Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Nov 12, 2023
Date Accepted: Jun 24, 2024
Reliability Issues of Mobile Nutrition Apps for Cardiovascular Disease Prevention: A Comparative Study
ABSTRACT
Background:
Controlling saturated fat and cholesterol intake is crucial for preventing cardiovascular diseases (CVDs).
Objective:
The present study aimed to assess the accuracy of mobile nutrition applications (apps) in tracking these nutrients, with a focus on nutrient omissions and the reliability of universal commercial apps across nations.
Methods:
Nutrient data from four commercial apps (COFIT, MyFitnessPal-Chinese, MyFitnessPal-English, and LoseIt!) and an academic app (Formosa-FoodApp) were compared against corresponding national reference databases (United States Department of Agriculture Food and Nutrient Database for Dietary Studies (USDA-FNDDS) and Taiwan Food Composition Database (TaiwanFCD)). Percentages (%) of missing nutrients were recorded, and data inconsistencies were calculated using the coefficient of variation (CV). Paired t-tests compared the apps to national reference data, while a one-way analysis of variance (ANOVA) examined app-to-app discrepancies. Cross-national reliability was studied comparing Chinese and English versions of MyFitnessPal against the USDA-FNDDS and TaiwanFCD.
Results:
Across five apps, 836 food codes from 42 items were analyzed. Four apps, including COFIT, MyFitnessPal-Chinese, MyFitnessPal-English, and LoseIt!, significantly underestimated saturated fat with errors ranging -13.8% to -40.3% (all P<0.05). All apps underestimated cholesterol with errors ranging -26.3% to -60.3% (all P<0.05). COFIT-Chinese omitted 47% of saturated fat data, and MyFitnessPal-Chinese missed 62% of cholesterol data. MyFitnessPal-Chinese recorded the highest CVs (96.7% for saturated fat and 112.1% for cholesterol), followed by MyFitnessPal-English (70.2% and 97.7%) and LoseIt! (83.5% and 95.6%). Cholesterol variability was consistently high in dairy (71%–118%) and prepackaged foods (84%–118%) across all apps. When examining cross-national usage, discrepancies between apps appeared to be attributed to the platform's inherent errors rather than differences in reference nutrient databases.
Conclusions:
The findings underscore the importance of rigorous validation of mobile nutrition apps and highlights challenges in the use of cross-national diet-tracking apps in CVD prevention.
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