Dietary preferences and diabetic risk in China: A large‐scale nationwide Internet data‐based study

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Abstract
Background: Unhealthy diet is one of the important risk factors of diabetes, which is one of the major public health problems in China. The Internet tools provide large‐scale passively collected data that show people's dietary preferences and their relationship with diabetes risk.Methods: 212 341 708 individuals' dietary preference labels were created based on Internet data from online search and shopping software. Metabolic data obtained from the 2010 China Noncommunicable Disease Surveillance, which had 98 658 participants, was used to estimate the relation between dietary preferences geographical distribution and diabetes risk.Results: Chinese dietary preferences had different geographical distribution, which is related to the local climate and consumption level. Fried food preference proportion distribution was significantly positively correlated with diabetes prevalence, hypertension prevalence and body mass index (BMI). Similarly, grilled food preference proportion distribution had significantly positive correlation with the prevalence of diabetes and hypertension. In contrast, spicy food preference proportion distribution was negatively correlated with diabetes prevalence. Sweet food preference proportion distribution was positively related to diabetes prevalence. Using dietary preferences data to predict regional prevalence of diabetes, hypertension and BMI, the average values of error (95% CI) between the three paired predicted and observed values were 9.8% (6.9%‐12.7%), 7.5% (5.0%‐10.0%) and 1.6% (1.2%‐2.0%), respectively.Conclusions: Fried food, grilled food, and sweet food preferences were positively related to diabetes risk whereas spicy food preference was negatively correlated with diabetes risk. Dietary preferences based on passively collected Internet data could be used to predict regional prevalence of diabetes, hypertension, and BMI and showed good value for public health monitoring.
Funding Information
  • Ministry of Science and Technology of the People's Republic of China (2016YFC0901200, 2016YFC1304904, 2016YFC1305600, 2017YFC1310700, 2018YFC1311800)
  • National Natural Science Foundation of China (81500610, 81500660, 81621061, 81622011)
  • Health and Family Planning Commission of Sichuan Province (20174Y0014)

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