Evidence map›Paper›PMID 38654168›Full record

ArticleBMC public health2024

The regional disparities in liver disease comorbidity among elderly Chinese based on a health ecological model: the China Health and Retirement Longitudinal Study.

Wei Gong, Hong Lin, Xiuting Ma, Hongliang Ma, Yali Lan, Peng Sun, Jianjun Yang

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2024. 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
2.7field-weighted citation impact, top 10% of its field
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, 7 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Wei Gong *Public Health School, Ningxia Medical University, Yinchuan, 750004, China.
Hong Lin *Public Health School, Ningxia Medical University, Yinchuan, 750004, China.
Xiuting MaPublic Health School, Ningxia Medical University, Yinchuan, 750004, China.
Hongliang MaSchool of Clinical Medicine, Ningxia Medical University, Yinchuan, 750004, China.
Yali LanPublic Health School, Ningxia Medical University, Yinchuan, 750004, China.
Peng SunPublic Health School, Ningxia Medical University, Yinchuan, 750004, China. preston.sunpeng@gmail.com.
Jianjun YangPublic Health School, Ningxia Medical University, Yinchuan, 750004, China. yangjj@nxmu.edu.cn.
Ningxia Medical University · CN

Funding

Key research and development project in Ningxia 2021BEG03031Scientific research project of Ningxia Medical University in 2020 No. XT2020024This work was supported by the National Natural Science Foundation of China No. 82060597
6 · The paper itself

Abstract

purposeThis study aimed to investigate the risk factors for liver disease comorbidity among older adults in eastern, central, and western China, and explored binary, ternary and quaternary co-morbid co-causal patterns of liver disease within a health ecological model.

methodBasic information from 9,763 older adults was analyzed using data from the China Health and Retirement Longitudinal Study (CHARLS). LASSO regression was employed to identify significant predictors in eastern, central, and western China. Patterns of liver disease comorbidity were studied using association rules, and spatial distribution was analyzed using a geographic information system. Furthermore, binary, ternary, and quaternary network diagrams were constructed to illustrate the relationships between liver disease comorbidity and co-causes.

resultsAmong the 9,763 elderly adults studied, 536 were found to have liver disease comorbidity, with binary or ternary comorbidity being the most prevalent. Provinces with a high prevalence of liver disease comorbidity were primarily concentrated in Inner Mongolia, Sichuan, and Henan. The most common comorbidity patterns identified were "liver-heart-metabolic", "liver-kidney", "liver-lung", and "liver-stomach-arthritic". In the eastern region, important combination patterns included "liver disease-metabolic disease", "liver disease-stomach disease", and "liver disease-arthritis", with the main influencing factors being sleep duration of less than 6 h, frequent drinking, female, and daily activity capability. In the central region, common combination patterns included "liver disease-heart disease", "liver disease-metabolic disease", and "liver disease-kidney disease", with the main influencing factors being an education level of primary school or below, marriage, having medical insurance, exercise, and no disabilities. In the western region, the main comorbidity patterns were "liver disease-chronic lung disease", "liver disease-stomach disease", "liver disease-heart disease", and "liver disease-arthritis", with the main influencing factors being general or poor health satisfaction, general or poor health condition, severe pain, and no disabilities.

conclusionThe comorbidities associated with liver disease exhibit specific clustering patterns at both the overall and local levels. By analyzing the comorbidity patterns of liver diseases in different regions and establishing co-morbid co-causal patterns, this study offers a new perspective and scientific basis for the prevention and treatment of liver diseases.

Indexed as

ComorbidityLiver DiseasesAgedAged, 80 and overChinaEast Asian PeopleFemaleHealth Status DisparitiesHumansLongitudinal StudiesMaleMiddle AgedPrevalenceRisk FactorsAssociation rulesCo-morbid co-causal patternElderly peopleGeographic information systemLiver disease comorbidity

Identifiers

PMID38654168
PMCPMC11040959
OpenAlexW4395049381

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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.