The relative validity of a food record using the smartphone application MyFitnessPal (original) (raw)
Related papers
JMIR mHealth and uHealth, 2019
Background: More alternatives are needed for recording people's normal diet in different populations, especially adults or the elderly, as part of the investigation into the effects of nutrition on health. Objective: The aim of this study was to compare the estimated values of energy intake, macro-and micronutrient, and alcohol consumption gathered using the EVIDENT II smartphone app against the data estimated with a food frequency questionnaire (FFQ) in an adult population aged 18 to 70 years. Methods: We included 362 individuals (mean age 52 years, SD 12; 214/362, 59.1% women) who were part of the EVIDENT II study. The participants registered their food intake using the EVIDENT app during a period of 3 months and through an FFQ. Both methods estimate the average nutritional composition, including energy intake, macro-and micronutrients, and alcohol. Through the app, the values of the first week of food recording, the first month, and the entire 3-month period were estimated. The FFQ gathers data regarding the food intake of the year before the moment of interview. Results: The intraclass correlation for the estimation of energy intake with the FFQ and the app shows significant results, with the highest values returned when analyzing the app's data for the full 3-month period (.304, 95% CI 0.144-0.434; P<.001).
The British journal of nutrition, 2016
Automation of dietary assessment can reduce limitations of established methodologies, by alleviating participant and researcher burden. Designed as a research tool, the electronic Dietary Intake Assessment (e-DIA) is a food record in mobile phone application format. The present study aimed to examine the relative validity of the e-DIA with the 24-h recall method to estimate intake of food groups. A sample of eighty university students aged 19-24 years recorded 5 d of e-DIA and 3 d of recall within this 5-d period. The three matching days of dietary data were used for analysis. Food intake data were disaggregated and apportioned to one of eight food groups. Median intakes of food groups were similar between the methods, and strong correlations were found (mean: 0·79, range: 0·69-0·88). Cross-classification by tertiles produced a high level of exact agreement (mean: 71 %, range: 65-75 %), and weighted κ values were moderate to good (range: 0·54-0·71). Although mean differences (e-DIA-...
Nutrition Journal, 2010
We have developed a food frequency questionnaire (FFQ) for the assessment of habitual diet, with special focus on the intake of fruit, vegetables and other antioxidant-rich foods and beverages. The aim of the present study was to evaluate the relative validity of the intakes of energy, food and nutrients from the FFQ. Methods: Energy intake was evaluated against independent measures of energy expenditure using the ActiReg® system (motion detection), whereas 7-days weighed food records were used to study the relative validity of food and nutrient intake. The relationship between methods was investigated using correlation analyses and crossclassification of participants. The visual agreement between the methods was evaluated using Bland-Altman plots.
2014
Background: Advances in nutritional assessment are continuing to embrace developments in computer technology. The online Food4Me food frequency questionnaire (FFQ) was created as an electronic system for the collection of nutrient intake data. To ensure its accuracy in assessing both nutrient and food group intake, further validation against data obtained using a reliable, but independent, instrument and assessment of its reproducibility are required. Objective: The aim was to assess the reproducibility and validity of the Food4Me FFQ against a 4-day weighed food record (WFR). Methods: Reproducibility of the Food4Me FFQ was assessed using test-retest methodology by asking participants to complete the FFQ on 2 occasions 4 weeks apart. To assess the validity of the Food4Me FFQ against the 4-day WFR, half the participants were also asked to complete a 4-day WFR 1 week after the first administration of the Food4Me FFQ. Level of agreement between nutrient and food group intakes estimated by the repeated Food4Me FFQ and the Food4Me FFQ and 4-day WFR were evaluated using Bland-Altman methodology and classification into quartiles of daily intake. Crude unadjusted correlation coefficients were also calculated for nutrient and food group intakes. Results: In total, 100 people participated in the assessment of reproducibility (mean age 32, SD 12 years), and 49 of these (mean age 27, SD 8 years) also took part in the assessment of validity. Crude unadjusted correlations for repeated Food4Me FFQ ranged from .65 (vitamin D) to .90 (alcohol). The mean cross-classification into "exact agreement plus adjacent" was 92% for both nutrient and food group intakes, and Bland-Altman plots showed good agreement for energy-adjusted macronutrient intakes. Agreement between the Food4Me FFQ and 4-day WFR varied, with crude unadjusted correlations ranging from .23 (vitamin D) to .65 (protein, % total energy) for nutrient intakes and .11 (soups, sauces and miscellaneous foods) to .73 (yogurts) for food group intake. The mean cross-classification into "exact agreement plus adjacent" was 80% and 78% for nutrient and food group intake, respectively. There were no significant differences between energy intakes estimated using the Food4Me FFQ and 4-day WFR, and Bland-Altman plots showed good agreement for both energy and energy-controlled nutrient intakes.
