Evidence map›Paper›PMID 40079059›Full record

ArticlePublic health nutrition2025

Digital platform-based conceptual framework for food environment research in China.

Na Cong, Keumseok Koh, Mei-Po Kwan, Hongsheng Zhang

Abstract read
In one paragraph

Article in Public health nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Na CongDepartment of Geography, Faculty of Social Science, The University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region of China.ORCID 0009-0001-4041-9493
Keumseok KohDepartment of Geography, Faculty of Social Science, The University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region of China.ORCID 0000-0001-7263-2697
Mei-Po KwanDepartment of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region of China.
Hongsheng ZhangDepartment of Geography, Faculty of Social Science, The University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

China has dedicated significant efforts to preventing obesity, but the rising prevalence of overweight and obesity remains a pressing public health issue. Therefore, unique solutions are required to address this challenge in China. As a research priority, the food environment plays a pivotal role in addressing overweight and obesity. However, research on this topic in China lags behind that in other developed countries, and the conflicting global evidence on the association between the food environment and obesity cannot be directly applied to policymaking and intervention in China. In addition, the rapid advancement of digital technology has introduced complexities and uncertainties in the food environment. To address these challenges, we propose an alternative research framework through (a) dissecting the challenges associated with defining and measuring the food environment, (b) reorganising the relationship chains between the food environment and human diet/health and (c) taking into consideration digital platforms as crucial monitoring tools for studying the food environment. Our framework aims to unlock the potential of food environment research in the digital age, ultimately striving to tackle the overweight and obesity issues in China.

Indexed as

Digital TechnologyEnvironmentFood SupplyObesityChinaDietHumansOverweightPublic HealthChinaDigital platformFood environmentObesitySystematic framework

Identifiers

PMID40079059
PMCPMC11984002

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.