TY  - JOUR
AU  - Li, Yuan
AU  - Ding, Jingmin
AU  - Wang, Yishan
AU  - Tang, Chengyao
AU  - Zhang, Puhong
PY  - 2019
DA  - 2019/07/30
TI  - Nutrition-Related Mobile Apps in the China App Store: Assessment of Functionality and Quality
JO  - JMIR Mhealth Uhealth
SP  - e13261
VL  - 7
IS  - 7
KW  - mobile phone
KW  - mobile apps
KW  - apps
KW  - nutrition
KW  - diet
KW  - food
KW  - behavior change
AB  - Background: There are an increasing number of mobile apps that provide dietary guidance to support a healthy lifestyle and disease management. However, the characteristics of these nutrition-related apps are not well analyzed. Objective: This study aimed to evaluate the functionality and quality of nutrition-related apps in China. Methods: Mobile apps providing dietary guidance were screened in the Chinese iOS and Android app stores in November 2017, using stepwise searching criteria. The first screening consisted of extracting information from the app descriptions. Apps that (1) were free, (2) contain information on diet and nutrition, and (3) were last updated after January 1, 2016, were downloaded for further analysis. Nutritional functionalities were determined according to the Chinese Dietary Guidelines framework. Market-related functionalities were developed from previous studies and tailored to downloaded apps. The quality of apps was assessed with the user version of the Mobile App Rating Scale (uMARS). Results: Out of 628 dietary guidance apps screened, 44 were nutrition-related. Of these, guidance was provided on diet exclusively (11/44, 25%), fitness (17/44, 39%), disease management (11/44, 25%), or maternal health (5/44, 11%). Nutritional functionalities included nutritional information inquiry (40/44, 91%), nutrition education (35/44, 80%), food record (34/44, 77%), diet analysis (34/44, 77%), and personalized recipes (21/44, 48%). Dietary analysis and suggestions mainly focused on energy intake (33/44, 75%) and less on other factors such as dietary structure (10/44, 23%). Social communication functionalities were available in 42 apps (96%), user incentives were supported in 26 apps (59%), and intelligent recognition technology was available in 8 apps (18%). The median score for the quality of the 44 apps, as determined on a 5-point uMARS scale, was 3.6 (interquartile range 0.7). Conclusions: Most nutrition-related apps are developed for health management rather than for dietary guidance exclusively. Although basic principles of energy balance are used, their nutritional functionality was relatively limited and not individualized. More efforts should be made to develop nutrition-related apps with evidence-based nutritional knowledge, comprehensive and personalized dietary guidance, and innovative technology. 
SN  - 2291-5222
UR  - http://mhealth.jmir.org/2019/7/e13261/
UR  - https://doi.org/10.2196/13261
UR  - http://www.ncbi.nlm.nih.gov/pubmed/31364606
DO  - 10.2196/13261
ID  - info:doi/10.2196/13261
ER  -