Endocrinologia, diabetes y nutricion, 2018
Several instruments developed to assess dietary intake of groups or populations have strengths and weaknesses that affect their specific application. No self-administered, closed-ended dietary survey was previously used in Argentina to assess current food and nutrient intake on a daily basis. To design and validate a self-administered, structured food record (NutriQuid, NQ) representative of the adult Argentine population's food consumption pattern to measure individual energy and nutrient intake. Records were loaded onto a database using software that checks a regional nutrition information system (SARA program), automatically quantifying energy and nutrient intake. NQ validation included two phases: (1) NQ construct validity comparing records kept simultaneously by healthy volunteers (45-75 years) and a nutritionist who provided meals (reference), and (2) verification of whether NQ reflected target population consumption (calories and nutrients), week consumption differences, ...
Performance of the Digital Dietary Assessment Tool MyFoodRepo
Nutrients, 2022
Digital dietary assessment devices could help overcome the limitations of traditional tools to assess dietary intake in clinical and/or epidemiological studies. We evaluated the accuracy of the automated dietary app MyFoodRepo (MFR) against controlled reference values from weighted food diaries (WFD). MFR’s capability to identify, classify and analyze the content of 189 different records was assessed using Cohen and uniform kappa coefficients and linear regressions. MFR identified 98.0% ± 1.5 of all edible components and was not affected by increasing numbers of ingredients. Linear regression analysis showed wide limits of agreement between MFR and WFD methods to estimate energy, carbohydrates, fat, proteins, fiber and alcohol contents of all records and a constant overestimation of proteins, likely reflecting the overestimation of portion sizes for meat, fish and seafood. The MFR mean portion size error was 9.2% ± 48.1 with individual errors ranging between −88.5% and +242.5% compa...
An Italian Case Study for Assessing Nutrient Intake through Nutrition-Related Mobile Apps
Nutrients
National food consumption surveys are crucial for monitoring the nutritional status of individuals, defining nutrition policies, estimating dietary exposure, and assessing the environmental impact of the diet. The methods for conducting them are time and resource-consuming, so they are usually carried out after extended periods of time, which does not allow for timely monitoring of any changes in the population’s dietary patterns. This study aims to compare the results of nutrition-related mobile apps that are most popular in Italy, with data obtained with the dietary software Foodsoft 1.0, which was recently used in the Italian national dietary survey IV SCAI. The apps considered in this study were selected according to criteria, such as popularity (downloads >10,000); Italian language; input characteristics (daily dietary recording ability); output features (calculation of energy and macronutrients associated with consumption), etc. 415 apps in Google Play and 226 in the iTunes...
