Evidence map›Paper›PMID 30785409›Full record

ArticleJMIR mHealth and uHealth2019

Popular Nutrition-Related Mobile Apps: An Agreement Assessment Against a UK Reference Method.

Rosalind Fallaize, Rodrigo Zenun Franco, Jennifer Pasang, Faustina Hwang, Julie A Lovegrove

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 2 pooled it
11.5field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 2 syntheses or guidelines pooled it, 70 citations in OpenAlex.

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  9. Reliability and Validity of Nutrient Assessment Applications for Canadian Endurance Athletes: MyFitnessPal and Cronometer.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Rosalind Fallaize *Hugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, Department of Food and Nutritional Sciences, University of Reading, Reading, United Kingdom.ORCID 0000-0003-3734-6489
Rodrigo Zenun Franco *Department of Biomedical Engineering, School of Biological Sciences, University of Reading, Reading, United Kingdom.ORCID 0000-0002-1998-4367
Jennifer PasangHugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, Department of Food and Nutritional Sciences, University of Reading, Reading, United Kingdom.ORCID 0000-0002-5133-046X
Faustina HwangDepartment of Biomedical Engineering, School of Biological Sciences, University of Reading, Reading, United Kingdom.ORCID 0000-0002-3243-3869
Julie A LovegroveHugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research, Department of Food and Nutritional Sciences, University of Reading, Reading, United Kingdom.ORCID 0000-0001-7633-9455
University of Reading · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNutrition-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.

objectiveThe 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.

methodsWe 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

resultsThe difference in estimation of energy and saturated fat intake between Dietplan6 and the diet apps was not significant. Estimates of protein and sodium intake were significantly lower using Lose It! and FatSecret than using Dietplan6. Lose It! also gave significantly lower estimates for other reported outputs (carbohydrate, fat, fiber, and sodium) than did Dietplan6. Samsung Health and MyFitnessPal significantly underestimated calcium, iron, and vitamin C compared with Dietplan6, although there was no significant difference for vitamin A. We observed no other significant differences between Dietplan6 and the apps. Correlation coefficients ranged from r=-.12 for iron (Samsung Health vs Dietplan6) to r=.91 for protein (FatSecret vs Dietplan6). Noom Coach was limited to energy output, but it had a high correlation with Dietplan6 (r=.91). Samsung Health had the greatest variation of correlation, with energy at r=.79. Bland-Altman analysis revealed potential proportional bias for vitamin A.

conclusionsThe findings suggest that the apps provide estimates of energy and saturated fat intake comparable with estimates by Dietplan6. With the exception of Lose It!, the apps also provided comparable estimates of carbohydrate, total fat, and fiber. FatSecret and Lose It! tended to underestimate protein and sodium. Estimates of micronutrient intake (calcium, iron, vitamin A, and vitamin C) by 2 apps (Samsung Health and MyFitnessPal) were inconsistent and less reliable. Lose It! was the app least comparable with Dietplan6. As the use and availability of apps grows, this study helps clinicians and researchers to make better-informed decisions about using these apps in research and practice.

Indexed as

Reference StandardsAdultBody Mass IndexDietary FatsDiet SurveysEnergy IntakeFemaleHumansMaleMiddle AgedMobile ApplicationsNutrition AssessmentNutrition PolicyReproducibility of ResultsUnited KingdomDietary Fatsdiet appsdietary assessmentdiet recordsmobile applicationsnutrition appssmartphone applicationweighed food records

Identifiers

PMID30785409
PMCPMC6401676
OpenAlexW2900770945

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.