Evidence map›Paper›PMID 30591053›Full record

ArticlePopulation health metrics2018

Health status in a transitional society: urban-rural disparities from a dynamic perspective in China.

Junfeng Jiang, Peigang Wang

Abstract read
In one paragraph

Article in Population health metrics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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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.

Junfeng JiangSchool of Health Sciences, Wuhan University, Wuhan, China, No.115 Donghu Road, Wuhan City, 430071, China.
Peigang WangSchool of Health Sciences, Wuhan University, Wuhan, China, No.115 Donghu Road, Wuhan City, 430071, China. wpg926@whu.edu.cn.

Funding

the Fundamental Research Funds for the Central Universities Whu2016026
6 · The paper itself

Abstract

backgroundThe phenomenon of urban-rural segmentation has emerged and is remarkable, and the health disparities between rural and urban China should be stressed.

methodsBased on data from the Chinese General Social Survey from 2005 to 2013, this study not only explored the net age, period, and cohort effects of self-rated health, but compared these effects between rural and urban China from a dynamic perspective through hierarchical age-period-cohort-cross-classified random effects model.

resultsUrban-rural disparities, as well as work status and gender disparities in health increased with age, in line with the cumulative advantage/disadvantage effects theory, while marital status disparities in health declining with age was in line with the age-as-leveler effects theory. The war cohort, famine cohort, later cultural revolution cohort, and early reform cohort had poorer health than did those in the early China cohort, economic recovery cohort, and later reform cohort. The economic crisis period, war cohort, baby boomer, and early cultural revolution cohort encountered larger urban-rural health disparities, while the early China cohort and early reform cohort experienced smaller urban-rural disparities in health.

conclusionsPopulation health is closely related to social context and health care development. It is necessary to keep economic development stable and boost medical technology improvements and the construction of the health care system.

Indexed as

Health Status DisparitiesAdolescentAdultAgedAged, 80 and overChinaFemaleHealth StatusHumansMaleMiddle AgedPopulation DynamicsRural PopulationUrban PopulationYoung AdultHierarchical age-period-cohort-cross-classified random effects modelSelf-rated healthUrban-rural disparityVariation rules

Identifiers

PMID30591053
PMCPMC6307183

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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.