‘My Meal Mate’ (MMM): validation of the diet measures captured on a smartphone application to facilitate weight loss

Carter, Michelle C.; Burley, Victoria J.; Nykjaer, Camilla; Cade, Janet

doi:10.1017/s0007114512001353

Cited by 134 publications

(212 citation statements)

References 20 publications

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“…The present study aimed to validate the diet measures recorded on MMM against a reference measure of 24 h dietary recalls. wide; however, at the group level, MMM appears to have potential as a dietary assessment tool [16]. The Luxembourgian MENSSANA project, instead, is a new telemedicine tool developed for allergy patients and allergists.…”

Section: -Nutritionmentioning

confidence: 99%

Smartphones and Health Promotion: A Review of the Evidence

et al. 2013

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ObjectivesCommunication via mobile phones has become an essential tool for health professionals. The latest generation of smartphones is comparable to computers, allowing the development of new applications in health field. This paper aims to describe the use of smartphones by health professionals and patients in the field of health promotion. MethodsWe conducted a bibliographic search through Pubmed. Then, research results were analyzed critically in order to select the best experiences available. All searches were carried out on November 2012 and were not limited by date. Each item from the initial search was reviewed independently by members of the project team. ResultsInitial search returned 472 items with PubMed. After the removal of duplicates, 406 items were reviewed by all the members of the project team and 21 articles were identified as specifically centered on health promotion. In the nutrition field there are applications that allow to count calories and keep a food diary or more specific platforms for people with food allergies, while about physical activity many applications suggest exercises with measurement of sports statistics. Some applications deal with lifestyles suggestions and tips. Finally, some positive experiences are reported in the prevention of falls in elderly and of sexually-transmitted diseases. ConclusionsSmartphones are transforming the ways of communication but the lack of monitoring of contents, the digital divide, the confidentiality of data, the exclusion of the health professional from the management of patient, are the main risks related to their use.

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Section: -Nutritionmentioning

confidence: 99%

Smartphones and Health Promotion: A Review of the Evidence

et al. 2013

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“…Statistics show their use/ ownership is increasing among a variety of age groups and they are usually carried by the individual, enabling users to record data conveniently and discretely in real-time (26,52,53) . App for tracking dietary intake can be solely dietary based or integrated into other app such as physical activity app e.g.…”

Section: Mobile Methods Of Dietary Assessmentmentioning

confidence: 99%

“…The digital revolution has evolved the process in which dietary assessment methods are administered and dietary intakes are measured, resulting in a rise in the development of new technology-based instruments for assessing dietary intakes (23)(24)(25)(26)(27)(28) . These new instruments can be broadly categorised into three key areas: online (webbased) methods; mobile methods; sensor technologies.…”

Section: New Technologies For Dietary Assessmentmentioning

confidence: 99%

Personalised nutrition: the role of new dietary assessment methods

et al. 2015

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Food records or diaries, dietary recalls and FFQ are methods traditionally used to measure dietary intake; however, advancing technologies and growing awareness in personalised health have heightened interest in the application of new technologies to assess dietary intake. Dietary intake data can be used in epidemiology, dietary interventions and in the delivery of personalised nutrition advice. Compared with traditional dietary assessment methods, new technologies have many advantages, including their ability to automatically process data and provide personalised dietary feedback advice. This review examines the new technologies presently under development for the assessment of dietary intakes, and their utilisation and efficacy for personalising dietary advice. New technology-based methods of dietary assessment can broadly be categorised into three key areas: online (web-based) methods, mobile methods and sensor technologies. Several studies have demonstrated that utilising new technologies to provide tailored advice can result in positive dietary changes and have a significant impact on selected nutrient and food group intakes. However, comparison across studies indicates that the magnitude of change is variable and may be influenced by several factors, including the frequency and type of feedback provided. Future work should establish the most effective combinations of these factors in facilitating dietary changes across different population groups.

