Evidence map›Paper›PMID 41882646›Full record

ArticleInternational journal of health geographics2026

Identifying and assessing online food delivery swamps in major Chinese cities.

Sui Ye, Jianchao Xi, Ziqiang Li

Abstract read
In one paragraph

Article in International journal of health geographics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Sui YeInstitute of Geographic Sciences and Natural Resources Research, Key Laboratory of Regional Sustainable Development Modeling, Chinese Academy of Sciences, Beijing, 100101, China.
Jianchao XiInstitute of Geographic Sciences and Natural Resources Research, Key Laboratory of Regional Sustainable Development Modeling, Chinese Academy of Sciences, Beijing, 100101, China. xijc@igsnrr.ac.cn.
Ziqiang LiInstitute of Geographic Sciences and Natural Resources Research, Key Laboratory of Regional Sustainable Development Modeling, Chinese Academy of Sciences, Beijing, 100101, China.

Funding

A Study on the Exploration, Preservation, and Utilization of Resources for Ethnic Interaction, Exchange, and Integration along the Sichuan-Tibet Railway U24A20583
6 · The paper itself

Abstract

The rise of "online food delivery swamps," driven by digital platforms, raises important questions about how urban food delivery systems affect nutritional equality. To overcome the limitations of traditional methods that rely on store classifications and physical proximity, this study introduces a high-resolution framework integrating dish-level nutritional data with digital accessibility. Applying this to 254,642 vendors across ten major Chinese cities, our analysis reveals a widespread structural imbalance in the food environment, marked by an oversupply of energy, fat, and carbohydrates. Spatially, all cities exhibit a stark "core-oasis, periphery-swamp" pattern, exposing significant intra-urban inequality. We uncover a critical mismatch between the geographical extent of these swamps and the actual residential proximity to nutritionally imbalanced food supply, identifying distinct urban patterns from "extensive coverage-low residential exposure" to "high coverage-high residential exposure". Furthermore, we demonstrate that "food swamps" are not monolithic; instead, they comprise heterogeneous subtypes with unique nutritional deviation profiles. This study uncovers new dimensions of urban nutritional supply inequality in the digital era, providing evidence that may inform the development of food environment policies.

Indexed as

CitiesCommerceFood SupplyUrban PopulationChinaDigital MediaHumansDigital Food EnvironmentFood SwampNutritional InequalityOnline Food DeliveryUrban Health

Identifiers

PMID41882646
PMCPMC13220461

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.