Evidence map›Paper›PMID 42410375›Full record

ArticleBMC geriatrics2026

Prevalence and determinants of multimorbidity in older Chinese adults: a nationwide cross-sectional study using CLASS data.

Yi Li, Chenxi Zhao, Xinhao Zhuang, Songbo Jia, Xuelin Zhang, Liming Yan, Huaguang Zheng, Yiqun Pang, Bing Zhan, Xiaotian Li and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

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

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

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

16 authors.

Yi Li *Capital University of Physical Education and Sports, Beijing, 100191, China.
Chenxi Zhao *School of Sciences, Hebei University of Technology, Tianjin, 300401, China.
Xinhao Zhuang *Capital University of Physical Education and Sports, Beijing, 100191, China.
Songbo JiaCapital University of Physical Education and Sports, Beijing, 100191, China.
Xuelin ZhangCapital University of Physical Education and Sports, Beijing, 100191, China.
Liming YanSchool of Medicine, Tsinghua University, Beijing, 100084, China.
Huaguang ZhengBeijing Tiantan Hospital, Capital Medical University, Beijing, China.
Yiqun PangSchool of Physical Education, Southwest Petroleum University, Chengdu, Sichuan Province, 610000, China.
Bing ZhanCapital University of Physical Education and Sports, Beijing, 100191, China.
Xiaotian LiCapital University of Physical Education and Sports, Beijing, 100191, China.
Jinxi ZhangCapital University of Physical Education and Sports, Beijing, 100191, China.
John S JiVanke School of Public Health, Tsinghua University, Beijing, 100084, China.
Yanjun GuoSchool of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, 430030, China. yanjunguo@hust.edu.cn.
Bingxiang XuKey Laboratory of Hebei Province for Molecular Biophysics, Institute of Biophysics, School of Health Science & Biomedical Engineering, Hebei University of Technology, Tianjin, 300130, China. xubingxiang@sus.edu.cn.
Zhixiong ZhouCapital University of Physical Education and Sports, Beijing, 100191, China. zhouzhixiong@cupes.edu.cn.
Qingzhu YangCapital University of Physical Education and Sports, Beijing, 100191, China. yangqingzhu@cupes.edu.cn.ORCID 0000-0002-8107-0099

Funding

National Key Research and Development Program of China 2020YFC2006200National Natural Science Foundation of China 31771314National Program on Key Research Project of China 2024YFC2607300R&D Program of Guangzhou Laboratory GZNL2023A01008Science and Technology School Strengthen Project of CUPES 155225002/002Young Elite Scientists Sponsorship Program by BAST BYESS2023383
6 · The paper itself

Abstract

backgroundMultimorbidity, the coexistence of two or more chronic conditions, is rising in China's aging population, with limited data on prevalence and regional drivers.

methodsUsing 2020 China Longitudinal Aging Social Survey data for adults aged ≥ 60, supplemented by official regional statistics, we defined multimorbidity from 22 self-reported conditions. A Generalized Linear Mixed Model (GLMM) with village/community-level random effects was used to identify individual-level correlates of multimorbidity, while Random Forests (RF) evaluated county-level determinants.

resultsAmong 11,372 participants (mean [Standard Deviation, SD] 71.6 [6.6] years), 46.03% had multimorbidity. Higher odds of multimorbidity were associated with older age (Odds Ratio [OR] = 2.24; 95% Confidence Interval [CI] 1.81-2.76), female (OR = 1.32; 95% CI 1.20-1.45), receiving ≥ 3 social security benefits (OR = 1.64; 95% CI 1.09-2.48), and obesity (OR = 1.90; 95% CI 1.48-2.44). Lower odds were associated with higher educational level (OR = 0.55; 95% CI 0.39-0.75), being physically active (OR = 0.66; 95% CI 0.56-0.77), better access to medical institutions (OR = 0.67; 95% CI 0.45-0.99) and beds (OR = 0.55; 95% CI 0.37-0.80). Random Forests prioritized physical activity, disposable income, sleep duration, social security benefits, and Body Mass Index (BMI) as top county-level associated factors.

conclusionsThese insights advocate optimizing medical resources, bolstering primary care, and fostering healthy lifestyles to reduce the burden of multimorbidity among older Chinese adults.

Indexed as

East Asian PeopleMultimorbidityAgedAged, 80 and overChinaCross-Sectional StudiesFemaleHumansLongitudinal StudiesMaleMiddle AgedPrevalenceAssociated factorsChinese older adultsMedical resourcesMultimorbidityPrevalence

Identifiers

PMID42410375
PMCPMC13625285

What OpenQuestion holds

Textmetadata
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.