Evidence map›Paper›PMID 38166980›Full record

ArticleBMC public health2024

Association of physical activity with socio-economic status and chronic disease in older adults in China: cross-sectional findings from the survey of CLASS 2020 after the outbreak of COVID-19.

Yi Li, Mingyuan Cui, Yiqun Pang, Bing Zhan, Xiaotian Li, Qiurui Wang, Fang Chen, Zhixiong Zhou, Qingzhu 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 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
6.5field-weighted citation impact, top 3% 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

9 authors at 2 institutions in 1 country.

Yi LiCapital University of Physical Education and Sports, Beijing, 100000, China.
Mingyuan CuiCapital University of Physical Education and Sports, Beijing, 100000, China.
Yiqun PangSouthwest Petroleum University, Chengdu, 610000, China.
Bing ZhanCapital University of Physical Education and Sports, Beijing, 100000, China.
Xiaotian LiCapital University of Physical Education and Sports, Beijing, 100000, China.
Qiurui WangCapital University of Physical Education and Sports, Beijing, 100000, China.
Fang ChenCapital University of Physical Education and Sports, Beijing, 100000, China.
Zhixiong ZhouCapital University of Physical Education and Sports, Beijing, 100000, China. zhouzhixiong@cupes.edu.cn.
Qingzhu YangCapital University of Physical Education and Sports, Beijing, 100000, China. yangqingzhu@cupes.edu.cn.
Capital University of Physical Education and Sports · CNSouthwest Petroleum University · CN

Funding

National Key Research and Development Program of China No. 2020YFC2006200Young Elite Scientists Sponsorship Program by BAST No. BYESS2023383
6 · The paper itself

Abstract

backgroundIn 2021, China had a population of 264·01 million individuals over the age of 60, indicating a high prevalence of chronic diseases. Among older adults, physical inactivity (PI) is a significant risk factor for chronic diseases. However, few studies have been conducted on the correlation of physical activity (PA) with the economic status, geography and chronic disease risks in Chinese elderly. The objectives of this study were to better understand the distribution of PA among older adults in China and its relationship with economic status, geography, and chronic disease risks.

methodsThis study utilized data from the China Longitudinal Aging Social Survey (CLASS) in 2020, post-COVID-19. The study employed a stratified, multistage, probabilistic sampling approach and included 11,396 adults over the age of 59 from 28 provinces in China. Data on demographics, the duration and intensity of PA, history of diseases and personalized factors influencing PA were collected via structured interviews by researchers. In this study, we conducted a comprehensive analysis, employing a range of statistical methods including descriptive analysis, Wilcoxon rank-sum tests, Bayesian networks, and chi-square tests.

resultsThe prevalence of PI among older adults over 59 in China is 28·82%. Significant regional differences were observed in the duration of PA at different intensities. Older adults residing in more economically developed areas were more likely to engage in moderate-to-vigorous physical activity (MVPA) and exhibited longer sedentary behavior. Economic status and urban-rural disparities consistently emerged as direct influential factors across all intensity types. Chronic disease risks were significantly lower in active older adults compared to inactive ones. Lack of social guidance, family support, and personal inclination towards sedentary behavior were the main personalized factors affecting PA among older adults, and these factors could be relatively easily modified.

conclusionsEconomic status, geography, and living areas (urban and rural) significantly influenced the distribution of physical activities in China. Particularly, economic status and living areas acted as direct factors. Older adults reaching the recommended standards for PA had significantly lower chronic disease risks, highlighting the importance of improving personalized factors which are crucial for promoting PA.

Indexed as

COVID-19Economic StatusAgedAgingBayes TheoremChinaChronic DiseaseCross-Sectional StudiesDisease OutbreaksExerciseHumansAssociationOlder adultsPhysical activitySocio-economic

Identifiers

PMID38166980
PMCPMC10762973
OpenAlexW4390500277

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.