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. 2021 Jun;24(8):2021-2032.
doi: 10.1017/S136898002000035X. Epub 2020 Jun 9.

Associations between taste preferences and chronic diseases: a population-based exploratory study in China

Hanqi Li  1 , Peng Jia  2   3 , Teng Fei  1
Affiliations

Associations between taste preferences and chronic diseases: a population-based exploratory study in China

Hanqi Li et al. Public Health Nutr. 2021 Jun.

Abstract

Objective: To explore the associations between dietary tastes and chronic diseases quantitatively.

Design: We used the Geodetector method to establish associations between seven tastes and a variety of chronic diseases from the perspective of spatial stratified heterogeneity and explained the effects of dietary tastes on the spatial distribution of chronic diseases.

Setting: We used crowdsourcing online recipe data to extract multiple taste information about cuisines, combined with point of interest data on categorised restaurant data in different regions, to quantitatively analyse the taste preferences of people in different regions.

Participants: Crowdsourcing online recipe data and restaurant data in different regions.

Results: The results showed that sixteen diseases were significantly associated with dietary tastes among the seventy-one types of chronic diseases. Compared with the effects of individual tastes, the interactions of tastes increased the risk of sixteen diseases, and many combinations of tastes produced nonlinear enhancement effects on the risk for diseases.

Conclusions: This study presents a quantitative study approach based on the crowdsourcing of data to explore potential health risk factors, which can be applied to the exploratory analysis of disease aetiology and help public health authorities to develop corresponding interventions.

Keywords: Chronic disease; Crowdsourcing data; Dietary taste; Geodetector; Risk factor.

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Figures

Fig. 1
Fig. 1
Seasonings of a dish (captured from Meishijie.com)
Fig. 2
Fig. 2
Data processing and research flow
Fig. 3
Fig. 3
Proportions of various types of POI in provincial regions. formula image, Chuan; formula image, Dongbei; formula image, Gangtai; formula image, Hubei; formula image, Hu; formula image, Hui; formula image, Jing; formula image, Lu; formula image, Min; formula image, Qingzhen; formula image, Su; formula image, Xibei; formula image, Xiang; formula image, Yue; formula image, Yungui; formula image, Zhe. POI, points of interest
Fig. 4
Fig. 4
Standardised indexes of seven tastes in provincial regions
Fig. 5
Fig. 5
Standardised mortality of haemorrhagic stroke in provincial regions
Fig. 6
Fig. 6
Risk detector results for haemorrhagic stroke (NB(6): natural break method, six levels)
See this image and copyright information in PMC

References

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