Evidence map›Paper›PMID 38310224›Full record

ArticleBMC public health2024

Comorbidity risk and distribution characteristics of chronic diseases in the elderly population in China.

Zihang Xiang, Hao Wang, Handong Li

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 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
10.1field-weighted citation impact, top 1% 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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.

  1. Patient-reported outcome measures for patients with chronic comorbidities: a systematic review of psychometric properties.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
    Pooled it
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  6. Association of metabolic markers, inflammatory biomarkers, and sedentary time with comorbidities among cancer patients: Results from NHANES 2021-2023.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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  14. Observational
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  16. Mitigating Bias in Opportunistic Screening for MACE with Causal Reasoning.IEEE transactions on artificial intelligence · 2025
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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

3 authors at 2 institutions in 1 country.

Zihang XiangSchool of Systems Science, Beijing Normal University, Beijing, 100875, China.
Hao WangChina National Health Development Research Center, Beijing, 100044, China.
Handong LiSchool of Systems Science, Beijing Normal University, Beijing, 100875, China. lhd@bnu.edu.cn.
Beijing Normal University · CNChina National Health Development Research Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe risk of comorbid chronic diseases in elderly people is an important problem affecting their health and quality of life. We analyzed the incidence of chronic diseases for combinations of chronic diseases analyzed.

methodsWe used the original data to construct hypothetical cohorts of elderly individuals that evolved with age. The complex network was used to reduce the dimensionality of disease. The multistate transition model is used to calculate the incidence of each chronic disease, exploring comorbidity characteristics and rules.

results(1) By using complex network, seven chronic diseases were screened out in men, including hypertension, diabetes, heart disease, stroke, chronic lung disease, arthritis and dyslipidemia; six chronic diseases in women showed significant comorbidity except chronic lung disease. (2) Incidence show differences in age and sex; incidence of chronic diseases generally increased with age. (3) The marginal risk increases with the number of basic chronic diseases associated with comorbidities. (4) When hypertension is present as a basic disease, its impact on the risk of other chronic diseases is much less than that of other chronic diseases. (5) When diseases occur as basic chronic diseases, hypertension-heart disease and diabetes-dyslipidemia are combinations that have the greatest impact on each other in men; hypertension-heart disease in women.

conclusionsThe incidence of chronic diseases in patients who have chronic diseases and will form comorbidities differs from that in healthy states, and the related effects of different chronic diseases also differ. Among these conditions, hypertension is caused by a special mechanism.

Indexed as

Diabetes MellitusDyslipidemiasHeart DiseasesHypertensionLung DiseasesAgedChronic DiseaseComorbidityFemaleHumansMaleQuality of LifeChronic diseasesComorbidity riskComplex networkElderlyMultistate transition model

Identifiers

PMID38310224
PMCPMC10837928
OpenAlexW4391512674

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.