Evidence map›Paper›PMID 40012813›Full record

ArticleInternational journal of public health2025

Rural-Urban Disparity in Premature Cancer Mortality in Young People Aged 15-44 Years in China, 2004-2021.

Chunrong Chen, Xing Xing, Shaojie Li, Bo Qu, Chunyu Liu, He Zhu

Abstract read
In one paragraph

Article in International journal of public health, 2025. 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.

Chunrong ChenDepartment of Radiation Oncology, The First Affiliated Hospital of Qiqihar Medical College, Qiqihar, Heilongjiang, China.
Xing XingSchool of Public Health, Peking University, Beijing, China.
Shaojie LiSchool of Public Health, Peking University, Beijing, China.
Bo QuDepartment of Radiation Oncology, The First Affiliated Hospital of Qiqihar Medical College, Qiqihar, Heilongjiang, China.
Chunyu LiuDepartment of Radiation Oncology, The First Affiliated Hospital of Qiqihar Medical College, Qiqihar, Heilongjiang, China.
He ZhuSchool of Public Health, Peking University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to examine and compare premature cancer mortality in young people aged 15-44 years old between rural and urban areas to inform early-onset cancer prevention. Methods: The data were obtained from the China Death Surveillance Datasets from 2004 to 2021. The study sample consisted of cancer deaths of young people aged 15-44 years old. Age-standardized mortality rates (ASMRs) were calculated, and joinpoint regressions were used to examine trends in ASMRs. Results: There were overall decreasing trends in ASMRs for all cancers in both rural and urban young people in China from 2004 to 2021. However, the decrease was relatively slower in rural areas, where ASMRs for pancreatic and ovarian cancers showed increasing trends. The five leading types of cancer deaths consistently remained liver, lung, leukemia, stomach, and other cancers in both rural and urban areas after 2013. Conclusion: Our findings indicate that there were rural-urban disparities in cancer mortality in young people, which showed a different pattern compared to other age groups. More efforts are needed to develop effective early-onset cancer prevention strategies, with particular emphasis on liver cancer and rural areas.

Indexed as

Health Status DisparitiesMortality, PrematureNeoplasmsRural PopulationUrban PopulationAdolescentAdultChinaFemaleHumansMaleYoung Adultage-standardized mortality ratecancermortalityrural-urban disparityyoung people

Identifiers

PMID40012813
PMCPMC11859585

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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.