Evidence map›Paper›PMID 32515723›Full record

ArticlePublic health nutrition2021

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

Hanqi Li, Peng Jia, Teng Fei

Open access · greenAbstract read
In one paragraph

Article in Public health nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 22 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Hanqi LiSchool of Resource and Environmental Sciences, Wuhan University, Wuhan, Hubei430079, China.ORCID 0000-0002-9208-8470
Peng JiaDepartment of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong kong, China.
Teng FeiSchool of Resource and Environmental Sciences, Wuhan University, Wuhan, Hubei430079, China.
Wuhan University · CNHong Kong Polytechnic University · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo explore the associations between dietary tastes and chronic diseases quantitatively.

designWe 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.

settingWe 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.

participantsCrowdsourcing online recipe data and restaurant data in different regions.

resultsThe 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.

conclusionsThis 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.

Indexed as

Food PreferencesTasteChronic DiseaseDietHumansTaste PerceptionChronic diseaseCrowdsourcing dataDietary tasteGeodetectorRisk factor

Identifiers

PMID32515723
PMCPMC10195596
OpenAlexW3033998621

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.