Evidence map›Paper›PMID 40397893›Full record

ArticlePloS one2025

Chronic diseases and self-rated health disparity between urban and rural residents in China.

Yu Wang, Li Liu

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Construction and validation of a predictive model for sleep disorders among rural older adults with mild cognitive impairment.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
    Article
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  5. Attitudes toward partner notification ofFrontiers in public health · 2026
    Article
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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

2 authors.

Yu WangCollege of Public Health, Chongqing Medical University, Chongqing, China.
Li LiuCollege of Public Health, Chongqing Medical University, Chongqing, China.ORCID 0009-0007-3902-4180

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the significant disparities between urban and rural areas in China, particularly in terms of health status, which are driven by economic inequality and the uneven distribution of healthcare resources. Chronic diseases are a major threat to the health of Chinese residents, and this study explores how these diseases contribute to the disparity in self-rated health between urban and rural populations. Using data from the 2021 Chinese General Social Survey, various data analysis methods, including descriptive, regression, and decomposition analyses, were employed. The results reveal substantial disparities in self-rated health between urban and rural residents, with chronic diseases playing a significant role in explaining these disparities. Approximately 39% of the urban-rural disparity in self-rated health can be explained by differences in chronic disease prevalence, with additional factors such as age, socio-economic status, social participation, and sleep quality also contributing. This study identified the correlation between chronic diseases and the disparity in self-rated health, and limitations may arise from the use of self-reported health and the complexity of urban-rural health disparities. The findings suggest that the urban-rural disparity in chronic diseases is the primary driver of the health disparity, and that policymakers should focus on improving health education, promoting chronic disease prevention and management, and emphasizing preventive healthcare in rural areas.

Indexed as

Health Status DisparitiesRural PopulationUrban PopulationAdolescentAdultAgedChinaChronic DiseaseFemaleHumansMaleMiddle AgedPrevalenceSelf ReportSocioeconomic FactorsYoung Adult

Identifiers

PMID40397893
PMCPMC12094759

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.