Evidence map›Paper›PMID 39233588›Full record

ArticleJMIR mHealth and uHealth2024

Reliability Issues of Mobile Nutrition Apps for Cardiovascular Disease Prevention: Comparative Study.

Dang Khanh Ngan Ho, Wan-Chun Chiu, Jing-Wen Kao, Hsiang-Tung Tseng, Cheng-Yu Lin, Pin-Hsiang Huang, Yu-Ren Fang, Kuei-Hung Chen, Ting-Ying Su, Chia-Hui Yang and 4 more

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Effect ofInternational journal of medical sciences · 2026
    Trial
  2. Article
  3. Review
  4. Article
  5. 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
    Observational
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

14 authors.

Dang Khanh Ngan HoSchool of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, 250 Wuxing Street, Xinyi District, Taipei, 110, Taiwan, 886 2-27361661 ext 6542.ORCID 0000-0001-8782-2768
Wan-Chun ChiuSchool of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, 250 Wuxing Street, Xinyi District, Taipei, 110, Taiwan, 886 2-27361661 ext 6542.ORCID 0000-0003-4638-5412
Jing-Wen KaoSchool of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, 250 Wuxing Street, Xinyi District, Taipei, 110, Taiwan, 886 2-27361661 ext 6542.ORCID 0009-0007-6768-0628
Hsiang-Tung TsengSchool of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, 250 Wuxing Street, Xinyi District, Taipei, 110, Taiwan, 886 2-27361661 ext 6542.ORCID 0009-0003-8364-2980
Cheng-Yu LinSchool of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, 250 Wuxing Street, Xinyi District, Taipei, 110, Taiwan, 886 2-27361661 ext 6542.ORCID 0009-0000-3123-5484
Pin-Hsiang HuangSchool of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, 250 Wuxing Street, Xinyi District, Taipei, 110, Taiwan, 886 2-27361661 ext 6542.ORCID 0009-0000-0696-2532
Yu-Ren FangSchool of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, 250 Wuxing Street, Xinyi District, Taipei, 110, Taiwan, 886 2-27361661 ext 6542.ORCID 0009-0000-2970-0009
Kuei-Hung ChenSchool of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, 250 Wuxing Street, Xinyi District, Taipei, 110, Taiwan, 886 2-27361661 ext 6542.ORCID 0009-0007-1402-8310
Ting-Ying SuSchool of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, 250 Wuxing Street, Xinyi District, Taipei, 110, Taiwan, 886 2-27361661 ext 6542.ORCID 0009-0001-9162-0111
Chia-Hui YangSchool of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, 250 Wuxing Street, Xinyi District, Taipei, 110, Taiwan, 886 2-27361661 ext 6542.ORCID 0009-0004-8633-3398
Chih-Yuan YaoDepartment of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.ORCID 0009-0008-3258-1272
Hsiu-Yueh SuSchool of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, 250 Wuxing Street, Xinyi District, Taipei, 110, Taiwan, 886 2-27361661 ext 6542.ORCID 0009-0001-5066-5807
Pin-Hui WeiDepartment of Nutrition, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan.ORCID 0009-0008-3864-6380
Jung-Su ChangSchool of Nutrition and Health Sciences, College of Nutrition, Taipei Medical University, 250 Wuxing Street, Xinyi District, Taipei, 110, Taiwan, 886 2-27361661 ext 6542.ORCID 0000-0001-8608-9349

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Controlling saturated fat and cholesterol intake is important for the prevention of cardiovascular diseases. Although the use of mobile diet-tracking apps has been increasing, the reliability of nutrition apps in tracking saturated fats and cholesterol across different nations remains underexplored. Objective: This study aimed to examine the reliability and consistency of nutrition apps focusing on saturated fat and cholesterol intake across different national contexts. The study focused on 3 key concerns: data omission, inconsistency (variability) of saturated fat and cholesterol values within an app, and the reliability of commercial apps across different national contexts. Methods: Nutrient data from 4 consumer-grade apps (COFIT, MyFitnessPal-Chinese, MyFitnessPal-English, and LoseIt!) and an academic app (Formosa FoodApp) were compared against 2 national reference databases (US Department of Agriculture [USDA]-Food and Nutrient Database for Dietary Studies [FNDDS] and Taiwan Food Composition Database [FCD]). Percentages of missing nutrients were recorded, and coefficients of variation were used to compute data inconsistencies. One-way ANOVAs were used to examine differences among apps, and paired 2-tailed t tests were used to compare the apps to national reference data. The reliability across different national contexts was investigated by comparing the Chinese and English versions of MyFitnessPal with the USDA-FNDDS and Taiwan FCD. Results: Across the 5 apps, 836 food codes from 42 items were analyzed. Four apps, including COFIT, MyFitnessPal-Chinese, MyFitnessPal-English, and LoseIt!, significantly underestimated saturated fats, with errors ranging from -13.8% to -40.3% (all P<.05). All apps underestimated cholesterol, with errors ranging from -26.3% to -60.3% (all P<.05). COFIT omitted 47% of saturated fat data, and MyFitnessPal-Chinese missed 62% of cholesterol data. The coefficients of variation of beef, chicken, and seafood ranged from 78% to 145%, from 74% to 112%, and from 97% to 124% across MyFitnessPal-Chinese, MyFitnessPal-English, and LoseIt!, respectively, indicating a high variability in saturated fats across different food groups. Similarly, cholesterol variability was consistently high in dairy (71%-118%) and prepackaged foods (84%-118%) across all selected apps. When examining the reliability of MyFitnessPal across different national contexts, errors in MyFitnessPal were consistent across different national FCDs (USDA-FNDSS and Taiwan FCD). Regardless of the FCDs used as a reference, these errors persisted to be statistically significant, indicating that the app's core database is the source of the problems rather than just mismatches or variances in external FCDs. Conclusions: The findings reveal substantial inaccuracies and inconsistencies in diet-tracking apps' reporting of saturated fats and cholesterol. These issues raise concerns for the effectiveness of using consumer-grade nutrition apps in cardiovascular disease prevention across different national contexts and within the apps themselves.

Indexed as

Cardiovascular DiseasesMobile ApplicationsHumansReproducibility of ResultsTaiwanappapplicationapplicationsappscardiovascularcardiovascular disease preventiondietdietary assessmentfitnessmHealthmobile appsmobile healthnutrientsnutritionvalidity

Identifiers

PMID39233588
PMCPMC11391091

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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.