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“…However, this form of dietary assessment has yet to be validated and wholly accepted by healthcare providers to confidently recommend its use. Known limitations of these apps include limited nutrient data, particularly micronutrients, and inaccurate nutrient compositions [1], [6]. Despite this, reported nutrition app use in dietetic practice in the UK, New Zealand and Australia (5% response rate from the practitioners contacted) is high (62%) [7].…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, with the growing number of commercial nutrition-related apps, the difficulty of creating criteria to assess them increases with varying features and databases. Previous studies by Carter et al [6] and Raatz et al [9] comparing commercial nutrition-related apps with reference methods have used 24-hour recalls and weighed food records (WFR) respectively. Both studies found no significant differences in mean energy and macronutrients between the nutritionrelated app and reference method.…”

Section: Introductionmentioning

confidence: 99%

Popular Nutrition-Related Mobile Apps: An Agreement Assessment Against a UK Reference Method (Preprint)

Fallaize¹,

Franco²,

Pasang³

et al. 2018

Preprint

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Background: Nutrition-related apps are commonly used to provide information about the users' dietary intake, but limited research has been performed on the evaluation of their reliability. Objective: To evaluate the relative reliability of popular nutrition-related apps for the assessment of energy and available macro-and micronutrients against a standard method. Methods: Dietary analysis of 24-hour weighed food records (n = 20) were compared between five nutrition-related apps: S Health, MyFitnessPal, FatSecret, Noom Coach and Lose It!, and DietPlan6 (reference method). Estimates of energy, macronutrients (carbohydrate, protein, fat, saturated fat and fibre) and micronutrients (sodium, calcium, iron, vitamin A and vitamin C) were compared using t-tests and Wilcoxon signed-rank tests, correlation coefficients and Bland-Altman plots. 24-hour weighed food records from 20 participants (female/male, 15/5; mean age, 36.3 years; mean body mass index, 22.9 kg/m 2 ) recruited from previous controlled studies conducted at the Hugh Sinclair Unit of Human Nutrition, University of Reading, UK. Results: No significant difference in estimation of energy and saturated fat intake between DietPlan6 and the diet apps was observed. Estimates of protein and sodium intake were significantly lower using Lose It! and FatSecret than DietPlan6. Lose It! also gave significantly lower estimates for other reported outputs: carbohydrate, fat, fibre and sodium, compared with DietPlan6. For S Health and MyFitnessPal, calcium, iron and vitamin C were all significantly under-estimated compared with DietPlan6, although there was no significant difference for vitamin A. No other significant differences were observed between DietPlan6 and the apps. Correlation coefficients ranged from -0.12 for iron (S Health vs. DietPlan6) to 0.91 for protein (FatSecret vs DietPlan6). Noom Coach was limited to energy output but it had a high correlation with DietPlan6 (r=0.91) and S Health had the greatest variation of correlation, with energy at 0.79. Bland-Altman analysis revealed potential proportional bias for vitamin A. Conclusions: The findings suggest that the apps provide comparable estimates of energy and saturated fat intake compared with DietPlan6. With the exception of Lose It!, the apps also provided comparable estimates of carbohydrate, total fat and fibre. Two apps displayed a tendency to underestimate protein and sodium (FatSecret and Lose It!). Apart from vitamin A, the estimates of micronutrient intake (calcium, iron and vitamin C) by the two apps (S Health and MyFitnessPal) were inconsistent and less reliable. Lose It! was the less comparable app in relation to DietPlan6. As the use and availability of apps grows, this study helps clinicians and researchers to make betterinformed decisions about using these apps in research and practice.

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‘My Meal Mate’ (MMM): validation of the diet measures captured on a smartphone application to facilitate weight loss

Cited by 134 publications

References 20 publications

Smartphones and Health Promotion: A Review of the Evidence

Smartphones and Health Promotion: A Review of the Evidence

Personalised nutrition: the role of new dietary assessment methods

Popular Nutrition-Related Mobile Apps: An Agreement Assessment Against a UK Reference Method (Preprint)

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