Evidence map›Paper›PMID 38803809›Full record

ArticleFrontiers in public health2024

Health inequality of rural-to-urban migrant workers in eastern China and its decomposition: a comparative cross-sectional study.

Sisi Du, Yufan Yang, Miaomiao Zheng, Haiyan Zhang, Tingting Li, Fuman Cai

Abstract readComparative Study
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. 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

6 authors.

Sisi Du *College of Nursing, Wenzhou Medical University, Wenzhou, China.
Yufan Yang *The Second School of Medicine, Wenzhou Medical University, Wenzhou, China.
Miaomiao ZhengCollege of Nursing, Wenzhou Medical University, Wenzhou, China.
Haiyan ZhangCollege of Nursing, Wenzhou Medical University, Wenzhou, China.
Tingting LiThe First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Fuman CaiCollege of Nursing, Wenzhou Medical University, Wenzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: As a specific group with high health inequality, it is crucial to improve the health status and health inequalities of rural-to-urban migrant workers. This study aimed to evaluate the health inequality of migrant and urban workers in China and decompose it. Methods: A cross-sectional study was carried out, using a standardized questionnaire to obtain basic information, self-rated health to evaluate health status, concentration index to measure health inequalities, and WDW decomposition to analyze the causes of health inequalities. Results: The concentration index of health for migrants was 0.021 and 0.009 for urban workers. The main factors contributing to health inequality among rural-to-urban migrant workers included income, exercise, and age. In contrast, the main factors of health inequality among urban workers included income, the number of chronic diseases, social support, and education. Conclusion: There were health inequalities in both rural-to-urban migrant and urban workers. The government and relevant authorities should formulate timely policies and take targeted measures to reduce income disparities among workers, thereby improving health inequality.

Indexed as

Health Status DisparitiesRural PopulationTransients and MigrantsUrban PopulationAdultChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedSocioeconomic FactorsSurveys and Questionnairesconcentration indexdecompositionhealth inequalityrural-to-urban migrant workerurban worker

Identifiers

PMID38803809
PMCPMC11128589

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.