2018
Background: Nutrition-related apps are commonly used to provide information about the user's dietary intake, but limited research has been performed to assess how well their outputs agree with those from standard methods. Objective: The objective of our study was to evaluate the level of agreement of popular nutrition-related apps for the assessment of energy and available macronutrients and micronutrients against a UK reference method. Methods: We compared dietary analysis of 24-hour weighed food records (n=20) between 5 nutrition-related apps (Samsung Health, MyFitnessPal, FatSecret, Noom Coach, and Lose It!) and Dietplan6 (reference method), using app versions available in the United Kingdom. We compared estimates of energy, macronutrients (carbohydrate, protein, fat, saturated fat, and fiber), and micronutrients (sodium, calcium, iron, vitamin A, and vitamin C) using paired t tests and Wilcoxon signed-rank tests, correlation coefficients, and Bland-Altman plots. We obtained 24-hour weighed food records from 20 participants (15 female, 5 male participants; mean age 36.3 years; mean body mass index 22.9 kg/m 2) from previous controlled studies conducted at the
Popular Nutrition-Related Mobile Apps: An Agreement Assessment Against a UK Reference Method
JMIR mHealth and uHealth, 2019
Background: Nutrition-related apps are commonly used to provide information about the user's dietary intake, but limited research has been performed to assess how well their outputs agree with those from standard methods. Objective: The objective of our study was to evaluate the level of agreement of popular nutrition-related apps for the assessment of energy and available macronutrients and micronutrients against a UK reference method. Methods: We compared dietary analysis of 24-hour weighed food records (n=20) between 5 nutrition-related apps (Samsung Health, MyFitnessPal, FatSecret, Noom Coach, and Lose It!) and Dietplan6 (reference method), using app versions available in the United Kingdom. We compared estimates of energy, macronutrients (carbohydrate, protein, fat, saturated fat, and fiber), and micronutrients (sodium, calcium, iron, vitamin A, and vitamin C) using paired t tests and Wilcoxon signed-rank tests, correlation coefficients, and Bland-Altman plots. We obtained 24-hour weighed food records from 20 participants (15 female, 5 male participants; mean age 36.3 years; mean body mass index 22.9 kg/m 2) from previous controlled studies conducted at the
Online Dietary Intake Estimation: The Food4Me Food Frequency Questionnaire
Journal of Medical Internet Research, 2014
Background: Dietary assessment methods are important tools for nutrition research. Online dietary assessment tools have the potential to become invaluable methods of assessing dietary intake because, compared with traditional methods, they have many advantages including the automatic storage of input data and the immediate generation of nutritional outputs. Objective: The aim of this study was to develop an online food frequency questionnaire (FFQ) for dietary data collection in the "Food4Me" study and to compare this with the validated European Prospective Investigation of Cancer (EPIC) Norfolk printed FFQ. Methods: The Food4Me FFQ used in this analysis was developed to consist of 157 food items. Standardized color photographs were incorporated in the development of the Food4Me FFQ to facilitate accurate quantification of the portion size of each food item. Participants were recruited in two centers (Dublin, Ireland and Reading, United Kingdom) and each received the online Food4Me FFQ and the printed EPIC-Norfolk FFQ in random order. Participants completed the Food4Me FFQ online and, for most food items, participants were requested to choose their usual serving size among seven possibilities from a range of portion size pictures. The level of agreement between the two methods was evaluated for both nutrient and food group intakes using the Bland and Altman method and classification into quartiles of daily intake. Correlations were calculated for nutrient and food group intakes. Results: A total of 113 participants were recruited with a mean age of 30 (SD 10) years (40.7% male, 46/113; 59.3%, 67/113 female). Cross-classification into exact plus adjacent quartiles ranged from 77% to 97% at the nutrient level and 77% to 99% at the food group level. Agreement at the nutrient level was highest for alcohol (97%) and lowest for percent energy from polyunsaturated fatty acids (77%). Crude unadjusted correlations for nutrients ranged between .43 and .86. Agreement at the food group level was highest for "other fruits" (eg, apples, pears, oranges) and lowest for "cakes, pastries, and buns". For food groups, correlations ranged between .41 and .90. Conclusions: The results demonstrate that the online Food4Me FFQ has good agreement with the validated printed EPIC-Norfolk FFQ for assessing both nutrient and food group intakes, rendering it a useful tool for ranking individuals based on nutrient and food group intakes.