基于众源数据挖掘的中国饮食口味与慢性病的空间关联

Translated title of the contribution: Geographical association between dietary tastes and chronic diseases in China: An exploratory study using crowdsourcing data mining techniques

Hanqi Li, Peng Jia, Teng Fei*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

Chronic diseases are the main cause for death in the world. Among all risk factors concerning chronic diseases, those related to an unhealthy diet are most important. Although much research was done on dietary behavior, there are only few quantitative studies on the relationship between dietary taste and chronic diseases. In this article, a taste dataset of the major categories of Chinese cuisine is established based on crowdsourced data from Chinese recipe websites. For a quantitative analysis of people's taste in different regions, additionally the locations of restaurants by category (using their respective points of interest) are integrated. Using the software Geodetector, these regional taste preferences are then correlated with the three chronic diseases, hemorrhagic stroke, pancreatic cancer, and upper respiratory tract infection. For all the three diseases, the results indicate very salty, moderate sweet and very spicy food as the primary risk factors. Also, the degree of sweetness is not linear with the risk of pancreatic cancer. These results are statistically significant. In this study, a quantitative method on discovering potential health risk factors based on mining of crowdsourced data is proposed for the first time. This method can be applied before disease- related experiments to filter potential factors, and it is helpful for the public health department to make quick corresponding intervention policies.

Translated title of the contributionGeographical association between dietary tastes and chronic diseases in China: An exploratory study using crowdsourcing data mining techniques
Original languageChinese (Traditional)
Pages (from-to)1637-1649
Number of pages13
JournalDili Xuebao/Acta Geographica Sinica
Volume74
Issue number8
DOIs
Publication statusPublished - 25 Aug 2019

Keywords

  • Chronic disease
  • Crowdsourcing data mining
  • Dietary tastes
  • Geodetector
  • Risk factor

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