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

Zhiyun Zhao, Mian Li, Chao Li, Tiange Wang, Yu Xu, Zhizheng Zhan, Weishan Dong, Zhiyong Shen, Min Xu, Jieli Lu, Yuhong Chen, Shenghan Lai, Wei Fan, Yufang Bi, Weiqing Wang, Guang Ning

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
JournalJournal of Diabetes
DOIs
StateAccepted/In press - Jan 1 2019

Fingerprint

Food Preferences
Internet
China
Hypertension
Body Mass Index
Public Health
Food
Climate
Software
Diet

Keywords

  • diabetes mellitus
  • dietary preferences
  • geographical distribution
  • large-scale internet data

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism

Cite this

Dietary preferences and diabetic risk in China : A large-scale nationwide Internet data-based study. / Zhao, Zhiyun; Li, Mian; Li, Chao; Wang, Tiange; Xu, Yu; Zhan, Zhizheng; Dong, Weishan; Shen, Zhiyong; Xu, Min; Lu, Jieli; Chen, Yuhong; Lai, Shenghan; Fan, Wei; Bi, Yufang; Wang, Weiqing; Ning, Guang.

In: Journal of Diabetes, 01.01.2019.

Research output: Contribution to journalArticle

Zhao, Z, Li, M, Li, C, Wang, T, Xu, Y, Zhan, Z, Dong, W, Shen, Z, Xu, M, Lu, J, Chen, Y, Lai, S, Fan, W, Bi, Y, Wang, W & Ning, G 2019, 'Dietary preferences and diabetic risk in China: A large-scale nationwide Internet data-based study', Journal of Diabetes. https://doi.org/10.1111/1753-0407.12967
Zhao, Zhiyun ; Li, Mian ; Li, Chao ; Wang, Tiange ; Xu, Yu ; Zhan, Zhizheng ; Dong, Weishan ; Shen, Zhiyong ; Xu, Min ; Lu, Jieli ; Chen, Yuhong ; Lai, Shenghan ; Fan, Wei ; Bi, Yufang ; Wang, Weiqing ; Ning, Guang. / Dietary preferences and diabetic risk in China : A large-scale nationwide Internet data-based study. In: Journal of Diabetes. 2019.
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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.",
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T1 - Dietary preferences and diabetic risk in China

T2 - A large-scale nationwide Internet data-based study

AU - Zhao, Zhiyun

AU - Li, Mian

AU - Li, Chao

AU - Wang, Tiange

AU - Xu, Yu

AU - Zhan, Zhizheng

AU - Dong, Weishan

AU - Shen, Zhiyong

AU - Xu, Min

AU - Lu, Jieli

AU - Chen, Yuhong

AU - Lai, Shenghan

AU - Fan, Wei

AU - Bi, Yufang

AU - Wang, Weiqing

AU - Ning, Guang

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

KW - diabetes mellitus

KW - dietary preferences

KW - geographical distribution

KW - large-scale internet data

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