Evidence map›Paper›PMID 42755802›Full record

ArticleFrontiers in public health2026

Mortality trends and influencing factors of mental disorders among urban and rural residents in China between 2009 and 2021: a longitudinal study with projections to 2030.

Kaiyao Shen, Chenghao Wu, Wenhui Kong, Xu Wang, Yujie Zhao, Xueying Wang, Shan Hong, Hui Li

Abstract read
In one paragraph

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

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0cells of the map it votes in
0citing papers in PubMed
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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

8 authors.

Kaiyao ShenSchool of Public Health, Jilin University, Changchun, China.
Chenghao WuSchool of Public Health, Jilin University, Changchun, China.
Wenhui KongSchool of Public Health, Jilin University, Changchun, China.
Xu WangSchool of Public Health, Jilin University, Changchun, China.
Yujie ZhaoSchool of Public Health, Jilin University, Changchun, China.
Xueying WangSchool of Public Health, Jilin University, Changchun, China.
Shan HongSchool of Public Health, Jilin University, Changchun, China.
Hui LiSchool of Public Health, Jilin University, Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Mental disorders pose a major public health challenge in China, with marked urban-rural disparities in resources and outcomes. However, long-term mortality trends, their influencing factors, and future projections across urban and rural areas remain underexplored. This study aimed to analyze these mortality trends, identify relevant factors, and project mortality to 2030 using national data from 2009 to 2021. Methods: Data were extracted from the Results: From 2009 to 2021, urban crude mortality rates (CMR) remained stable, whereas rural CMR increased significantly (AAPC = 1.21%, Conclusion: This study reveals significant urban-rural disparities in mental disorder mortality, with rural areas experiencing a marked recent increase. Males, the oldest old, and young adults are particularly vulnerable. Population aging showed the strongest association with mortality, and this association persisted after controlling for additional confounders. Scenario projections indicated continued divergence between urban and rural trends. These findings underscore the need for life-course prevention strategies and differentiated resource allocation between urban and rural areas.

Indexed as

Mental DisordersMortalityRural PopulationUrban PopulationAdultAgedChinaFemaleForecastingHumansLongitudinal StudiesMaleMiddle AgedRisk FactorsagingGrey forecasting modelinfluencing factorsmental disordersmortality trendsurban-rural disparities

Identifiers

PMID42755802
PMCPMC13581816

What OpenQuestion holds

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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.