Evidence map›Paper›PMID 42406949›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Feeding health inequality through platform-based food delivery in China.

Hai Ding, Chenran Liu, Yu Xie, Jia Yu, Zhengrong Yuan

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. 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. Feeding health inequality through platform-based food delivery in China.Proceedings of the National Academy of Sciences of the United States of America · 2026
    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

5 authors.

Hai Ding *Guanghua School of Management, Peking University, Beijing 100871, China.
Chenran Liu *School of Economics, Renmin University of China, Beijing 100872, China.ORCID 0000-0002-5826-379X
Yu Xie *Paul and Marcia Center on Contemporary China, Princeton University, Princeton, NJ 08544.ORCID 0000-0002-3240-8620
Jia Yu *Center for Social Research, Guanghua School of Management, Peking University, Beijing 100871, China.ORCID 0000-0002-7194-7635
Zhengrong Yuan *School of Economics, Zhongnan University of Economics and Law, Wuhan 430073, China.

Funding

MOST | National Natural Science Foundation of China (NSFC) 72192844MOST | National Natural Science Foundation of China (NSFC) 72473003
6 · The paper itself

Abstract

This study examines how the expansion of online food delivery platforms affects health inequality in China. Exploiting the staggered rollout of platforms across counties and nationally representative panel data from 2010 to 2022, we find that platform entry increases overweight among low-income individuals while reducing it among high-income individuals. This divergence operates through two channels: low-income users increase consumption of fried foods and reallocate time from cooking to sedentary leisure, whereas high-income users reduce intake of calorie-dense foods and increase physical activity. These behavioral changes accumulate into downstream health consequences affecting weight-related chronic diseases and children's overweight in low-income households. Equal access to digital convenience thus does not translate into equal health benefits, suggesting that technological diffusion may amplify health disparities.

Indexed as

Feeding BehaviorHealth Status DisparitiesChinaDigital MediaHumansOverweightSocioeconomic Disparities in Healthdigital platformshealth inequalityoverweightsocioeconomic status

Identifiers

PMID42406949
PMCPMC13367860

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.