Evidence map›Paper›PMID 39011332›Full record

ArticleFrontiers in public health2024

Prevalence and pattern of multimorbidity in China: a cross-sectional study of 224,142 adults over 60 years old.

Xing Hu, Shugang Li, Zhimin Wei, Dishan Wu, Lingbing Meng, Jianyi Li, Jiapei Xu, Luyao Zhang, Qinan Ma, Hui Li and 4 more

Abstract read
In one paragraph

Article in Frontiers in 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
–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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
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

14 authors.

Xing HuHealth Service Department of the Guard Bureau of the Joint Staff Department, Beijing, China.
Shugang LiSchool of Public Health, Capital Medical University, Beijing, China.
Zhimin WeiHealth Service Department of the Guard Bureau of the Joint Staff Department, Beijing, China.
Dishan WuDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, National Health Commission Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Lingbing MengDepartment of Cardiology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
Jianyi LiDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, National Health Commission Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Jiapei XuDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, National Health Commission Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Luyao ZhangDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, National Health Commission Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Qinan MaDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, National Health Commission Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Hui LiDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, National Health Commission Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Xuezhai ZengDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, National Health Commission Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Qiuxia ZhangChina Research Center on Aging, Beijing, China.
Juan LiInstitute of Psychology, Chinese Academy of Sciences, Beijing, China.
Deping LiuDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, National Health Commission Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: To examine the prevalence and potential risk factors of multimorbidity among older adult in China. In addition, we investigated the pattern of multimorbidity. Methods: This study is based on data from the fourth Sample Survey of the Aged Population in Urban and Rural China (SSAPUR) in 2015, a comprehensive survey of individuals aged 60 years or older in China. We calculated baseline data and prevalence rates for comorbidities, stratified by household registration, age, sex, education, exercise, and health insurance. Univariate and multivariate logistic regression analyses were conducted to identify potential risk factors for comorbidities. Furthermore, we determined the prevalence rates for the three most frequent disease combinations. Results: A total of 215,040 participants were included in our analysis. The prevalence of multimorbidity was 50.5% among the older adult in China. The prevalence rate was slightly higher in rural areas than in urban areas, with rates of 51.5 and 49.6%, respectively ( Conclusion: Our findings indicate a high prevalence of multimorbidity among the older adult in China. Increased expenditure on preventive health care, popularization of general medicine and popular medical education may be adopted by the Government to cope with the high prevalence of multimorbidity.

Indexed as

MultimorbidityRural PopulationAgedAged, 80 and overChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrevalenceRisk FactorsSurveys and QuestionnairesUrban Populationepidemiologymultimorbiditypatterns of multimorbidityrisk factorsthe older adult

Identifiers

PMID39011332
PMCPMC11247643

What Socratic 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 Socratic graph.