassification.
Correlation coefficients and cross-classification of energy and nutrients between three days of 24-hour dietary recall and five days of electronic Dietary Intake Assessment.
Energy and |
Correlation coefficientsa,b | Cross-classification into quartilesc | ||||
|
Unadjusted | Energy- |
De- |
Same | Same or |
Extreme |
Energy, kJ | 0.66 | — | 0.68 | 38 | 81 | 0 |
Protein, g | 0.79 | 0.77 | 0.79 | 58 | 87 | 1 |
Total fat, g | 0.68 | 0.71 | 0.69 | 41 | 81 | 5 |
SFAd, g | 0.75 | 0.78 | 0.76 | 46 | 91 | 0 |
MUFAe, g | 0.62 | 0.62 | 0.64 | 45 | 79 | 6 |
PUFAf, g | 0.50 | 0.43 | 0.55 | 46 | 82 | 2 |
Carbohydrate, g | 0.64 | 0.75 | 0.67 | 49 | 87 | 2 |
Sugars, g | 0.56 | 0.57 | 0.62 | 48 | 84 | 0 |
Starch, g | 0.65 | 0.65 | 0.72 | 46 | 89 | 2 |
Fiber, g | 0.54 | 0.63 | 0.64 | 59 | 93 | 1 |
Alcohol, g | 0.77 | 0.69 | 0.62 | 44 | 88 | 1 |
Vitamin A REg, μg | 0.61 | 0.66 | 0.61 | 49 | 88 | 4 |
Thiamin, mg | 0.61 | 0.40 | 0.66 | 35 | 79 | 9 |
Riboflavin, mg | 0.77 | 0.70 | 0.76 | 45 | 90 | 0 |
Niacin, mg | 0.69 | 0.58 | 0.71 | 53 | 83 | 2 |
Folate DFEh, μg | 0.69 | 0.72 | 0.71 | 58 | 89 | 2 |
Vitamin C, mg | 0.68 | 0.71 | 0.75 | 56 | 89 | 0 |
Vitamin E, mg | 0.53 | 0.60 | 0.56 | 40 | 85 | 1 |
Calcium, mg | 0.75 | 0.57 | 0.72 | 40 | 80 | 2 |
Iron, mg | 0.57 | 0.42 | 0.61 | 34 | 75 | 6 |
Zinc, mg | 0.69 | 0.54 | 0.70 | 49 | 82 | 2 |
Magnesium, mg | 0.71 | 0.69 | 0.72 | 48 | 88 | 0 |
Phosphorus, mg | 0.76 | 0.69 | 0.78 | 53 | 87 | 1 |
Sodium, mg | 0.60 | 0.59 | 0.60 | 48 | 88 | 5 |
Potassium, mg | 0.64 | 0.68 | 0.68 | 59 | 92 | 2 |
aPearson correlation coefficients used for energy and macronutrients; Spearman rank correlation coefficients used for alcohol and micronutrients.
bAll correlations were significant (
cBased on energy-adjusted data.
dSFA: saturated fatty acids
eMUFA: monounsaturated fatty acids
fPUFA: polyunsaturated fatty acids
gRE: retinol equivalents
hDFE: dietary folate equivalents
Bland-Altman plots illustrating the agreement between the 24-hour dietary recalls and e-DIA for energy and selected nutrient intakes are shown in
Bland-Altman plot of 24-hour dietary recalls (24HR) and electronic Dietary Intake Assessment (e-DIA) for energy intake.
Bland-Altman plot of 24-hour dietary recalls (24HR) and electronic Dietary Intake Assessment (e-DIA) for protein intake.
Bland-Altman plot of 24-hour dietary recalls (24HR) and electronic Dietary Intake Assessment (e-DIA) for carbohydrate intake.
Bland-Altman plot of 24-hour dietary recalls (24HR) and electronic Dietary Intake Assessment (e-DIA) for fat intake.
Bland-Altman plot of 24-hour dietary recalls (24HR) and electronic Dietary Intake Assessment (e-DIA) for saturated fat intake.
This study is the first to compare the energy and nutrient intakes using a mobile phone food diary app with 24-hour dietary recall as reference measure using an Australian food composition database. Mean intakes of energy and all nutrients were similar in both methods, with no consistently higher or lower values for either method. Correlation coefficients were moderate to strong ranging from 0.55 to 0.78. Cross-classification into quartiles revealed good agreement for energy and all nutrients. In addition Bland-Altman plots showed robust agreement between the e-DIA and 24-hour dietary recalls for energy and all nutrients, without bias and with most data points located within two standard deviations of the mean. The wide limits of agreement suggest that e-DIA is unsuitable to accurately estimate intake at an individual level. However, collectively the results suggest the potential of e-DIA as an assessment tool for dietary analysis at the population level.
These findings are consistent with those of other researchers. Carter et al recently validated a mobile phone app (My Meal Mate) designed to support weight loss [
Mobile phones are also being used for digital imaging to record food and beverage intake [
Although the use of 24-hour dietary recall was the preferred choice of reference method, it introduces several limitations to the study design. Reliance on memory is a well-documented limitation with participants likely to forget foods consumed the previous day, although the use of the multiple pass method and portion size aids are designed to minimize the impact of errors related to memory. As the 24-hour dietary recall was administered on days that the participants digitally recorded their food records into the e-DIA, there was potential for the recording process to have improved their recall of food and beverages. However, it should be noted that records were deleted from the app at midnight and recalls were conducted up to 22 hours after their deletion. As both methods relied on self-report, more objective measures of dietary intake such as biomarkers are needed to further validate the e-DIA.
Compared with the 2011-2012 Australian Health Survey [
The use of the e-DIA also has limitations, including the burden of recording foods prospectively for a prolonged period of time and trouble navigating within the e-DIA tool itself. When entering a food into the e-DIA, participants were presented with a long list of food options that was challenging to navigate. However, the presence of the favorites function relieves some of this burden by prioritizing the food options according to individual preferences. Commercial apps may have shorter lists but this is likely to result in less accurate food records and resulting nutrient intakes.
One of the main strengths of the study is the ability of e-DIA to collect dietary intake data without alerting the participants to their ongoing caloric intake. The app is linked to the Australian national food composition database compiled by Food Standards Australia New Zealand which consists of over 4500 foods [
This validation study demonstrated good agreement between the e-DIA and 24-hour dietary recalls at a group level, and no evidence of bias for energy, macro-, and micronutrients was noted. With the growing popularity of mobile phones among young adults this method of collecting dietary intake is highly acceptable in this population group. Future studies should explore the validity of the e-DIA in larger, more representative samples and employ external biomarkers to reflect usual intakes. Studies assessing the e-DIA’s sensitivity to changes in dietary intake are also required. This would confirm its value as a tool to monitor dietary intake in intervention studies in public health and clinical trials.
24-hour dietary recall
Australian Food, Supplement, and Nutrient Database
body mass index
electronic Dietary Intake Assessment
monounsaturated fatty acids
personal digital assistant
We would like to thank the participants in the validation study as well as the research students involved in the original validation and diet quality studies. This research was partly supported by funding from the Faculty of Engineering and Information Technologies, The University of Sydney, under the Faculty Research Cluster Program.
MAF, JK, LMT, JL, and RR developed the app; SOC, VG, MY, RR, JL, LH, and AR were involved in data collection; AR analyzed the data and drafted the manuscript; and all authors were involved in editing the final draft and approving the manuscript.
None declared.